Jitney-Lite: a Low-Cost Strategy for Informal Flexible Feeder Service With

Jitney-lite: a low-cost strategy for informal ﬂexible feeder service with minimal technology

Tawit Sangveraphunsiri

A dissertation submitted in partial satisfaction of the

requirements for the degree of

Doctor of Philosophy

Engineering - Civil and Environmental Engineering

and the Designated Emphasis

Global Metropolitan studies

in the

Graduate Division

of the

University of California, Berkeley

Committee in charge:

Professor Michael Cassidy, Chair Professor Carlos Daganzo, Co-chair Professor Joan Walker Professor Marta Gonzalez

Spring 2021 Jitney-lite: a low-cost strategy for informal ﬂexible feeder service with minimal technology

Abstract

Jitney-lite: a low-cost strategy for informal ﬂexible feeder service with minimal technology

Tawit Sangveraphunsiri

Doctor of Philosophy in Engineering - Civil and Environmental Engineering

and the Designated Emphasis in

Global Metropolitan studies

University of California, Berkeley

Professor Michael Cassidy, Chair

Professor Carlos Daganzo, Co-chair

Efforts to provide informal, low-cost, flexible feeder services have occurred in many parts of the world. However, these services are often inefficient because informal operators cannot afford technologies for matching users and operators and efficiently routing vehicles. Transit riders are also concerned with the prices of technologies. This study develops a low-cost strategy for collective flexible feeder service, called the Jitney-lite service, that requires minimal technology. Our Jitney-lite bus operations offer door-to-door service to patrons who egress from a trunk-line transit system and fixed-route feeder service to those accessing the trunk-line system. This research formulated analytical models for this strategy, and the other two strategies exist in developing countries: (i) fixed-route bus and (ii) stand-based motorcycle taxi services. The cost evaluation starts from a level of a single trunk-line transit station by choosing the most cost-effective mode, and these costs are combined together for representing an entire city. The Bangkok Metropolitan Region (BMR) is used as a case study. The cost comparisons indicate that users who travel from a trunk-line transit station gain much benefits from the proposed strategy. The comparisons also indicate that Jitney-lite service is the most cost-effective in suburbs where zone size is large and trip density is low. The Jitney-lite is more favorable where residents earn low-to-middle incomes and/or where the quality of walking infrastructure is underdeveloped. i

To my parents for their love and support and to all my friends for their encouragement.

Without them, I cannot make my life this far. ii

Contents

Contents ii

List of Figures iv

List of Tables v

Acknowledgements vi

1 Introduction 1 1.1 Motivation ...... 1 1.2 Background and Scope ...... 2 1.2.1 Overview of informal-and-ﬂexible transport ...... 2 1.2.2 Scope of the study ...... 3 1.3 Literature Review ...... 4 1.4 Gap analysis ...... 4 1.5 Outline ...... 5

2 Feeder Strategies 6 2.1 Conventional feeder strategies ...... 6 2.1.1 Fixed-route bus service ...... 6 2.1.2 Stand-based motorcycle taxi service ...... 7 2.2 Proposed strategy: Jitney-lite service ...... 8

3 Predicting Performance of Feeder Strategies 10 3.1 Model setup and deﬁnitions ...... 10 3.2 Fixed-route bus model ...... 13 3.3 Stand-based motorcycle taxi model ...... 15 3.4 Jitney-lite model ...... 19

4 Modeling an Entire City 23 4.1 Selected characteristics of service zones ...... 23 4.2 Citywide model ...... 24 iii

5 Model Application 26 5.1 Background information ...... 26 5.2 Input data ...... 27 5.3 Conﬁgurations of the feeder system ...... 34 5.4 Cost comparisons ...... 37

6 Conclusions 39 6.1 Summary ...... 39 6.2 Future work ...... 40

Bibliography 42

A Variable list 47

B Value of inputs 50 B.1 Operating costs ...... 50 B.1.1 Distance-based operating costs ...... 50 B.1.2 Hourly operating costs ...... 51 B.2 Trip demand densities ...... 53 B.3 Values of in-vehicle time ...... 53

C Detail Results 65 iv

List of Figures

1.1 Informal-and-ﬂexible feeder and other types of transport ...... 3

2.1 A diagram of ﬁxed-route bus service ...... 7 2.2 A diagram of stand-based motorcycle taxi service ...... 8 2.3 A diagram of stand-based motorcycle taxi service ...... 9

3.1 An example of an idealized city and its trunk-line transit system . . . 11 3.2 An example service zone ...... 11 3.3 Example operations of ﬁxed-route buses ...... 13 3.4 Example operations of stand-based, motorcycle taxi service ...... 15 3.5 Catchment area of a stand ...... 16 3.6 State development of motorcycle taxis ...... 17 3.7 Example operations of Jitney-lite service ...... 20

5.1 Map of the BMR ...... 27 5.2 Map of BMR’s metro system in 2025 ...... 28 5.3 Types of informal transport in the BMR ...... 29 5.4 All service zones in the BMR ...... 31 5.5 Assigned income classes for all service zones ...... 32 5.6 Assigned levels of walking quality for all service zones ...... 33 5.7 System conﬁguration of the Proposed scenario ...... 35 5.8 Feeder strategies for each group in the Proposed scenario ...... 36 5.9 Cost comparison between two scenarios ...... 37 v

List of Tables

1.1 Classes of informal transport’s vehicle and services ...... 3

4.1 Selected characteristics and their variables ...... 23

5.1 Description of informal transport in the BMR ...... 29 5.2 Common input values ...... 30 5.3 Values representing income classes ...... 31 5.4 Values representing levels of walking-infrastructure quality ...... 33 5.5 Conﬁgurations and costs of the feeder system ...... 34

B.1 List of all operating costs ...... 53 B.2 List of all service zones and inputs ...... 55

C.1 Optimal results for Fixed-route bus service ...... 66 C.2 Optimal results for Stand-based Motorcycle Taxi service ...... 75 C.3 Optimal results for Jitney-lite service ...... 85 vi

Acknowledgments

This dissertation cannot be finished without the efforts, guidance, and supports of many, especially during the challenging time of the COVID-19 pandemic. Fore- most, I cannot express enough thanks to my leading advisor, Prof. Michael Cas- sidy, and my co-advisor, Prof. Carlos Daganzo, for the continuous support of my Ph.D. study and research. They always show me how a good researcher and teacher is and always available to support all their students. In addition, I would like to thank my research committee members – Prof. Joan Walker, and Prof. Marta Gonzalez – for the guidance and insight. The other people that I must express my appreciation for is Prof. Ipsita Banerjee, who support me for being her GSI of CE 259 for two years. I also acknowledge all research and financial supports of the Institute of Transportation Studies (ITS) and the Global Metropoli- tan Studies (GMS), University of California, Berkeley; and the Anandamahidol Foundation. Many of my Berkeley communities have also supported me throughout my study in the states. I am grateful for the fourth-floor research group at McLaughlin Hall and all my classmates in the first-floor office, who are too many to name. Special thanks to Ibrahim Itani, Bassel Sadek, Soomin Woo, Matthew Reither, Jiaxi Liu, Sili Kong, Jean Doig, and Lin Yang. I really appreciate all your help and assistance in my work and research, including my social life at Cal. I also thank my Thai communities in the Bay Area, Thailand and all over the world. They always emotionally support me during my out-of-work time here, especially P’Pim who always help and manage everything for me since the first day in the states, and also during the pandemic. I also thank to the classmates, teachers, and professors from my high school (Chulalongkorn University Demon- stration School), and my undergraduate university (Chulalongkorn University). I need to express regret for un-naming anyone here. If I name all of these valuable people here, this section would be ten-page long. I must take the time to show my gratitude to my lifelong advisor, Prof. Pisit Jarumaneeroj, who suggested me to apply for the scholarship in the first place for pursuing my graduate studies here at Cal. Lastly, I would like to show my most profound appreciation to my parents, Prof. Viboon and Chaleephan Sangveraphunsiri, who always support me to do what I want and follow my dream here. 1

Chapter 1

Introduction

1.1 Motivation

First-mile and last-mile connectivity play a significant role in a public transportation system. A feeder, which delivers connections between users and the system, should be organized and provided efficiently. Providing this sort of service remains a challenge in many parts of the world, especially in developing countries (Venter et al., 2019). Financial and institutional limitations preclude public agencies from themselves delivering first- and last-mile service. As a result, informal operators often emerge to fill gaps in feeder service. These operators possibly provide flexible service to their users (Cervero, 2000; Cervero & Golub, 2007), and these services are also responsive to their demand. A typical service is delivering collective trips by buses without a predetermined route or a schedule. This first- and last-mile service appears to benefit both users and operators because they combine the low fares of collective transport with the adaptive routing of private transport. However, informal operators rarely provide this flexible service efficiently. To improve the efficiency of this sort of flexible transit, advancement in technology have opened up an opportunity. Technology mainly helps match users with a driver in real-time, and find efficient routes for drivers. A recent example is the development of online applications in many parts of the world, such as Uber and Lyft in the U.S., Didi Chuxing in China, and Grab in Southeast Asia. On the other hand, the cost of providing flexible service increases due to these technologies. Informal operators can rarely afford this kind of technology because of its price. Hence, the improvement of informal-and-flexible service cannot be achieved. The above technologies of flexible service precludes some transit riders from taking this service because these riders are concerned with the price of fares and technology (Shaheen & Chan, 2016). Users also struggle with walking to access a feeder, because the development of walking infrastructure tends to be below- CHAPTER 1. INTRODUCTION 2 standard, especially in a suburb. The development of a low-cost flexible strategy with minimal technological assistance can be another alternative. It can improve the efficiency of feeder service operated by informal operators in developing countries.

1.2 Background and Scope

Given the above, this dissertation will explore how to deliver ﬂexible transit service with minimal technological assistance by informal operators. This section reviews current practices and related research on this topic. Then, the scope of this dissertation is provided here.

1.2.1 Overview of informal-and-flexible transport In this study, informal transport refers to service that is operated by private operators. A government or a central agency does not fully control these operators. A reader may find many interchangeable terms for this kind of transport. Paratransit is one of the popular terms. This term means “alongside transit” that comple- ments fixed-route transit without pre-defining a route and a timetable (Potts et al., 2010; Phun et al., 2019). Another term is Indigenous transport that was proposed in Mateo-Babiano (2016). The other recent term is LAMAT, which stands for Locally Adapted, Modified and Advanced Transport (Phun & Yai, 2016). In practice, forms of informal transport range from collective transport by fixed-route buses to for-hired, door-to-door service by taxis. The size of vehicles is related to a degree of flexibility, as shown in Table 1.1. Large vehicles, such as pickup trucks and minibus, contain several onboard users at a same time with delivering either a fixed- or a variable-route. Small vehicles, for example, motorcycles and tricycles, tend to be used for individual and for-hired trips. In a city that its trunk-line system, such as a metro rail and a fixed-route bus, has been developed, informal transport would have shifted to be a feeder (Pongprasert & Kubota, 2017; Phun et al., 2019). This study focuses on improving service that connects users and a metro station using large vehicles, such as pickup trucks. These vehicles generally have a capacity of 12 – 24 people, and its routes could be either fixed or variable. This form of an informal feeder can be categorized as a subset of collective flexible transit. An informal-and flexible transport can be diagrammed as shown in Figure 1.1 that is modified from Figure 7.1 in Daganzo & Ouyang (2019a). This kind of flexible transit provides an adaptive route and an adaptive schedule to several onboard users. It tends to be suitable where demand is between the effective level of demand for both individual transport and collective transport. CHAPTER 1. INTRODUCTION 3

Class Service features Passenger Routes Schedule Capacity Service niche Service coverage Minibus/jitney Fixed Semi-ﬁxed 12-24 Mixed Subregion Microbus/pickup Fixed Semi-ﬁxed 4-11 Distribution Subregion Three-wheeler/motorcycle Variable Variable 1-4 Feeder Neighborhood Pedicab/horse-cart Variable Variable 1-6 Feeder Neighborhood Source: Cervero (2000)

Table 1.1: Classes of informal transport’s vehicle and services

Source: Daganzo & Ouyang (2019a)

Figure 1.1: Informal-and-ﬂexible feeder and other types of transport

Examples of this informal transport are, such as; Song Thaeo and Silor Lek in Thailand, Matatu in Kenya, and Jeepney in the Philippines.

1.2.2 Scope of the study This dissertation only discusses the mechanism of providing informal-and-flexible feeder service. A low-cost strategy is proposed with minimal technological assistance, called Jitney-lite service. Apart from the proposed strategy, the other two strategies discussed here are providing feeder service by using fixed-route buses and motorcycle taxis. This study explores only when informal operators maximize net benefits to society. These operators are also assumed to be obedient to rules and instructions. This study therefore leaves how to encourage informal operators to adopt these strategies (e.g., determining an incentive) as future work. CHAPTER 1. INTRODUCTION 4

1.3 Literature Review

Collective flexible transit was first developed in the ’80s when technology was not advanced. Daganzo et al. (1977) and Daganzo (1978) developed a model to deliver one-to-many and many-to-many services, respectively. Daganzo (1984) proposed using checkpoints to pick-up and drop-off customers so that the buses can provide a closer to a door-to-door service. Checkpoints are advantageous because they can match users and operators with minimal technologies, and they can prevent buses from making long detours. Chang & Schonfeld (1991a) introduced a subscription service so a service provider can plan its operations several hours in advance. In this study, a service zone is equally subdivided to reduce the distance traveled per trip and improve the cost-effectiveness with minimal technological assistance. Another strategy entailed switching between flexible services and fixed- route services to suit different demand rates at different times of day (Chang & Schonfeld, 1991b). Unfortunately, this form of flexible service could not much improve the cost-effectiveness of collective flexible service. Only a small range of demand is suitable for delivering this kind of service. Since technology became more general in providing transit, further research only focuses on collective flexible service that is accompanied by technologies. However, this requirement tends to prevent informal operators from improving their service. This dissertation introduces these latter studies for the current practices of collective flexible transport. A velocity of buses can be real-time controlled when they deviate from a predetermined route (Quadrifoglio et al., 2006). Qiu et al. (2014), Stiglic et al. (2015) and Zheng et al. (2019) developed a dynamic station strategy that slows users to walk to temporary stops in a zone to reduce the number of rejected requests. A planner can determine each request specifically based on each user’s willingness-to-pay and plan a route (Pei et al., 2019). A switch between collective flexible and fixed-route services can also be made and informed to users directly (Quadrifoglio & Li, 2009; Li & Quadrifoglio, 2010; Kim & Schonfeld, 2012; Qiu et al., 2015; Kim et al., 2018). Recent work in Daganzo & Ouyang (2019a,b) presented a framework to model and compared some other collective flexible services practices. A reader can see some other practical experiences in Koffman (2004) and Potts et al. (2010).

1.4 Gap analysis

To fill gaps in the literature, this dissertation develops a low-cost strategy for collective flexible transit with minimal technological assistance. It is called Jitney-lite service in this dissertation because it allows a fixed-route Jitney, as in Table 1.1, to provide service that is closer to door-to-door trips. The model proposed here allows us to compare outcomes of the proposed strategy with those of existing feeder CHAPTER 1. INTRODUCTION 5 service by fixed-route buses and motorcycle taxis. This dissertation also further determines the appropriate circumstances for providing the proposed strategy. Generic-and-idealized models are developed to design and estimate the cost of providing all considered strategies. Apart from a model for the proposed strategy, this dissertation is the first study to formulate a model for motorcycle taxi service. The purpose is to support a planner to design a feeder strategy in any cities with a small number of inputs. A continuous-approximation framework is developed here with assuming that an operator maximizes net benefits to society. These generic models start with finding an optimal design and cost of providing a feeder to- and-from each trunk-line station. Each station’s minimum cost is then combined back to determine the average costs imposed on both users and operators in a case study.

1.5 Outline

This dissertation proposes a novel low-cost strategy for providing informal-and- flexible feeder service. Chapter 2 describes the proposed strategy and the other two considered strategies (i.e., fixed-route bus and stand-based motorcycle taxi services). Chapter 3 explains a modeling approach and how to analytically model incurred costs of all three service strategies in a representative of a single-station system. Then, how to measure the benefits of applying these strategies in an entire city is modeled in Chapter 4. The model application will be shown using a case study of Bangkok Metropolitan Region (BMR) in Chapter 5. Lastly, Chapter 6 summarizes the findings of the study and introduces the overview of future work. 6

Chapter 2

Feeder Strategies

This chapter describes the three feeder strategies of present interest, and how they are delivered with only minimal technology. Recall that the three strategies are (i) fixed-route bus, (ii) stand-based motorcycle taxi, and (iii) Jitney-lite. Each of these delivers feeder service to-and-from a single trunk-line station, called a terminal. We focus on the case that only one driver association, defined as a service provider, operates these strategies. Section 2.1 introduces conventional service delivered by fixed-route buses and motorcycle taxis. Description of the proposed Jitney-lite strategy follows in Section 2.2.

2.1 Conventional feeder strategies

Section 2.1.1 presents ﬁxed-route bus service, and Section 2.1.2 presents motorcycle taxi service provided with stands.

2.1.1 Fixed-route bus service Fixed-route bus service provides collective transport with routes and schedules that are predetermined. The buses depart from the terminal, and visit ﬁxed stops on their routes. After arriving at the route terminus, buses travel back by retracing the same route. Figure 2.1 diagrams this service. A service provider stores some buses at the terminal and at the route termini. These locations serve as control points for stabilizing schedules1. Buses are delayed by slack time at these points.

1Some control strategies can be applied here with minimal technologies, such as in Daganzo (2009), and Bartholdi & Eisenstein (2012). CHAPTER 2. FEEDER STRATEGIES 7

Figure 2.1: A diagram of ﬁxed-route bus service

2.1.2 Stand-based motorcycle taxi service Motorcycle taxi service provides only individual transport2. This dissertation focuses on only the case in which motorcycle taxis are operated with stands. Figure 2.2 diagrams this service. With minimal technology, users can access this service at either the terminal or at stands that reside in a zone. After departing from a trunk-line system at the terminal, an outbound user informs a driver of her destination, and travels there. A user in the opposite direction (i.e., inbound) walks to the nearest stand to access service. If a user arrives at this stand when it is empty of motorcycles, the user can call for service using a public phone installed at the stand3. A service provider stores motorcycles at both the terminal and stands. At the terminal, there are enough motorcycles to serve all users who travel outbound from the terminal, and to be dispatched to pick up users at empty stands. At each stand, there are enough motorcycles to ensure that a stand is rarely empty. The

2A reader can see some examples in Mo et al. (2014); Ratanawaraha & Chalermpong (2015); Ehebrecht et al. (2018) 3In some cases, such as when an inﬂow is more than an outﬂow at a stand, users may still have to wait for a motorcycle from the terminal. To reduce the probability that a user is waiting at a stand, we add one more motorcycle at each stand in our model formulation in the next chapter. CHAPTER 2. FEEDER STRATEGIES 8

Figure 2.2: A diagram of stand-based motorcycle taxi service service provider determines the maximum number of waiting motorcycles that are allowed at each stand. Users typically enjoy service inbound to the terminal with little time waiting at those stands. A motorcycle taxi goes through a cycle starting with its departure from a trunk-line system at the terminal. It picks up an outbound-from-terminal user at the terminal and drops her oﬀ directly at the destination. Then, the driver travels to the nearest stand to check whether or not the stand is full. If the stand is full of other motorcycles, the driver will travel back to the terminal without checking other stands. Otherwise, the driver waits for its turn to serve an inbound user at the stand.

2.2 Proposed strategy: Jitney-lite service

Jitney-lite service falls between collective transport by ﬁxed-route buses, and individual transport by motorcycle taxi service. Jitney-lite buses provide door-to-door service to users who travel outbound from the terminal; and ﬁxed-route service to users who travel in the inbound direction. Figure 2.3 diagrams this strategy. Jitney-lite service requires only minimal technologies because outbound users can individually inform drivers of their destinations while at the terminal. Users in CHAPTER 2. FEEDER STRATEGIES 9

Figure 2.3: A diagram of stand-based motorcycle taxi service the opposite direction get service by walking to the nearest bus stops and waiting there, just as in fixed-route bus service. A Jitney-lite bus waits for outbound users at the terminal, and departs from there in coordination with the trunk-line schedule. The driver then drops off all onboard users at their destinations one at a time. For those door-to-door trips, a Jitney-lite bus travels in a longitudinal direction without backtracking to a designated stop. The bus then deviates from a longitudinal direction when dropping off each user. After arriving at the route terminus, the bus travels back to the terminal following a predetermined route, and visits predefined stops along the route. A service provider stores buses at the terminal and termini, much as in fixed- route bus service. Jitney-lite buses are dispatched following schedules at these locations. A service provider can set these locations as control points, and assign slack time to delay buses there4. These control points are the same as what are applied in the fixed-route bus service in Section 2.1.1. At the terminal, there should always be at least one Jitney-lite bus per each predetermined route. At each terminus, there are enough buses so as to dispatch them according to schedules.

4Control strategies here are similar to those of ﬁxed-route bus service. 10

Chapter 3

Predicting Performance of Feeder Strategies

This section describes our building-block approach to design a feeder system to serve a trunk-line transit system that covers all or parts of a city. Each building block is a sub-model for a feeder system serving a single trunk-line station. A continuous approximation approach is used to describe building blocks. The same approach will be used in Chapter 4 to fit building blocks together. Section 3.1 presents the setup of a city used to design and evaluate our feeder strategies. Variables are defined in this section. The building-block models for fixed-route bus service, stand-based motorcycle taxi service, and Jitney-lite service are presented in Section 3.1, 3.2 and 3.3, respectively.

3.1 Model setup and deﬁnitions

The development of a feeder system in any large cities requires many steps. We first diagram by an idealized city with its trunk-line system in Figure 3.1. A modeler can downsize a design unit from an entire city (like in Figure 3.1) to that of a single trunk-line station. The latter are represented as stars in the figure. Each trunk-line station, called a terminal, connects to at most two building blocks (one on each side of the terminal) that define the terminal’s coverage area. Each block can be redrawn as a rectangular service zone, as shown in Figure 3.2. In this chapter, we focus on only feeder systems for a single zone. The feeder mode that serves the zone at the least generalized cost (to users and operators combined) is determined. We evaluate this cost for a full day in units of riding time per hour. Consider a rectangular service zone, R [km2], as shown in Figure 3.2, that is L km long, and W km wide. Note the terminal T that is located at the one end of the zone. The street configuration is assumed to be a grid with longitudi- CHAPTER 3. PREDICTING PERFORMANCE OF FEEDER STRATEGIES 11

Figure 3.1: An example of an idealized city and its trunk-line transit system

Figure 3.2: An example service zone CHAPTER 3. PREDICTING PERFORMANCE OF FEEDER STRATEGIES 12 nal and lateral street spacings sx [km] and sy [km], respectively. The trunk-line operator is assumed to provide information about a trip generating density, δk [pax-trip/km2-h], and its ﬁxed headway, Hk [h], for all periods in a day. The superscript k represents each period, and avg for a daily-average level. Subscript will be eventually added to variables to denote service mode: f for ﬁxed-route bus service, m for stand-based motorcycle taxi service, and j for Jitney-lite service. Demand is composed outbound and inbound trips. Demand in each direction is assumed to follow a Poisson distribution with rate pkδkLW pax-trip/h for one direction, and (1−pk)δkLW pax-trip/h for the other, respectively, where pk is the proportion of outbound trips. The spatial distribution of demand is assumed to be uniform over the zone. An average cost imposed on user, U k [h/pax-trip], is determined. This cost in each direction is the sum of (i) riding time, Rk [h/pax-trip], (ii) waiting time, W k [h/pax-trip], and access time, Ak [h/pax-trip]. Transfer cost from/to the terminal is negligible in this work. Hence,

k 1 k k k U = [βoA + βoW + βiR ], (3.1) βi where βi is a value of in-vehicle time per hour, and βo is a value of out-of-vehicle time per hour. Another superscript will be added to indicate trip direction: o for outbound trips; and i for inbound ones. Operating costs, Ck [h], are both distance-based and hourly. Distance-based costs cover expenditures on fuel and maintenance that are inﬂuenced by the total distance traveled by vehicles per hour, V k [vehicle-km/h]. Hourly costs include labor cost, overhead cost, and vehicle-depreciation cost. These are estimated knowing the daily ﬂeet size, M. A value of M is set to be more than a required number in each period, M k [vehicle]. Hence, 1 Ck = ($V V k + $M M), (3.2) βi where $V and $M are the monetary unit cost per distance and vehicle-hour, respectively. The day-long generalized cost, z/βi [h], is the weighted sum of user and operating costs in all periods. Each period is tk h long, and the total operating time is Tt h. Hence,

z X tk = [δkLW [pkU o,k + (1 − pk)U i,k] + Ck]. (3.3) βi Tt ∀k The goal of the following sections is to find a method for designing a system that will minimize the generalized cost in (3.3), and to predict its performance, as functions of the service zone’s characteristics. These characteristics include a CHAPTER 3. PREDICTING PERFORMANCE OF FEEDER STRATEGIES 13 zone’s size, the income of its residents and the quality of its infrastructure for walking. The method presented here takes the forms of an optimization problem. The service provider is assumed to perform efficiently, and the trip demand is fixed and given. A zone’s data will serve as input to our models, and the operator’s choices are decision variables.

3.2 Fixed-route bus model

Fixed-route bus service is diagrammed in Figure 3.3. A service planner seeks to determine an optimal number of routes, nf , and a day-long ﬂeet size, Mf . Each route covers a subzone with a width of W/nf km. The stop spacing is assumed to equal the longitudinal street spacing, sx km. Buses depart every ﬁxed headway of the trunk-line system. They travel from the terminal to the far end of each route, labeled E in Figure 3.3. The number of onboard users in each direction is assumed to be less than a bus’s passenger-carrying capacity, Of . Time lost due to stopping at each stop and serving each user is given by τ [h], and τ 0 [h], respectively. We start by formulating costs imposed on users. Outbound users travel, on average, the sum of (i) half of route length, L/2 km, and (ii) an average distance of ρ km from the terminal to a service route, where vt,f [km/h] is the operating speed of buses. Outbound users are also delayed, on average, by L/2sx stops and k k k p δ H LW/2nf users onboard. Thus, an average in-vehicle riding cost imposed on each outbound trip is given by

k k k o,k 1 L L p δ H LW 0 Rf = ρ + + τ + τ . (3.4) vt,f 2 2sx 2nf

Figure 3.3: Example operations of ﬁxed-route buses CHAPTER 3. PREDICTING PERFORMANCE OF FEEDER STRATEGIES 14 The only diﬀerence between the in-vehicle riding time per outbound trip and those of each inbound trip is the number of users onboard. Therefore,

k k k i,k 1 L L (1 − p )δ H LW 0 Rf = ρ + + τ + τ . (3.5) vt,f 2 2sx 2nf Outbound users walk from their origins to their nearest bus stops in the lateral direction for an average distance of W/4nf km, and in the longitudinal direction for an average distance of sx/4 km. The walking distance is the same for users who travel inbound to the terminal. Hence, o,k i,k 1 W sx Af = Af = + , (3.6) vw 4nf 4 where vw [km/h] is the walking speed. Inbound users wait for buses for a duration of half of the service headway on average, so 1 W i,k = Hk. (3.7) f 2 We next formulate expressions for estimating operating costs for the agency. k We express Vf [vehicle-km/h]. The total trip distance is twice the sum of ρ km, k and the route length of L km. Then, Vf is the product of the number of routes, k nf , the total trip distance, and the bus ﬂow, 1/H . Therefore, n V k = f [2(ρ + L)] . (3.8) f Hk On each route, total trip time is composed of (i) travel time per trip, (ii) lost time due to stopping at designing bus stops, and (iii) lost time due to serving users. Items (i) and (ii) are time-independent, and are 2(ρ + L)/vt,f h and 2Lτ/sx h, respectively. The upper-bound of Item (iii) can be approximated by the average number of onboard users per trip including a standard deviation. The upper- k bound trip time, Tf [h], can thus be approximated as

" k k k k 1/2# k ρ + L 2L δ H LW δ H LW 0 Tf = 2 + τ + + 2 τ . (3.9) vt,f sx nf nf

k k k As a result, Mf is the product of nf , Tf , and the bus ﬂow, 1/H . The expression k for Mf is: n M k = f T k. (3.10) f Hk f Then, the optimization problem can be formulated as follows: CHAPTER 3. PREDICTING PERFORMANCE OF FEEDER STRATEGIES 15 z min f , (3.11a) nf ,Mf βi

k s.t. Mf ≥ Mf , ∀k; (3.11b) pkδkHkLW (1 − pk)δkHkLW Of ≥ max , , ∀k; (3.11c) nf nf W ≥ nf ≥ 1; (3.11d) sy

Mf ≥ 1. (3.11e)

3.3 Stand-based motorcycle taxi model

Example tours for the motorcycle taxi service described in Section 2.1.2 are diagrammed in Figure 3.4. A service planner seeks an optimal number of stands, nm, s,k and a day-long ﬂeet size, Mm. A stand s has at most mi motorcycles waiting for inbound users in period k. All stands are identical and uniformly distributed over a zone. So, all stands limit the number of motorcycles at the same value of s,k mi . Figure 3.5 shows the square catchment area of each stand. Average costs imposed on each user are ﬁrst determined. All users travel an average distance of L/2 km in the longitudinal direction and W/4 km in the lateral direction. Hence, o,k i,k 1 L W 0 Rm = Rm = + + τ + τ , (3.12) vt,m 2 4

Figure 3.4: Example operations of stand-based, motorcycle taxi service CHAPTER 3. PREDICTING PERFORMANCE OF FEEDER STRATEGIES 16

Figure 3.5: Catchment area of a stand

where vt,m [km/hr] is the operating speed of motorcycles. Inbound users, on average, walk a quarter of each square catchment areas’ side, as shown in Figure 3.5. Therefore, 1/2 i,k 1 LW Am = . (3.13) 2vw nm If an inbound user arrives at the nearest stand when the stand is empty of motorcycles, average waiting time is the product of the proportion of time that users k arrive at empty stands, denoted pe , and a motorcycle’s average travel time from k the terminal to a stand. The values of pe will be analyzed later in this sub-section. Average waiting time is therefore expressed as

k i,k pe L W Wm = + . (3.14) vt,m 2 4 Analysis now moves to the agency’s operating costs. We start with a required k fleet size of motorcycles in period k, Mm. Formulas here are inspired by the stand- based flexible transport system in Daganzo & Ouyang (2019a). A motorcycle taxi can be in one of three states: (i) idle, (ii) assigned, and (iii) in-service, as diagrammed in Figure 3.6. Little’s formula (Little, 1961),m ¯ =µ ¯T¯ is used to determine the number of motorcycles in each state, where T¯ is the mean time spent in each state, andµ ¯ is the rate that motorcycle taxis move from one state k to another. In steady state period k,µ ¯ = δ LW/nm [pax-trip/h] for each stand. k Each of the mi idle motorcycles waits for users to arrive at the terminal or at stand s. We first focus on the number of idle motorcycles allowed at each stand, s,k mi . Assuming that both inflows and outflows are independent and mutually k k exclusive, the variation of users requesting service is δ H LW/nm (i.e., outflows s,k minus inflows). The mi is therefore the sum of 1 and twice the standard deviation. Then, k k 1/2 s,k δ H LW mi = 1 + 2 . (3.15) nm CHAPTER 3. PREDICTING PERFORMANCE OF FEEDER STRATEGIES 17

Figure 3.6: State development of motorcycle taxis

At the terminal, the number of idle motorcycles is the sum of an expected level of outbound trips and its standard deviation. Hence,

k s,k k k k k k k 1/2 mi = mi nm + p δ H LW + 2 p δ H LW . (3.16) k Assigned motorcycles numbering ma are dispatched to pick up users waiting at stands that are empty of motorcycles. We ﬁrst analyze a closed-form formula k for pe using a M/M/c/c queuing. This system considers arrivals of inbound users as its customer arrival process, and inter-arrivals of motorcycles traveling from the terminal as the service process. In an M/M/c/c queue, the ﬁrst M represents a Poisson arrival of customers; the second M represents an exponential service process; and the last two c represent the number of servers and the capacity of a stand, respectively, where c is the number of motorcycles allowed in each stand, s,k i.e., c = mi . If there are N > c users requesting service at a stand s, all N–c users will call and wait for motorcycles traveling from the terminal. We can estimate the proportion of time that a user is arriving at an empty stand by determining when all servers of the queue are occupied, as follows:

ms,k 1−pk i k k p pe = , (3.17) 1−pk s,k 1−pk exp pk Γ mi + 1, pk where Γ(a, b) is an upper incomplete-gamma function with parameters a and b. k The expected time spent in this state, Tm,a [h], is given by the product of (3.17), the proportion of inbound trips, 1 − pk, and the motorcycle’s average trip time from the terminal. Hence, k k k pe (1 − p ) L W Tm,a = + . (3.18) vt,m 2 4 CHAPTER 3. PREDICTING PERFORMANCE OF FEEDER STRATEGIES 18

k k k The ma is then the product of nm, Tm,a, and δ LW/nm (i.e. the trip demand per each stand). Hence, k k k ma = δ LW Tm,a. (3.19) k In-service motorcycles numbering ms are comprised of motorcycles that travel (i) with users, (ii) to the nearest stand after dropping off an outbound user, and (iii) back to the terminal if they arrive at stands filled with other motorcycles. Before analyzing the average time spent for each item, we first focus on the prob- k ability that a motorcycle taxi arrives at a full stand, denoted pf . A queuing k system is used here to estimate pf . This queuing system considers arrivals of motorcycles from the terminal as the customer arrival process, and inter-arrivals of inbound users at a stand as the service process. The M/M/1/c is used to obtain k a closed-form formula for pf . In this system, the first M denotes Poisson arrivals of customers at a stand; the second M represents the exponential service process; 1 represents a single-server queue, and c represents the number of motorcycles k allowed in each stand, as in the derivation of pe . This system is a single-server system because motorcycles are dispatched one at a time according to the arrivals k of inbound users at a stand. The expression of pf is thus

s,k  m k i k  (p ) (1−2p ) k  s,k s,k , if p 6= 0.5;  m +1 m +1 k k i k i pf = (1−p ) −(p ) (3.20)  1 k  s,k , if p = 0.5; mi +1 We next focus on the average time spent for each item. For Item (i), each motorcycle travels an average distance of L/2 + W/4 km with a user, including τ h and τ 0 h. For Item (ii), after dropping oﬀ a user, a motorcycle taxi travels an 1/2 average distance of 0.5(LW/nm) km to the nearest stand. For Item (iii), if the stand is full, the motorcycle travels back to the terminal for an average distance k of L/2 + W/4 km. Average time spent in each state, Tm,s [h], is given by the sum of the expected time for Items (i) – (iii). Then,

" k 1/2# k 1 k k L W p LW 0 Tm,s = 1 + p pf + + + τ + τ . (3.21) vt,m 2 4 2 nm

k k k The number of in-service motorcycles, ms , is the product of nm, Tm,s, and δ LW/nm. Hence, k k k ms = δ LW Tm,s. (3.22) k The total distance traveled by motorcycles per hour, Vm [vehicle-km/h], and k k the required ﬂeet size, Mm, are derived next. The Vm is the product of the motorcycle’s average trip distance, including the vehicle’s reposition, and the hourly CHAPTER 3. PREDICTING PERFORMANCE OF FEEDER STRATEGIES 19 trip demand. Therefore,

" k 1/2# k k k k k k L W p LW Vm = δ LW 1 + p pf + 1 − p pe + + . (3.23) 2 4 2 nm

k k The Mm is the sum of (3.15), (3.18), and (3.21). Therefore, Mm is expressed as

k h k k k k k k 1/2i k k 1/2 Mm = p δ H LW + 2 p δ H LW + nm + 2(δ H LW nm) + " " k 1/2# # k 1 k k k k L W p LW 0 δ LW (1 + p pf + 1 − p pe )( + ) + + τ + τ . vt,m 2 4 2 nm (3.24)

The optimization problem can now be formulated as follows: z min m , (3.25a) nm,Mm βi

k s.t. Mm ≥ Mm, ∀k; (3.25b)

nm ≥ 1; (3.25c)

Mm ≥ 1. (3.25d)

3.4 Jitney-lite model

The Jitney-lite service strategy partitions a zone into several elongated subzones; see the example in Figure 3.7 with two subzones. A service planner therefore seeks an optimal number of subzones, nj, and a day-long ﬂeet size, Mj. Each subzone has a width of W/nj km that is not narrower than the lateral street spacing of sy km. As a result, the lateral distance traveled per user is restricted by the subzone’s width. The Jitney-lite buses wait for outbound users and depart every Hk. The spacing between bus stops on a way back to the terminal is assumed to be given by the longitudinal street spacing, sx. The number of onboard users in 0 each direction is less than the bus’s carrying capacity, Oj. The τ and τ are added per each stop and per each user, respectively. We again start by formulating costs imposed on users. Users who travel from the terminal incur only in-vehicle riding time. Average travel time is determined by (i) an average distance from the terminal to a subzone, ρ [km], (ii) a longitudinal distance of L/2 km, and (iii) an average lateral distance. Item (iii) is given by the product of the lateral distance W/3nj km per user, and half the number of CHAPTER 3. PREDICTING PERFORMANCE OF FEEDER STRATEGIES 20

Figure 3.7: Example operations of Jitney-lite service

k k k outboard users per trip, i.e., p δ H LW/2nj [km]. The average in-vehicle riding time imposed on outbound users is given by:

k k k o,k 1 L p δ H LW W 0 Rj = ρ + + + τ + τ ), (3.26) vt,j 2 2nj 3njvt,j where vt,j [km/h] is the operating speed of Jitney-lite buses. Inbound users travel half of a predetermined route and an average distance from a subzone to the terminal, L/2 + ρ [km]. A Jitney-lite bus decelerates and accelerates to stop at k k k L/2sx bus stops, and for (1 − p )δ H LW/2nj onboard users on average. Hence,

k k k o,k 1 L L (1 − p )δ H LW 0 Rj = ρ + + τ + τ . (3.27) vt,j 2 2sx 2nj Each of inbound user walks, on average, half the maximum distance from an origin to the terminal, W/2nj + sx/2 [km]. Hence, i,k 1 W sx Aj = + . (3.28) 2vw 2nj 2 Average waiting time can be approximated as half of a headway, as thus 1 W i,k = Hk. (3.29) j 2

k We now approximate operating costs in each period, ﬁrst by expressing Vj [vehicle-km/h]. An average trip distance is the sum of 2(ρ + L) km in the longi- k k k tudinal direction, and W/3nj km per user with p δ H LW/nj users in the lateral CHAPTER 3. PREDICTING PERFORMANCE OF FEEDER STRATEGIES 21

k direction. The Vj is then the product of the number of subzones, nj, the bus ﬂow, 1/Hk, and the total trip distance. Therefore,

k k k 2 k nj p δ H LW Vj = k 2 (ρ + L) + 2 . (3.30) H 3nj

k The expression for Mj is as follows. The trip time is composed of travel time (i) in the longitudinal direction, (ii) in the lateral direction, and lost time due to (iii) stops and (iv) users. Item (i) is fixed, and can be approximated as 2(ρ + L)/vt,j h. The upper-bound on Item (ii) includes fluctuations in demand and in distance traveled between two consecutive destinations for outbound users. The standard deviation of the distance between two points in the lateral direction is therefore k k 1/2 (W/nj)[(nj/p δ LW + 1)/18] km per stop. The value for Item (iii) fluctuates only by the number of outbound users per trip. Lastly, Item (iv) includes the k standard deviation of trip demand rate. Then, the upper-bound trip time, Tj [h], can be expressed as the sum of Item (i) – (iv) as follows:

" 1/2!# k 1 k k k 2 1 1 2 nj Tj = 2 (ρ + L) + p δ H LW + 2 k k + 1 vt,j 3 nj 9 p δ LW ! pkδkHkLW pkδkHkLW 1/2 L + + 2 + τ nj nj sx ! δkHkLW δkHkLW 1/2 + + 2 τ 0. nj nj (3.31)

k The expression for Mj is the product of the number of subzones, nj, the upper- k k bound trip time, Tj , and the bus ﬂow, 1/H . Therefore,

T k M k = n j . (3.32) j j Hk The optimization problem can be formulated as follows: z min j , (3.33a) nj ,Mj βi

k s.t. Mj ≥ Mj , ∀k; (3.33b) pkδkHkLW (1 − pk)δkHkLW Oj ≥ max , , ∀k; (3.33c) nj nj W ≥ nj ≥ 1; (3.33d) sy CHAPTER 3. PREDICTING PERFORMANCE OF FEEDER STRATEGIES 22

Mj ≥ 1. (3.33e) The mathematical programs formulated in this chapter are our modeling building blocks. The next chapter will show how to use these building blocks to design a feeder system, and evaluate its performance over an entire city. 23

Chapter 4

Modeling an Entire City

In Chapter 3, we determined the conﬁguration of a feeder system, and its cost for all building blocks. All blocks’ costs are combined in the present chapter to estimate the day-long generalized cost of an entire city or parts of the city. To obtain these results, the mathematical programs use the service zone’s characteristics as input variables and the operator’s choices as decision variables. Section 4.1 describes all selected characteristics of service zones that are used as inputs to the models. Section 4.2 formulates a citywide model and describes two scenarios that are used to evaluate the cost-eﬀectiveness of a feeder system.

4.1 Selected characteristics of service zones

This section introduces all selected characteristics that reflect the heterogeneity of service zones. The goal is to reflect the setting, and the characteristics of demand for each service zone as realistically as possible. Table 4.1 enumerates the characteristics and the variables representing them. The first characteristic is a trip demand density, δavg [pax-trip/km2-h]. It reflects the number of transit riders requesting feeder service in each building

Characteristic Variable Trip demand density δavg Length of a service zone L Width of a service zone W Resident’s income βi Walking quality βo/βi

Table 4.1: Selected characteristics and their variables CHAPTER 4. MODELING AN ENTIRE CITY 24 block. This value is set as the target for a service provider. A population density can be used to estimate the value of the trip density in each building block. The length, L, and width, W , of a service zone are two other characteristics. These affect not only a trip length, but also the number of transit riders requesting feeder service. Since all building blocks are redrawn as rectangular zones, we can easily measure these two variables. The width corresponds to a zone’s side where a terminal is located, and the length is the other side. The other two characteristics, resident’s income and walking quality, reflect perceived values of both the in-vehicle and out-vehicle time for transit riders, i.e., βi and βo respectively. If both values are high, transit riders prefer to spend less time in travel. We use three classes of neighborhoods that are based on an average resident’s income: (i) low-income, (ii) middle-income, and (iii) high-income. For walking quality, there are two classes: (i) medium-quality and (ii) poor-quality. We first estimate a value of in-vehicle time by the average income of transit riders residing in a service zone. We multiply it with a value representing walking quality to estimate a value of out-vehicle time. After assigning values to the selected variables of all service zones, a day- long generalized cost for an entire city is determined as described in the following section. The method can find an optimal feeder-system configuration for an entire city using the models in Chapter 3. All building blocks are then combined to determine the day-long generalized cost for the city.

4.2 Citywide model

To evaluate the improvement in cost-effectiveness, we will compare the proposed feeder system’s performance (i.e., Proposed scenario) with a scenario representing the status quo, or Conventional scenario. The latter scenario is when all service zones are served by fixed-route buses only. Either the Jitney-lite or the motorcycle taxi strategy likely produces a lower cost than the conventional strategy in at least one zone of a city. As a result, the Conventional scenario’s total cost is always greater than or equal to that of the Proposed scenario. Once obtaining the day- long generalized costs for an entire city for both scenarios, we compare these two costs together and determine the improvement in the cost-effectiveness for a feeder system of the Proposed scenario. The day-long generalized cost for an entire city is measured in a converted unit of riding time per passenger-trip. It is denoted ztot [h/pax-trip]. When necessary to avoid ambiguity, a subscript will be added to indicate the scenario: (i) con for the Conventional scenario, and (ii) pro for the Proposed scenario. We first determine the total passenger-trip rate for the entire city, Λavg [pax-trip/h]. Since avg avg the trip rate in building block r is given by δr LrWr [pax-trip/h], Λ is easily CHAPTER 4. MODELING AN ENTIRE CITY 25 derived by summing all building blocks together. Therefore,

avg X avg Λ = δr LrWr. (4.1) ∀r

tot avg We then formulate z . Since the day-long generalized cost for a block r, zr tot avg avg [h], is given by the models in Chapter 3, z is the sum of zr divided by Λ . Hence, 1 X ztot = zavg. (4.2) Λavg r ∀r We compare the day-long generalized costs of two scenarios to measure the improvement in the cost-eﬀectiveness of a feeder system. The next chapter will show an application of the models formulated in Chapters 3 and 4 to a case study of the Bangkok Metropolitan Region. 26

Chapter 5

Model Application

This chapter applies the previously-formulated models to the Bangkok Metropoli- tan Region (BMR). We focus on only the suburb of the BMR, because transit riders tend to travel to-and-from the CBD using the trunk-line transit system. The assignment of input values for all building blocks follows the ideas described in Chapter 4. Recall that in a Proposed scenario, the feeder mode that generates the lowest day-long generalized cost is the one chosen for each service zone; and in the Conventional scenario, all zones are served by ﬁxed-route buses. Background information on the BMR is given in Section 5.1, and the input data for the BMR in Section 5.2. The feeder system and its costs for both the Proposed and Conven- tional scenarios are presented in Section 5.3. Cost comparisons of both scenarios follow in Section 5.4.

5.1 Background information

The BMR provides inspiration of sorts for applying flexible collective service. This region is located at the center of Thailand. It includes Bangkok and the other five surrounding provinces shown in Figure 5.1. According to its Travel Demand Survey (Office of Transport and Traffic Policy and Planning, 2018), about 15 million people resided there in 2017. Each resident generates 1.97 trips daily, so there are about 28 million passenger-trips per day in the region. About 60% of trips travel from/to the CBD. The survey also indicates that about 30% of transit riders’ trips include taking taxis and walking, 40% are made by personal cars, and the remaining 30% by motorcycles. Since the BMR’s metro was opened in late 1999, it has become the backbone of the region’s transit system. At the final phase of development (2042), the system is expected to have 557 km of metro lines and 302 stations. The only parts of the system shown in Figure 5.2 are those now approved and under construction, all of which are expected to be opened by 2025. By that time, there will be about CHAPTER 5. MODEL APPLICATION 27

Figure 5.1: Map of the BMR

390 km of rail and 195 stations. The BMR’s metro system in 2025 is used as our focus. Although the metro system is expanding throughout the region, people who reside outside the system’s catchment area struggle with walking or taking transit to the metro. Several informal transport types have emerged to ﬁll these gaps. There are three classes of informal transport in the BMR. Figure 5.3 and Table 5.1 show and describe the service types and vehicles in use for these informal services. Our focus is on services that use pickup trucks (i.e., Song Thaeo) for Jitney-lite and ﬁxed-route bus services, and motorcycles for taxi service.

5.2 Input data

All inputs are shown in Table 5.2, and are common over the BMR. Apart from these common inputs, the inputs that are diﬀerently assigned for each zone are described later in this section as follows: (i) a trip density, (ii) a length of a zone, CHAPTER 5. MODEL APPLICATION 28

Source: Department of Rail Transport (2019)

Figure 5.2: Map of BMR’s metro system in 2025

(iii) a width of a zone, (iv) a resident’s income, and (v) a quality of zone’s walking infrastructure. A reader can see their derivations in detail in Appendix B. We ﬁrst analyze dimensions of all service zones in the BMR. Of the 195 metro stations scheduled for 2025, 123 stations are in the suburb. As shown in Figure 5.4(a), there is a total of 216 service zones. The trip density in each service zone is derived from the population density available from the WorldPop dataset (WorldPop & Columbia University, 2020). These densities range from 9.73 to 241.76 pax-trip/km2-h. The sizes of service zones vary from 0.59 to 92.05 km2. The scatter plot in Figure 5.4(b) displays the relationship between service zone sizes and the trip densities. Each data point represents an individual service zone. The zones connected with terminals that are far away from the CBD are generally larger and their trip densities are typically lower than zones residing close to the CBD. CHAPTER 5. MODEL APPLICATION 29

(a) Motorcycle (Google Maps, 2019a) (b) Tuk tuk (Google Maps, 2014)

(e) Passenger van (Google Maps, 2019c)

Figure 5.3: Types of informal transport in the BMR

Class Vehicle Service features Passenger Routes Schedules Capacity For-hired two-wheeler (a) Motorcycle Variable Variable 1-2 For-hired three-wheeler (b) Tuk tuk Variable Variable 2-4 Four-wheeler (c) Silor lek Variable Semi-fixed 6-11 Pickup truck (d) Fixed Semi-fixed 12-20 (Song Thaeo) (e) Passenger van Fixed Semi-fixed 4-14

Source: Choocharukul & Sriroongvikrai (2011); Mo et al. (2014); Phun & Yai (2016); Chalermpong et al. (2016); Amrapala & Choocharukul (2019)

Table 5.1: Description of informal transport in the BMR CHAPTER 5. MODEL APPLICATION 30

Input

Longitudinal street spacing sx 0.5 km Lateral street spacing sy 0.25 km km Walking speed vw 3 /h Time lost per stop τ 0.0095 h Time lost per passenger τ 0 0.0005 h Operating speed km Jitney-lite buses vt,j 25 /h km Fixed-route buses vt,f 25 /h km Motorcycle taxis vt,m 35 /h Operating cost per unit distance V THB Jitney-lite buses $j 8 /veh-km V THB Fixed-route buses $f 8 /veh-km V THB Motorcycle taxis $m 2 /veh-km Operating cost per veh-hour M THB Jitney-lite buses $j 171 /veh-h M THB Fixed-route buses $f 171 /veh-h M THB Motorcycle taxis $m 130 /veh-h Headway of a trunk-line service Morning peak Hmp 0.067 h Off-peak Hop 0.133 h Evening-peak Hep 0.067 h Proportion of outbound users Morning peak pmp 0.2 - Off-peak pop 0.5 - Evening-peak pep 0.8 - Time period Morning peak tmp 3 h Off-peak top 12 h Evening peak tep 3 h Entire day Tt 18 h

Table 5.2: Common input values CHAPTER 5. MODEL APPLICATION 31

(a) Service zones (b) Scatter plot: zone sizes VS trip densities

Figure 5.4: All service zones in the BMR

βi [THB/h] Low-income 35 Middle-income 81 High-income 161

Table 5.3: Values representing income classes

Two other characteristics are chosen to reflect a perceived value of time for users in each service zone. These two characteristics are (i) an average income of residents in each service zone and (ii) the quality of a zone’s infrastructure for walking. The values of all income classes are shown in Table 5.3. An income value is randomly assigned to each block. Although this assignment does not reflect the actual setting in BMR, it helps us evaluate how all considered feeder strategies are affected by income. Figure 5.5 displays the assignment of the residents’ income classes. The other input is a perceived out-of-vehicle value of time that is derived from CHAPTER 5. MODEL APPLICATION 32

Figure 5.5: Assigned income classes for all service zones

the quality of a zone’s walking infrastructure. Table 5.4 shows the values of βo/βi, representing walking quality in the BMR. A value is systematically assigned for each zone based on its location. Service zones near the CBD are assumed to have better infrastructure (i.e., medium-quality). This denotes that a sidewalk is available, also with facilities (e.g., streetlights and footpaths), but it may be of lower quality than in CBD. The other level is poor-quality, denoting a zone in which walking is a struggle; i.e., people need to walk on a street, and thus mix with automobiles. A streetlight is seldom found there. Figure 5.6 shows the assignment of this input. Once all input data are furnished for all building blocks, conﬁgurations of the BMR’s feeder system and their costs are determined. These determinations are made below. CHAPTER 5. MODEL APPLICATION 33

β o/βi Medium-quality 3 Poor-quality 5

Table 5.4: Values representing levels of walking-infrastructure quality

Figure 5.6: Assigned levels of walking quality for all service zones CHAPTER 5. MODEL APPLICATION 34

Conventional Proposed Number of zones Fixed-route 216 79 Motor-taxi 0 3 Jitney-lite 0 134 Day-long generalized cost 55.53 49.96 [min/pax-trip] User cost Total 39.5 31.04 [min/pax-trip] Outbound 16.96 8.57 Inbound 22.54 22.47 Agency cost 16.03 18.92 [min/pax-trip]

Table 5.5: Conﬁgurations and costs of the feeder system

5.3 Conﬁgurations of the feeder system

This section presents a configuration of the BMR’s feeder system for both Pro- posed and Conventional scenarios. Recall the idea in Chapter 4: we first evaluate all three modes and find the most cost-effective one for each service zone. Once obtaining obtained the modes and minimum costs for all zones, we combine these costs together to represent the Proposed scenario. The day-long generalized costs for delivering fixed-route bus service in all zones constitute the Conventional scenario. Results for both scenarios are shown in Table 5.5. A reader can see more detailed results in Appendix C. In the Conventional scenario, the costs of the feeder system generate the minimum total cost at 55.53 minutes per passenger-trip. The total cost imposed on each passenger-trip is 39.50 min/pax-trip. The fixed-route bus service imposes costs on each outbound and inbound user of about 16.96 and 22.54 min/pax-trip, respectively. When the generalized cost is minimum, a service provider needs to pay 16.03 min/pax-trip. For the Proposed scenario, the results in Table 5.5 show that the Jitney-lite strategy generally outperforms the other strategies. There are 134 zones out of the 216 where the Jitney-lite is the most cost-effective option (i.e., 62.04%). The fixed-route bus strategy is best for 79 zones, and the stand-based motorcycle taxi strategy for only 3 zones. The minimum day-long generalized cost per trip in the region is 49.96 min/pax-trip. The feeder system imposes costs on each outbound and inbound user of about 8.57 and 22.47 min/pax-trip, respectively. When the generalized cost is minimum, a service provider pays 18.92 min/pax-trip. CHAPTER 5. MODEL APPLICATION 35

Figure 5.7: System conﬁguration of the Proposed scenario

The results reveal that the Jitney-lite strategy is suitable in outer zones, where their sizes are large and trip densities are relatively low. Figure 5.7 shows where and which strategy outperforms the other alternatives presented in this research. We divide all service zones into six groups for analyzing the characteristics of the zones that are suited for the Jitney-lite strategy. Each group represents a combination of a resident’s income class and a level of walking quality. Figure 5.8 additionally addresses the relationship between zone sizes and trip densities for all groups. A pie chart for each group in this figure shows the proportion of zones where a particular strategy generates the lowest total cost. In zones where residents earn low wages, the fixed-route bus strategy is generally the most cost-effective option. However, the Jitney-lite strategy turns out to be the most cost-effective option in large-sized zones, especially where transit riders struggle CHAPTER 5. MODEL APPLICATION 36

Figure 5.8: Feeder strategies for each group in the Proposed scenario CHAPTER 5. MODEL APPLICATION 37 with walking. For middle-income residents, the Jitney-lite strategy becomes more cost-eﬀective than it does where residents earn low income. Where residents earn high income, the Jitney-lite strategy is the dominant one, regardless of walking quality. There are only a few zones that the motorcycle-taxi strategy outperforms the other two. Those zones are relatively small in size, and their trip densities are relatively low. Apart from being an exclusive strategy for a zone, motorcycle taxis can be provided as complementary service for users who earn high wages.

5.4 Cost comparisons

This section compares the cost-eﬀectiveness of the Proposed scenario with that of the Conventional one. Figure 5.9 diagrams the costs of both scenarios. The Proposed scenario incurs a city-level generalized cost at 49.96 min/pax-trip, and is roughly 10% lower than that of the Conventional scenario. In the Proposed scenario, the average cost per each outbound trip is about half that of the Con- ventional scenario. However, the average cost per inbound trip of both scenarios is slightly diﬀerent by only 0.07 min/pax-trip. A service provider pays about 18% more to deliver all three strategies in the Proposed scenario than in the Conven- tional scenario.

Figure 5.9: Cost comparison between two scenarios CHAPTER 5. MODEL APPLICATION 38

The finding from this analysis confirms that the Jitney-lite strategy combines low operating cost of collective transport and low user cost of demand-responsive transport. The expected cost imposed on users is lower in the Proposed scenario than in the Conventional one. The cost of the Proposed scenario imposed on the transit provider is higher than that of the other scenario, however. The results further show that users who travel from a terminal gain more benefits from the Jitney-lite strategy. However, users in the opposite direction tend not to gain much benefit, because inbound users still need to walk and wait for feeder service. Due to customized requests of users, a service provider needs to pay more for delivering a feeder system in the Proposed scenario. Implementing the Jitney-lite strategy thus helps improve the cost-effectiveness of the BMR’s feeder system. This strategy plays a dominant role and outperforms the other alternatives where residents earn middle-to-high wages and/or walking infrastructure is underdeveloped. Although a service provider pays more to furnish this strategy, outbound users from a terminal enjoy a feeder that is closer to door- to-door service. 39

Chapter 6

Conclusions

Research ﬁndings and insights are summarized in Section 6.1. Future work is introduced in Section 6.2.

6.1 Summary

This dissertation proposed a novel strategy, called Jitney-lite, for providing collective-flexible feeder service with minimal technology. The strategy allows a driver to provide door-to-door service to users who travel from a terminal. Users traveling in the opposite direction receive fixed-route feeder service. Transit users can access the Jitney-lite buses without any communication devices. Furthermore, since the Jitney-lite strategy is low-tech and inexpensive, informal operators in developing countries can easily adopt it. Transit riders benefit from door-to-door service, along with low fares. Analytical models were formulated to evaluate the Jitney-lite strategy, as well as two conventional feeder forms: fixed-route buses and stand-based motorcycle taxis. A building-block approach was used in which the city-wide models were decomposed into possibly many sub-models. Each of the three feeder forms were optimized and evaluated in each service zone. Characteristics of each zone and of the transit users were considered. The feeder form that minimized day-long generalized cost for a service zone was presented to be implemented in that zone. Day-long costs for the city were determined by summing resulting costs across all service zones. That cost was compared against the cost of serving all zones via fixed-route feeder buses. Inputs from the Bangkok Metropolitan Region (BMR) were used as a case study. The Jitney-lite strategy was found to be suitable in suburbs where service zone size is large and trip density is low. Furthermore, our Jitney-lite strategy was more favorable where residents earn middle-to-high incomes, and/or where CHAPTER 6. CONCLUSIONS 40 the quality of walking infrastructure is underdeveloped. In the case of BMR, more than half (62.04%) of the zones were best served by the Jitney-lite strategy. Cost comparisons confirm that users who travel outbound from a terminal obtain significant benefits from our Jitney-lite strategy, and that the added costs to operators are small by comparison. These users can save travel times by the door-to-door service, despite having to share trips with other onboard users. Users who travel inbound to the terminal still need to walk and wait for feeder service. So, the cost imposed on inbound users is almost unchanged. A service provider needs to pay a little more to furnish this proposed strategy.

6.2 Future work

The results presented here are still limited in scope, primarily because our models simplified the mechanisms of feeder service. Additional decision variables could be used for greater realism. Vehicle headway could be included in recognition that synchronization between trunk-line and feeder services is hard to implement. This would enable a service provider to adjust service frequencies to optimally suit trip demand. Further studies may also account for a vehicle size in the models. In the present study, it was assumed that only pickup trucks with a capacity of 18 people were used for providing our feeder service. In reality, a service provider can change vehicle size to better suit trip demand. Consideration of vehicle size might, therefore, improve the cost-effectiveness of a feeder system. The current study also ignored externalities that informal operators typically impose on society. This kind of transport induces heavy congestion with high emissions, and also safety concerns. Inclusion of these considerations in the models would reflect the impacts of informal operators more realistically. Future research might also consider service competition, since informal operators generally compete among themselves. In these cases, operators maximize profits or revenues, instead of social benefits. Since a government would like to regulate, subsidize or integrate informal operators into its transit plan, we might do well to include these plans in an analysis. These considerations will ensure maximum benefits to society. Future research could further consider the potential effects of intra-zonal user heterogeneity. Unlike in the present study, users within a service zone are typically diverse, especially in their income. The in-vehicle and out-vehicle times are therefore perceived differently among transit riders. As a result of this diversity, optimum access for a zone may not be provided as a single mode, as in this thesis. Additional research should explore the possibility of using more than one mode in some of the zones. Another investigation can be conducted when demand is sensitive to a fare and a feeder configuration. We might treat trip demand as a CHAPTER 6. CONCLUSIONS 41 constraint in the models, and form the demand level as a function of the decision variables. 42

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Appendix A

Variable list

THB βi = Value of in-vehicle time [ /h] THB βo = Value of out-vehicle time [ /h] avg pax-trip 2 δr = Daily-average trip demand density for zone r [ /km -h] k pax-trip 2 δr = Average trip demand density in period k for zone [ /km -h] r avg Λ = Total passenger-trip rate for an entire city [pax-trip/h] ρ = Average distance from the terminal to a service [km] route THB $M = Monetary unit cost per hour [ /veh-h] THB $V = Monetary unit cost per distance traveled [ /veh-km] τ = Delayed time per stop [h] τ 0 = Delayed time per user [h] i,avg h Al = Daily-average access time for an inbound user of [ /pax-trip] mode l i,k h Al = Average access time for an inbound user of mode [ /pax-trip] l in period k o,avg h Al = Daily-average access time for an outbound user [ /pax-trip] of mode l o,k h Al = Average access time for an outbound user of [ /pax-trip] mode l in period k avg h Al = Daily-average access time per user-trip of mode [ /pax-trip] l k h Al = Average access time per user-trip of mode l in [ /pax-trip] period k avg THB Cl = Daily-average operating cost of mode l [ /h] k THB Cl = Average operating cost of mode l in period k [ /h] E = Designated stops at the far end of service zone [-] Havg = Daily-average headway of a trunk-line system [h] APPENDIX A. VARIABLE LIST 48

Hk = Headway of a trunk-line system in period k [h] Lr = Length of a service zone r [km] k ma = Number of assigned motorcycles in period k [veh] s,k mi = Number of motorcycles allowed waiting at stand [veh] s in period k k mi = Number of idle motorcycles in period k [veh] Ml = Day-long total fleet size of mode l [veh-h] k Ml = Required fleet size of mode l in period k [veh-h] k ms = Number of in-service motorcycles in period k [veh] nl = Design variable for mode l [-] Of = Vehicle’s capacity for fixed-route bus service [pax] Oj =Vehicle’s capacity for Jitney-lite service [pax] pk = Proportion of outbound users in period k [-] k pe = Probability that a user is arriving at a stand [-] when it is empty of motorcycles in period k k pf = Probability that a motorcycle taxi is arriving at [-] a stand when it is full of motorcycles in period k R = Size of a service zone [km2] i,avg h Rl = Daily-average in-vehicle riding time for an in- [ /pax-trip] bound user of mode l i,k h Rl = Average in-vehicle riding time for an inbound [ /pax-trip] user of mode l in period k o,avg h Rl = Daily-average in-vehicle riding time for an out- [ /pax-trip] bound user of mode l o,k h Rl = Average in-vehicle riding time for an outbound [ /pax-trip] user of mode l in period k avg h Rl = Daily-average in-vehicle riding time per user-trip [ /pax-trip] of mode l k h Rl = Average in-vehicle riding time per user-trip of [ /pax-trip] mode l in period k sx = Longitudinal street spacing [km] sy = Lateral street spacing [km] tk = Time duration of period k [h] T = Trunk-line transit station, or a terminal [-] Tt = Total operating hours [h] k Tf = Average trip time of fixed-route bus service in [h] period k k Tj = Average trip time of Jitney-lite service in period [h] k APPENDIX A. VARIABLE LIST 49

k Tm,a = Average spent time of motorcycles when they are [h] assigned to pick up a user in period k k Tm,s = Average spent time of motorcycles when they are [h] in-service in period k i,avg h Ul = Daily-average user cost for an inbound user of [ /pax-trip] mode l i,k h Ul = Average user cost for an inbound user of mode l [ /pax-trip] in period k o,avg h Ul = Daily-average user cost for an outbound user of [ /pax-trip] mode l o,k h Ul = Average user cost for an outbound user of mode [ /pax-trip] l in period k avg h Ul = Daily-average user cost per user-trip of mode l [ /pax-trip] k h Ul = Average user cost per user-trip of mode l in pe- [ /pax-trip] riod k vt,l = Cruising speed of mode l [km/h] avg Vl = Daily-average total hourly distance traveled by [veh-km] vehicles of mode l in period k k Vl = Total hourly distance traveled by vehicles of [veh-km] mode l in period k vw = Average walking speed [km/h] Wr = Width of a service zone r [km] i,avg h Wl = Daily-average waiting time for an inbound user [ /pax-trip] of mode l i,k h Wl = Average waiting time for an inbound user of [ /pax-trip] mode l in period k o,avg h Wl = Daily-average waiting time for an outbound user [ /pax-trip] of mode l o,k h Wl = Average waiting time for an outbound user of [ /pax-trip] mode l in period k avg h Wl = Daily-average waiting time per user-trip of mode [ /pax-trip] l k h Wl = Average waiting time per user-trip of mode l in [ /pax-trip] period k THB zl = Daily-average hourly generalized cost of mode l [ /h] avg zr = Minimum day-long hourly generalized cost for [h] zone r tot h zs = Citywide generalized cost for scenario s [ /pax-trip] 50

Appendix B

Value of inputs

The input parameters in this dissertation are derived based on the case of BMR, Thailand. This appendix presents how to estimate the value of inputs relevant to operating costs of informal transport, trip demand densities and values of in- vehicle time. A reader can see the input values for all service zones later in Table B.2.

B.1 Operating costs

In this dissertation, operating costs are approximated by two components: (i) a total vehicular distance per hour and (ii) a day-long fleet size. A unit cost for these two components (i.e., $V and $M , respectively) are derived based on a type of vehicle in use and assumptions as follows. The derivations focus on using (i) pickup trucks for Jitney-lite service and fixed-route bus service and (ii) motorcycles for stand-based motorcycle taxi service. We use reports published by officials in the BMR to estimate unit costs for operating both pickup trucks (National Statistical Office, 2015a,b), and motorcycles (Center of Economics and Business Forecast, 2019).

B.1.1 Distance-based operating costs Distance-based operating costs are assumed to be comprised of (i) fuel and (ii) maintenance costs.

Fuel costs

We estimate fuel costs by assuming that, in 2020, the price of diesel is around 27 THB1 per liter. The total daily fuel cost for 41,636 pickup trucks is 9,378

130 THB ≈ 1 USD (2020) APPENDIX B. VALUE OF INPUTS 51 million-THB per year, so the average cost per vehicle is 963 THB/veh-day. For motorcycles, the total daily fuel cost is about 224 THB/veh-day. The fuel eﬃ- ciency of pickup trucks and motorcycles are 5 km/l and 20 km/l, respectively. Each pickup truck and motorcycle travel daily 129 and 166 km/day on average. Costs due to fuel can be derived as follow.

THB 1 day THB Cost due to Fuel (Pickup trucks) = 963 ∗ ≈ 6 (B.1) veh − day 129 km veh − km THB 1 day THB Cost due to Fuel (Motorcycles) = 224 ∗ ≈ 1.5 (B.2) veh − day 166 km veh − km Maintenance costs

Maintenance costs per pickup truck and per motorcycle are about 243 THB/veh- day and 9 THB/veh-day, respectively. Therefore,

THB 1 day THB Cost due to Maintenance (Pickup trucks) = 243 ∗ ≈ 2 veh − day 129 km veh − km (B.3)

THB 1 day THB Cost due to Maintenance (Motorcycles) = 9 ∗ ≈ 0.5 veh − day 166 km veh − km (B.4)

B.1.2 Hourly operating costs Hourly operating costs are assumed to be comprised of (i) labor costs, (ii) current proﬁts, (iii) overhead costs, and (iv) vehicle-depreciation costs.

Labor costs

We estimate labor costs based on minimum wages earned that are controlled by a government. These costs are identical for operating both pickup trucks and motorcycles. In 2020, the minimum wage is about 331 THB/day (Ministry of Labour of Thailand, 2020). We assumed that a service provider pays a more com- petitive rate at 400 THB/day. The number of ﬂeet conductors are considered to be one-tenth of the number of drivers. Each driver works about 9 hours per day. Therefore, THB driver 1 day THB Labor costs = 400 ∗ 1.1 ∗ ≈ 49 (B.5) driver − day veh 9 h veh − h APPENDIX B. VALUE OF INPUTS 52

Current profits We assume that current profits are pooled and shared equally among all drivers. The average level of profits per driver-day is about 794 THB/driver-day for pickup trucks and 510 THB/driver-day for motorcycles. Therefore,

THB driver 1 day THB Current proﬁts (Pickup trucks) = 794 ∗1.1 ∗ ≈ 98 driver − day veh 9 h veh − h (B.6)

THB driver 1 day THB Current proﬁts (Motorcycles) = 510 ∗ 1.1 ∗ ≈ 63 driver − day veh 9 h veh − h (B.7)

Overhead costs

We assume that overhead costs can be estimated by day-long ﬂeet size. The average level of overhead costs per vehicle-day is about 270 THB/veh-day for pickup trucks and 267 THB/veh-day for motorcycles. A service provider operates 18 hours daily. Hence, THB 1 day THB Overhead costs (Pickup trucks) = 270 ∗ ≈ 15 (B.8) veh − day 18 h veh − h

THB 1 day THB Overhead costs (Motorcycles) = 267 ∗ ≈ 15 (B.9) veh − day 18 h veh − h

Vehicle-depreciation costs

In this dissertation, we assume that both pickup trucks and motorcycles can be operated for 10 years. Their values are linearly depreciated, and they will be sold at 10% of the original price. A new modiﬁed pickup truck costs around 588 thousand THB, and a new motorcycle costs around 55 thousand THB. Therefore,

Vehicle − depreciation costs (Pickup trucks) 103 THB 1 1 1 yr 1 day = 588 ∗ 0.9 ∗ ∗ ∗ veh 10 yr 325 day 18 h (B.10) THB ≈ 9 veh − h APPENDIX B. VALUE OF INPUTS 53

Vehicle − depreciation costs (Motorcycles) 103 THB 1 1 1 yr 1 day = 55 ∗ 0.9 ∗ ∗ ∗ veh 10 yr 325 day 18 h (B.11) THB ≈ 2 veh − h Unit costs per distance travel and a day-long ﬂeet size can be summarized as follow in Table B.1.

Pickup truck Motorcycle Distance-based costs Fuel 6 1.5 Maintenance 2 0.5 Hourly costs Labor 49 49 Proﬁt 98 63 Overhead 15 15 Vehicle depreciation 9 2

Table B.1: List of all operating costs

B.2 Trip demand densities

avg 2 This subsection shows how to derive a trip demand density, δr [pax-trip/km -h], avg 2 by using a population density, λr [pax/km ], for zone r. In this dissertation, we first estimate a population density for all service zones by using the WorldPop dataset (Gaughan et al., 2013; WorldPop & Columbia University, 2020). Trip demand densities are then derived by using an Office of Transport and Traffic Policy and Planning (2018) survey. According to the survey, each person generates 1.97 pax-trip/day and 59.4% of all trips made in the BMR travel between the CBD and its suburb. We assume that only 20% of trips are made by both a feeder system and a trunk-line system. Then,

pax-trip 1 day pax δavg = 1.97 ∗ 20% ∗ 59.4% ∗ ∗ λavg = 9.75 ∗ 10−3 ∗ λavg (B.12) r day 24 h r km2 r

B.3 Values of in-vehicle time

In this dissertation, we estimate the value of in-vehicle time by using wages earned by residents. The OTP survey (Office of Transport and Traffic Policy and Plan- APPENDIX B. VALUE OF INPUTS 54 ning, 2018) provides a forecast of the number of residents and incomes in the BMR. We use estimated values in 2022 for the analysis. The value for a low- income class is first evaluated by the minimum wages in this zone. Refer to Table 5.3, we then estimated the value for a middle-income class using an average income of the residents in BMR. The value for a high-income class is approximated by doubling that of a middle-income class. The values of in-vehicle time can be approximated as follow. For the value of the low-income class, we assume that the annual minimum wage is 100,000 THB per person. Then,

THB 1 yr 1 mon 1 day βi (low − income class) = 100, 000 ∗ ∗ ∗ yr − pax 12 mon 30 day 8 h (B.13) THB ≈ 35 h The survey also indicates that there are about 5.7 million households, and each of them has 2.52 people on average. An average income per household is approximately 49,000 THB per month. Therefore, THB 1 hh 1 mon 1 day β (middle − income class) = 49, 000 ∗ ∗ ∗ i mon − hh 2.52 pax 30 day 8 h THB = 80.5 h THB ≈ 81 h (B.14)

As indicated, we estimate the value for the high-income class by doubling that of the middle-income class. Hence,

THB βi (high − income class) ≈ 80.5 ∗ 2 h (B.15) THB = 161 h APPENDIX B. VALUE OF INPUTS 55 ] h / o THB β [ ] h / i THB β [ ] -h 2 km / avg r pax-trip δ [ ] 2 km / avg r pax λ [ r W [km] r L [km] Table B.2: List of all service zones and inputs Station’s name KhukoatKhukoatK.m.25K.m.25Royal Thai Air Force MuseumBhumibol Adulyadej HospitalSaphanmaiSai Yud 11.82Sai 5.04 Yud 3.03Wongwian Lak Si 1.32 4801.72 11.73Wongwian Lak Si 7475.62 6.53 1.8011th Infantry 46.59 RegimentBang 3945.12 Bua 6.53 13.75 72.53Royal Forest 0.91 Department 2.63 9000.14 38.28Kasetsart University 5359.16 1.74Yaek 3.95 Fai 87.32 Chai 35Bang 9373.61 Wa 1.26 1.58 51.99 1.42 81Bang Wa 0.79 2.83 4.41 1.23 0.75 90.94 8563.02Phetkasem 35 48 0.92 175 0.75 1.20 1.04 8379.94 12911.24Phetkasem 48 83.08 81 405 1.00 12911.24Phasi 4.03 9732.60 125.26 Charoen 9617.78 81.30 81Phasi 13779.19 175 125.26 Charoen 0.96 94.43 0.96 93.31Bang 81 Khae 133.69 405 12981.53 1.13 4.94 405 81 125.95 81 10213.35 1.87 81 405 161 99.09 3.49 161 8493.77 161 35 4.35 405 1.39 243 1.24 5.01 483 1.38 82.41 243 161 4.79 1.24 483 14505.82 1.55 483 11101.57 9.84 105 1.46 13866.47 140.74 81 8448.39 107.71 483 2.43 10658.32 134.53 4.94 81.97 8000.15 103.41 81 1.57 243 77.62 161 9334.03 161 81 243 90.56 161 81 483 483 243 35 483 405 161 175 483 r 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 APPENDIX B. VALUE OF INPUTS 56 ] h / o THB β [ ] h / i THB β [ ] -h 2 km / avg r pax-trip δ [ ] 2 km / avg r pax λ [ r W [km] r L [km] Table B.2: List of all service zones and inputs Station’s name Bang KhaeLak SongLak SongThammasat UniversityThammasat UniversityChiang RakChiang RakKlong NuengKlong 17.54 NuengRangsit 4.50 6.98 9.87Rangsit 2105.90 4.50 1.19 5.06Lak Hok 1573.35 9.72Lak 9029.84 20.43 Hok 9.47Don Mueang 9.47 15.26 7422.32 87.61Kan 17.17 Kheha 5782.77Lak 3.14 6.10 Si 72.01 17.17Lak Si 56.10 2327.86 3.14 35 3.73 6.77Thung Song Hong 2152.78 161 3004.61 22.58 161Thung 3.73 Song HongBang Khen 11.80 2473.92 20.89 175 29.15 161Hua 3.17 Mak 8.31 805 805 35 24.00Hua 2.43 Mak 7037.76 3.62 4.31Bang 805 7.32 Kruai 35 - 4.00 EGAT 5446.93 3.99 68.28 4.27 175 3.62 161 35 10989.50 0.89 7942.79 52.85 2.08 5822.71 106.62 2.42 175 161 2.51 8594.81 1.32 77.06 805 1.67 56.49 175 11726.96 1.23 1.03 161 83.39 805 9739.75 113.77 2.90 1.03 5.85 13424.38 81 161 94.50 2.51 16268.15 130.24 2.50 0.67 805 81 35 157.83 1.13 14457.84 8551.29 1.05 805 405 35 81 140.27 1.05 21652.84 82.96 405 11063.80 175 161 161 210.08 175 35 107.34 243 35 483 483 81 105 35 161 105 405 105 483 r 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 APPENDIX B. VALUE OF INPUTS 57 ] h / o THB β [ ] h / i THB β [ ] -h 2 km / avg r pax-trip δ [ ] 2 km / avg r pax λ [ r W [km] r L [km] Table B.2: List of all service zones and inputs Station’s name Bang BamruTaling ChanTaling ChanBan ChimphliBan ChimphliKanchanaphisekKanchanaphisekSala ThammasopSala Thammasop 4.57Sala Ya 5.07Sala 3.44 Ya 5.17Ramkhamhaeng 2.86 12 4.53 5332.77Ramkhamhaeng 3.42 12 4.71 5.19 4547.06 2.60Ramkhamhaeng 51.74 5.02 5203.57 2.77 2.17Ramkhamhaeng 5115.83 44.12 6.74 2.43 3659.07Rajamangala 3860.42 50.49 7.12 4.44 49.63 3453.26Rajamangala 5.44 35.50 37.45 1390.99Yaek Lum 161 Sali 1.91 33.50 3114.95Yaek Lum Sali 161 13.50 2.34 1.32Si Burapha 6.34 35 30.22 1.32 805 35Si Burapha 15762.50 2.03 9.39 5.19 161 35Khlong 805 Ban 17228.99 1.69 152.93 Ma 1.58 4.96 81Khlong 1003.06 Ban 175 167.16 Ma 0.99 161 175 20518.52 2206.02 1.84 805 9.73 161 175 23405.23 199.07 1.06 1.19 21.40 405 227.08 0.93 805 35 1.19 16219.54 0.65 805 35 1.25 21057.43 157.36 1.25 23634.98 161 2.92 204.30 105 81 3.99 24726.29 81 229.31 81 2.83 105 1.38 3.05 239.89 1.06 1.38 483 15803.04 1.06 161 405 7856.40 9612.31 405 243 153.32 35 6393.13 161 76.22 93.26 483 81 62.03 105 483 81 243 81 81 81 405 405 405 405 r 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 APPENDIX B. VALUE OF INPUTS 58 ] h / o THB β [ ] h / i THB β [ ] -h 2 km / avg r pax-trip δ [ ] 2 km / avg r pax λ [ r W [km] r L [km] Table B.2: List of all service zones and inputs Station’s name SummakonSummakonNom KlaoNom KlaoRat PattanaRat PattanaMin PattanaMin PattanaKheha RamkhamhaengMin 3.39 BuriPhawana 3.44 1.44Chokchai 4 1.44 2.24 5743.32Chokchai 4 4.16 6137.61 1.50Chalong 1.68 6.55 Rat 55.72 5.00Chalong 1.68 1.65 Rat 7342.54 59.55 1.82 5.80Wang Thonglang 1.65 5623.97 8056.26 0.95 4951.60 71.24Wang 1.73 Thonglang 4327.77 54.56Lad 1.73 78.16 Phrao 48.04 5952.26 101 35Lad 41.99 Phrao 10301.49 101 161Bang 8.25 57.75 Kapi 99.95 3.72Bang Kapi 35 4.10 3.49 175 Si 1.37 Kritha 805 81 2.22 35 1.86 3970.35 161 4.05Si 4.02 Kritha 15804.66 81 1.86 2.22 13377.01 1.27 1.65 175 38.52 161 1.15 153.34 15894.45 161 1.27 129.78 405 805 175 15545.02 1.15 15651.90 154.21 1.09 405 16286.35 150.82 18454.76 805 151.85 4.05 805 1.48 158.01 179.05 161 35 1.48 18217.90 35 2.91 13556.99 81 176.75 0.58 35 1.18 161 483 131.53 175 81 1.18 2.82 161 105 16420.27 1.32 243 24918.42 1.50 159.31 105 483 35 1.50 241.76 243 483 9822.65 81 15046.55 95.30 145.98 105 161 243 81 483 161 81 243 483 243 r 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 APPENDIX B. VALUE OF INPUTS 59 ] h / o THB β [ ] h / i THB β [ ] -h 2 km / avg r pax-trip δ [ ] 2 km / avg r pax λ [ r W [km] r L [km] Table B.2: List of all service zones and inputs Station’s name Si NutSi NutKing Rama IX ParkKing Rama IX ParkSi UdomSi UdomSi IamSi IamSi La Salle 5.90Si La Salle 2.10Si 2.41 Bearing 2.91Si 2.41 Bearing 3894.32 2.41Si Dan 2.93 11430.88Si 37.78 Thepha 2.93 110.90 6885.15Si 2.04 Thepha 11028.20Thipphawan 8.33 66.80 1.50 107.00Thipphawan 1.50 11958.31 8.06Khae Rai 161 161 2.13 4411.45 2.14Sanambin 116.02 Nam 2.02 8.10Sanambin 1.28 Nam 1.15 42.80 35 2.16 3851.78 161 805 Samakkhi 483 2.41 10447.71 15.35 10917.68 1.57Samakkhi 37.37 3509.68 2.74 101.36 105.92Royal 161 Irrigation 10207.97 483 Department 175 1.33 1.42 2712.51 34.05 99.04 2.12 16.22 161 2.10 1.36 26.32 483 1.74 3.56 1.66 12401.00 0.93 13952.38 161 81 35 2.19 1.75 4703.96 16037.14 805 120.31 135.37 1.71 1.46 2.69 1.39 16108.62 35 155.59 45.64 35 805 8574.11 1.39 3.07 156.29 243 11150.97 105 161 1.73 16396.31 17379.20 108.19 83.19 175 161 2.10 81 159.08 105 168.61 1.17 805 35 161 1.17 7685.88 35 483 12718.43 243 35 74.57 35 105 805 123.39 161 35 105 105 105 483 105 161 161 483 483 r 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 APPENDIX B. VALUE OF INPUTS 60 ] h / o THB β [ ] h / i THB β [ ] -h 2 km / avg r pax-trip δ [ ] 2 km / avg r pax λ [ r W [km] r L [km] Table B.2: List of all service zones and inputs Station’s name Royal Irrigation DepartmentPak KretPak Kret BypassPak Kret Bypass 2.13Chaeng Wattana - Pak 2.10 KretChaeng 28 Wattana - Pak KretMuang 7231.83 28 Thong ThaniMuang Thong 5.92 Thani 70.16Si Rat 1.82 1.11Si Rat 1.31 1.58Chaeng 7524.85 Wattana 14 4.21 1.05Chaeng 4.30 9164.32 Wattana 14 73.01 1.24Government 161 Complex 2.08 7462.49 2.54 88.91Government Complex 6.02 7316.81 0.93 5062.67 72.40TOT 0.99 483 70.99 8816.01TOT 49.12 7713.31 81Ratchaphat Phra Nakhon 4.32 85.53 81Ratchaphat Phra Nakhon 3.02 74.83 2.32 1.23Ram 161 Inthra 3 1.92 1.23 405 0.96 2.83Lat 8592.09 81 Pla Khao 161 243 0.96 5.76Lat 11376.28 Pla 9257.93 1.39 Khao 1.30 483 83.36 81Ram Inthra 9381.55 1.39 110.37 31 1.20 12348.69 1.09 161 89.82Ram 405 805 Inthra 31 7075.50 1.09 119.81 91.02 8994.09 243 10881.06 68.65 805 87.26 161 1.63 35 105.57 1.18 161 0.73 1.17 35 161 0.73 483 2.98 12531.76 1.13 105 35 2.29 483 8739.57 121.58 1.32 35 2.98 161 8830.32 105 483 1.32 3.68 8830.32 84.79 1.08 85.67 8068.74 175 1.08 483 7152.62 85.67 105 7412.99 161 78.28 69.39 71.92 161 35 483 161 483 161 35 105 805 81 805 175 405 r 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 APPENDIX B. VALUE OF INPUTS 61 ] h / o THB β [ ] h / i THB β [ ] -h 2 km / avg r pax-trip δ [ ] 2 km / avg r pax λ [ r W [km] r L [km] Table B.2: List of all service zones and inputs Station’s name MaiyalapMaiyalapWatcharaphonWatcharaphonRam Inthra 40Ram Inthra 40Ku BonKu BonRam Inthra 83Ram Inthra 83 4.09 6.09East Outer Ring 4.99 Road 4.07East 1.08 1.32 Outer Ring RoadNoppharat 1.08 1.32 Ratchathani 4.08 8646.65 6427.34Noppharat Ratchathani 6.41 8076.83 8524.96 1.25Bang 83.89 62.36 Chan 1.25Bang 7259.78 78.36 82.71 Chan 7.03Settabut 5467.04 Bamphen 9.95 7.54 70.43 3.94 2.84Settabut Bamphen 1.60 4.00 4.12 53.04 1.32 1.57 1.20Talat Min 1.60 1.18 81 Buri 161 5415.16 1.32 1.57On 4262.74 4781.93 Nut 2.29 161 161 6390.85 6432.85On 9141.48 8613.76 52.54 Nut 41.36 6420.52 46.39 35Bang 805 62.00 Chak 62.41 405 88.69 83.57 805 35Bang 805 Chak 62.29 5.56 1.21 0.84 175 1.48 3.65 35 1.87 175 35 1.48 81 6731.17 81 35 1.59 81 7256.61 161 9.61 11284.70 81 65.31 6477.31 2.32 175 109.48 70.40 175 405 405 175 62.84 805 4806.91 405 405 2.75 2.60 46.64 1.97 1.76 161 1.98 161 1.22 1.21 35 11862.09 1.11 161 13141.17 17389.28 115.09 805 15651.37 805 127.50 168.71 35 175 151.85 805 81 175 35 161 81 243 483 105 243 r 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 APPENDIX B. VALUE OF INPUTS 62 ] h / o THB β [ ] h / i THB β [ ] -h 2 km / avg r pax-trip δ [ ] 2 km / avg r pax λ [ r W [km] r L [km] Table B.2: List of all service zones and inputs Station’s name PunnawithiPunnawithiUdom SukUdom SukBang NaBang NaBearingBearingSamrong 2.09Samrong 2.49Pu Chao 1.06 Saming PhraiPu Chao 1.52 Saming 2.26 14221.27 PhraiErawan Museum 2.35 13679.86 137.97 1.79Erawan Museum 132.72 1.13Royal 2.55 Thai 14211.83 Naval AcademySamut 2.23 Prakan 12364.16 Cityhall 137.88 1.15 6.43Srinagarindra 2.34 119.96 1.15 0.83 81 11089.66Phraek 2.06 Sa 2.73 1.34 81 10777.89 3.33Phraek 1.40 107.59 2.22 Sa 15007.67 1.34 0.96 13200.21Sai 104.57 1.53 Luat 1.70 17369.82 161 1.20 145.60 243 9666.20Sai 128.07 1.53 Luat 5.32 35 2.17 14989.73 168.52 1.76 243 12630.05Kheha Samut Prakan 93.78 18537.37 2.34 1.69 145.43 483 Kheha 122.54 161 16286.61 Samut Prakan 179.85 161 9265.25 15134.74 158.01 105 35 161 9.70 146.84 483 81 89.89 483 2.56 81 161 35 105 1.75 483 81 6295.73 9.57 35 243 4.15 3.55 0.82 81 3.75 483 61.08 243 105 0.82 161 1.90 3.74 15365.40 6950.51 243 105 3.19 12494.89 149.08 1.21 7619.31 243 67.43 483 121.23 1.46 12550.72 73.92 35 11486.67 121.77 111.44 81 161 35 175 35 81 243 805 161 175 105 405 483 r 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 APPENDIX B. VALUE OF INPUTS 63 ] h / o THB β [ ] h / i THB β [ ] -h 2 km / avg r pax-trip δ [ ] 2 km / avg r pax λ [ r W [km] r L [km] Table B.2: List of all service zones and inputs Station’s name WutthakatKlong Bang PhaiKlong Bang PhaiTalat Bang YaiSam Yaek Bang YaiSam Yaek Bang YaiBang PhluBang PhluBang Rak 7.12 YaiBang 3.87 Rak 1.92 Yai 1.96Tha It 2.52 1.83 2.11Tha 8.52 2143.33 It 4.39 14278.06Sai 1.94 4356.68 Ma 5.59 20.79Sai 138.53 1.94 Ma 5376.07 1581.77 42.27Phranangklao Bridge 3760.76Phranangklao 52.16 Bridge 15.35 4.71Yaek 36.49 Nonthaburi 1 3.86 4.78 1.41 35Yaek 81 Nonthaburi 1 5.87 1.41 1.04Bang 35 3568.50 Kraso 2.19Bang 5155.65 5665.58 Kraso 35 35 34.62 1.83 105 Nonthaburi 405 5507.38 Civic 161 Center 50.02 54.97 2.04 4.84Nonthaburi 175 Civic 1.19 Center 53.43 4.21Ministry 1.77 of 175 1.78 Public 13017.18 175 3.72 Health 1.75 805 1.98 8774.80 7282.60 4.66 126.29 1.98 2.20 81 1.40 7625.03 1.58 1.84 35 1.51 35 85.13 70.66 7201.83 13428.04 0.83 35 1.15 73.98 8192.65 13553.82 130.28 1.63 69.87 405 2.72 1.15 18982.25 131.50 81 79.49 175 175 1.21 1.41 1.10 19875.81 184.17 175 1.10 16735.36 161 35 192.84 15277.72 81 35 243 162.37 11333.06 148.22 35 81 109.95 483 81 175 81 405 105 81 105 243 161 35 405 243 35 243 483 105 105 r 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 APPENDIX B. VALUE OF INPUTS 64 ] h / o THB β [ ] h / i THB β [ ] -h 2 km / avg r pax-trip δ [ ] 2 km / avg r pax λ [ r W [km] r L [km] Table B.2: List of all service zones and inputs Station’s name Yaek TiwanonYaek TiwanonRam KhamheangBan Thap ChangBan Thap ChangLat KrabangLat KrabangTalat PhluTalat 1.52 Phlu 2.21 2.00 1.79 0.97 2.56 2.32 12417.10 1.97 4.64 14208.11 16941.36 120.47 4.90 137.85 164.37 10222.69 7.02 10375.32 99.18 3.23 6.38 100.66 81 6.38 3.25 4173.68 81 81 1.46 4372.34 5.49 40.49 81 7.40 243 42.42 4371.39 35 243 243 5428.37 42.41 243 52.67 105 35 35 161 175 81 175 805 405 r 208 209 210 211 212 213 214 215 216 65

Appendix C

Detail Results

This appendix shows optimal conﬁguration of a feeder system and its costs for all service regions in the BMR. The result for ﬁxed-rout bus service, stand-based motorcycle taxi service and Jitney-lite service are shown in Table C.1, C.2, and C.3, respectively. APPENDIX C. DETAIL RESULTS 66 avg f C [h] ] pax-trip avg / , i f min U [ ] pax-trip avg / , o f min U [ ] pax-trip / avg f min U [ i /β f z [*1000 h] Table C.1: Optimal results for Fixed-route bus service f M [veh] f n 17124 4084 72103 108 199.333 32 75.42 2403 75.711 36 54.161 30.39 30 113.801 24 40.492 37.93 5 53.811 34.71 6 23.75 52.283 39.25 29.64 43 10 16.91 3.645 43.70 5 23.57 7.624 42.60 33 6.82 30.41 22.81 16.292 27.06 7.38 304 60 23.58 6.34 32.70 18.524 42.06 36 30.24 30.15 17.974 44.62 10 3048.73 29.47 22.96 28.67 11.5310 46.99 44 27.464 53.59 238.52 48 14.35 25.18 34.70 29.10 11.46 351.26 44 13.07 24.63 200 28.05 61.79 1797.49 102.95 12.33 15.53 30.46 48.97 48 11.73 26.93 70.16 104.11 18.35 116.83 15.35 12.55 27.82 17.07 97.70 12.02 28.99 70.53 16.33 39.44 13.23 42.33 15.73 47.30 11.47 30.09 37.09 19.35 16.55 11.91 19.44 16.02 12.49 30.76 6.87 17.23 17.83 33.40 20.32 15.47 13.04 16.11 53.71 15.91 49.39 16.49 13.38 193.73 24.50 26.98 59.46 17.04 33.91 71.38 17.38 155.54 1511.54 73.13 77.97 r 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 APPENDIX C. DETAIL RESULTS 67 avg f C [h] ] pax-trip avg / , i f min U [ ] pax-trip avg / , o f min U [ ] pax-trip / avg f min U [ i /β f z [*1000 h] Table C.1: Optimal results for Fixed-route bus service f M [veh] f n 5273110 100 3246 6207 156.93 3405 469.2211 90 309.906 231 151.3213 48.79 70 41.47 3639 94.37 107.26 48.6312 90 66.08 3129 72.21 163.788 21.06 162 17.40 844 54.80 107.00 65.40 429.90 20.982 144 29.70 146.55 62.661 50.19 88 123.623 27.73 44 24.07 51.24 78.69 50.80 24.074 29.37 10 27.656 101.44 48.56 5 36.37 28.00 21.761 30.61 36.33 12 135.81 2 15.12 28 529.54 22.29 46.80 22.07 30.737 36.03 48 4668.78 5.29 43.88 20.95 13.71 4 2547.54 34.66 28.43 44.36 14.83 34.77 10 26.10 29.17 91 28.95 20.07 28.73 148.24 1737.24 18.61 3.94 33.78 27.61 30.16 11.51 2729.95 113.85 18.85 21.50 26.59 94.74 11.05 27.53 146.99 26.73 507.73 25.27 14.89 33.03 522.62 13.08 25.88 25.51 140.26 11.29 43.08 15.05 11.77 1080.82 283.12 18.89 14.52 17.08 10.94 326.88 15.29 18.20 16.92 15.77 38.51 18.52 41.57 14.94 46.71 24.87 364.80 31.06 16.54 298.58 r 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 APPENDIX C. DETAIL RESULTS 68 avg f C [h] ] pax-trip avg / , i f min U [ ] pax-trip avg / , o f min U [ ] pax-trip / avg f min U [ i /β f z [*1000 h] Table C.1: Optimal results for Fixed-route bus service f M [veh] f n 8653 882 726 603 116.14 336 95.53 2410 41.94 664 26.95 36 42.556 21.16 90 1502 44.61 71.733 50.05 38.63 565 53.50 82.27 120 196.85 17.942 60.14 12 18.973 43.57 43.93 21 113.50 21.692 52.89 35 49.93 23.424 54.11 9.87 12 24.61 26.742 13.69 18 25.64 18.454 67.35 50.91 61.07 10 28.36 23.113 16.81 16 21.63 30.08 23.722 28.21 144.51 8 29.43 33.412 26.87 6.68 32 117.73 25.12 30.34 24.41 27.20 20.50 24 453.60 29.78 26.56 20 9.16 28.30 248.73 30.39 25.27 39.86 16 12.71 181.62 11.43 26.14 26.88 109.21 37.01 10.21 33.87 22.35 24.48 116.71 11.28 15.77 248.46 146.81 26.57 10.64 37.57 16.71 15.43 40.25 11.44 182.93 14.21 386.55 9.17 44.09 15.28 42.36 11.29 14.64 15.45 93.01 160.06 16.79 15.44 56.45 18.71 13.17 39.32 17.85 15.29 30.12 22.12 23.46 75.46 25.38 28.04 24.51 26.77 105.24 78.40 65.29 53.14 r 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 APPENDIX C. DETAIL RESULTS 69 avg f C [h] ] pax-trip avg / , i f min U [ ] pax-trip avg / , o f min U [ ] pax-trip / avg f min U [ i /β f z [*1000 h] Table C.1: Optimal results for Fixed-route bus service f M [veh] f n 2423 182 363 145 12.33 304 40.23 124 11.32 367 31.24 655 47.75 8.43 166 38.77 31.11 604 48.72 83.55 1265 45.11 20.46 50 20.543 87.45 60 46.99 65.75 16.054 46.33 28 21.023 42.65 69.21 50 19.222 36.14 32.15 21 27.215 46.73 30.62 40 20.16 50.84 22.72 19.834 25.53 18 27.69 17.992 26.80 21.41 10 25.89 14.744 28.02 62.51 50 135.85 20.033 27.02 26.83 27.30 32 22.09 59.26 26.50 27.09 7.49 8 105.79 24.66 11.40 26.38 42.77 32 98.95 21.41 12.01 27.56 46.19 15 26.70 11.51 89.26 24.73 28.76 7.93 116.59 11.54 37.30 29.12 107.05 15.40 11.19 27.72 14.19 28.12 16.01 11.78 25.66 97.12 15.51 10.37 938.80 15.54 25.91 26.66 12.56 80.78 15.19 11.86 25.88 456.34 15.78 10.83 91.27 14.37 379.14 10.95 11.33 16.56 68.45 15.86 10.94 65.82 14.83 29.55 14.95 15.33 75.74 163.83 14.94 52.91 26.49 52.55 50.45 r 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 APPENDIX C. DETAIL RESULTS 70 avg f C [h] ] pax-trip avg / , i f min U [ ] pax-trip avg / , o f min U [ ] pax-trip / avg f min U [ i /β f z [*1000 h] Table C.1: Optimal results for Fixed-route bus service f M [veh] f n 3756 244 493 654 24.12 422 67.08 242 83.94 544 49.80 682 53.38 30.67 147 26.60 87.37 142 46.21 100.68 685 25.78 8.00 14 23.3614 25.27 14.66 210 11.303 51.04 38.62 10 50.66 19.773 9.89 25 235.55 448 10.898 28.49 30.02 10.642 29.46 12.92 21 15.30 22.194 53.18 29.06 18 533.41 22.00 26.442 60.73 64 31.72 14.893 14.50 14 12.25 182.54 14.64 12.731 28.79 12.56 20 81.68 28.85 58.88 23.26 24.67 38.40 12 28.66 107.55 27.03 9.53 21 13.86 68.16 28.19 16.25 26.18 5 40.95 16.73 12.40 27.94 14.48 87.70 26.10 29.93 10.33 26.64 26.33 111.62 33.70 17.86 30.42 4.65 12.09 104.88 23.82 45.28 16.40 11.97 27.86 32.77 514.17 14.33 11.32 25.62 342.70 105.06 13.21 16.09 43.38 9.91 34.03 15.97 11.93 727.23 42.35 15.32 10.81 17.21 157.05 19.69 13.91 137.18 15.93 478.72 14.81 105.34 23.69 34.40 19.86 34.08 37.14 r 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 APPENDIX C. DETAIL RESULTS 71 avg f C [h] ] pax-trip avg / , i f min U [ ] pax-trip avg / , o f min U [ ] pax-trip / avg f min U [ i /β f z [*1000 h] Table C.1: Optimal results for Fixed-route bus service f M [veh] f n 4622 283 602 101 30.64 203 76.48 393 9.72 123 28.75 73 27.67 38.58 422 41.90 13.98 242 39 26.19 9.362 46.76 62.03 33 11.832 43.51 14.07 16 17.621 31.15 24.94 141 44.14 12 11.09 33.75 20.052 42.67 11.64 12 15.83 18.421 28.07 18.41 5 24.28 13.574 45.58 15.25 53 29.89 15.09 12.63 10 14.87 26.71 18.001 30.73 5 7.03 45.56 25.09 12.032 27.35 32 3.86 100.40 17.57 19.46 26.63 12.44 21 12.95 16.90 24.38 8 18.87 3.66 66.16 24.67 13.37 42.22 18 128.38 16.03 29.06 11.68 30.18 39.83 26.12 34.72 11.31 26.31 9.45 16.95 10.19 21.74 22.54 68.07 17.37 35.08 37.22 181.44 12.53 15.68 38.74 294.91 15.36 15.31 11.16 53.44 14.19 56.12 43.77 122.70 15.54 15.28 16.53 23.16 16.04 19.36 20.24 15.16 19.66 24.73 18.55 19.54 21.94 8.32 22.71 38.83 16.68 31.39 25.22 38.23 53.19 34.65 61.17 59.85 r 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 APPENDIX C. DETAIL RESULTS 72 avg f C [h] ] pax-trip avg / , i f min U [ ] pax-trip avg / , o f min U [ ] pax-trip / avg f min U [ i /β f z [*1000 h] Table C.1: Optimal results for Fixed-route bus service f M [veh] f n 2344 202 363 563 27.60 405 56.57 203 72.19 423 57.34 484 44.54 15.09 503 41.59 22.43 631 42.77 49.96 303 39.18 69.70 60 18.942 46.65 33.04 30 17.464 45.52 34.40 8 18.054 50.23 31.87 15 16.264 38.87 31.16 10 25.61 19.996 52.41 36 9.24 24.13 19.433 41.85 14.40 52 24.72 21.784 46.21 7.26 16 22.92 16.102 44.05 48.92 120 65.69 26.66 22.872 75.41 24 58.63 26.09 58.36 17.59 44.88 17.01 24 91.04 28.45 62.13 19.77 16 49.21 66.02 22.77 18.69 40.10 28.73 12 151.93 29.54 42.84 32.53 318.48 25.85 24.26 19.10 34.38 11.22 156.98 50.47 26.44 15.87 21.27 82.77 25.36 16.72 29.81 469.63 18.09 24.07 32.51 98.00 25.77 13.86 29.91 21.90 455.52 27.95 27.94 97.64 23.38 12.90 24.75 10.04 60.53 49.74 20.52 12.95 28.57 11.97 76.83 60.10 16.90 84.69 14.04 27.69 16.95 900.62 15.97 77.93 40.68 118.86 40.46 r 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 APPENDIX C. DETAIL RESULTS 73 avg f C [h] ] pax-trip avg / , i f min U [ ] pax-trip avg / , o f min U [ ] pax-trip / avg f min U [ i /β f z [*1000 h] Table C.1: Optimal results for Fixed-route bus service f M [veh] f n 2352 143 213 354 15.11 143 24.75 214 47.33 213 9.08 288 27.75 27.98 242 28.13 24.07 363 25.43 34.64 157 31.71 112 28.75 11.882 26.32 37.25 8 12.063 25.73 12.97 18 65.12 10.719 25.21 842 27.59 14 12.37 9.63 15.88 11.163 27.77 12.48 21 16.06 10.873 25.38 114.11 180 31.44 14.71 10.614 9.23 12 11.8014 16.37 26.18 30 45.12 15.16 89.94 28.01 11.896 27.92 18 70.05 30.54 14.87 10.69 10.51 36 13.72 57.60 14.61 280 50.00 29.04 15.80 106.80 28.42 18.92 54 35.42 48.07 12.01 15.89 11.96 47.27 140.41 13.27 34.47 14.69 25.30 17.72 46.40 37.93 32.60 12.52 39.15 12.21 37.15 20.70 16.01 116.93 15.96 47.43 27.20 17.27 48.32 10.65 850.01 15.63 31.75 16.52 16.21 15.24 27.37 27.48 136.63 20.38 11.60 139.10 14.65 22.30 13.87 105.61 68.16 21.91 1354.63 27.05 15.60 39.56 49.75 17.87 60.22 2098.88 58.27 411.94 r 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 APPENDIX C. DETAIL RESULTS 74 avg f C [h] ] pax-trip avg / , i f min U [ ] pax-trip avg / , o f min U [ ] pax-trip / avg f min U [ i /β f z [*1000 h] Table C.1: Optimal results for Fixed-route bus service f M [veh] f n 8224 802 324 122 42.83 722 32.19 122 8.60 444 50.42 224 27.70 8.76 204 60.86 47.86 223 21.29 52 53.474 73.82 12.90 48 11.852 13.09 40 51.20 27.104 43.59 33.01 302 49.69 27.92 44 23.40 33.583 48.21 47.01 12 15.853 45.21 19.05 24 22.26 33.77 18.461 47.87 51.75 12 21.512 43.46 30.07 13.72 18 40.24 20.772 43.60 28.26 24 600.05 19.274 33.73 28.93 8.74 5 102.99 25.13 20.60 43.54 19.32 12 28.18 18.40 93.10 28.25 13.13 8 541.39 27.44 18.47 26.27 24 4.31 25.94 14.86 92.27 15.59 29.71 71.54 27.27 18.44 27.14 8.72 72.36 25.06 12.13 26.41 30.58 149.92 25.13 11.14 168.10 18.86 34.74 27.54 12.85 395.22 25.10 11.57 356.85 16.13 26.13 11.21 24.21 132.33 15.14 222.96 15.37 11.77 16.85 144.33 15.57 39.87 11.07 15.21 10.11 40.95 19.37 15.77 91.54 60.70 15.07 179.93 14.11 38.42 38.88 27.48 39.32 r 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 APPENDIX C. DETAIL RESULTS 75 avg f avg m C [h] C [h] ] ] pax-trip pax-trip avg avg / / , , i i f m min min U U [ [ ] ] pax-trip pax-trip avg avg / / , , o f o m min min U [ U [ ] ] pax-trip pax-trip / / avg f avg m min min U [ U [ i i /β /β f m z [*1000 h] z [*1000 h] Table C.1: Optimal results for Fixed-route bus service f m Table C.2: Optimal results for Stand-based Motorcycle Taxi service M [veh] M [veh] f m n 3556 186 3511 306 16.95 3011 38.40 36 16510 35.60 25.52 54 99 27.70 27.88 97.47 50 27.70 26.60 42.70 111.01 29.34n 48.22 11.85 31.85 50.71 11.8549 11.30 56.0624 41.91 12.6716 44.75 15.85 13.93 22.02 276310 15.85 52326 15.30 24.70 17.62 61212 491.62 16.67 18811 19.04 57.97 105.73 17.93 28.69 14439 113.99 123.22 267 101.36 37.73 44.31 31.37 24.29 234 255.92 96.76 22.24 25.71 149 280.66 54.02 1252.18 36.02 47.28 20.12 6.73 403.17 40.77 160.90 31.74 2.47 170.94 24.01 6.39 22.17 1.80 6.02 37.58 12.64 19.77 2.74 29.64 2.30 18.32 11881.26 1.77 34.76 924.94 21.27 1130.58 19.87 326.20 6178.19 10.87 473.79 411.50 129.63 r 208 209 210 211 212 213 214 215 216 r 1 2 3 4 5 6 7 8 APPENDIX C. DETAIL RESULTS 76 avg m C [h] ] pax-trip avg / , i m min U [ ] pax-trip avg / , o m min U [ ] pax-trip / avg m min U [ i /β m z [*1000 h] m Table C.2: Optimal results for Stand-based Motorcycle Taxi service M [veh] m n 1222 402 5511 3011 6.57 4813 10.22 41 22314 5.91 2383 9.10 40416 7.38 48.44 15.39 28515 13.23 51.2018 83 76.81 9.43 33424 60.59 14.75 34918 14.49 0.91 12.42 389 1.1432 15.55 13.26 72.21 1383122 17.90 70.40 0.80 38775 12.37 1.10 84.42 80134 243.10 2.41 0.95 2595 14.4937 13.11 2.23 12.09 14.10 84.68 466425 2.82 23.44 190.61 625.48 191628 8.63 2.06 14.72 34.20 13.65 41234 822.65 12.07 156.27 11.47 1387 1.16 343.35 93.38 2.46 15.40 11.03 26.20 309 26.28 2.78 15.08 104.16 2126 248.07 2.67 25.03 5.04 10.30 81.32 40.12 197.56 76.69 68.80 56.17 378.03 2.75 11.95 210.30 11.64 4.79 34.51 4.50 721.17 20.66 53.73 250.81 6.50 12.05 29.17 30.03 8.78 51.32 141.36 296.58 12.65 4.26 21.41 21.78 620.45 8.33 346.95 5887.63 33.62 3.59 8.46 47.39 345.64 734.63 30.26 2373.56 45.40 20051.43 26.44 8300.23 42.86 371.13 5997.46 276.10 9204.07 r 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 APPENDIX C. DETAIL RESULTS 77 avg m C [h] ] pax-trip avg / , i m min U [ ] pax-trip avg / , o m min U [ ] pax-trip / avg m min U [ i /β m z [*1000 h] m Table C.2: Optimal results for Stand-based Motorcycle Taxi service M [veh] m n 388242 48037 232223 119132 119.63 53310 559.88 10034 242.73 7512 124.50 30.74 3654 178.25 31.1010 69 152.22 31.108 67 64.61 17.631 94 34.44 4.00 1713 14.46 6.04 24.3228 10.77 419 4.6438 17.49 27.68 45 36.98 2.2032 50 4.21 70.65 72815 26.74 10.58 25.07 3.00 51710 13.38 7.29 26.46 4218 13.11 2.58 10.59 12.74 146.63 51626 15.43 124.87 30.23 17.68 432.48 314 1.0914 102.13 2153.54 1.0533 21.32 241 92.25 13.49 2172.66 24.82 306 1.22 11.07 1.70 25.11 56.20 468.88 23.22 251 4233.39 2.08 43.42 24.30 348 9.50 74.54 1341.96 12.33 32.73 0.81 52.38 3.34 1.01 11.89 1504.43 31.74 11.04 88.28 3.00 34.67 3.09 15.60 24.83 58.57 263.26 3.25 29.50 12.68 21.48 160.36 2.80 10.06 148.63 35.02 20.23 2.99 1717.78 21.21 2.91 2.97 29.48 174.98 1308.27 42.27 4.14 28.94 460.77 31.68 375.29 21.92 2148.90 26.52 1296.60 30.88 996.86 271.34 445.73 312.61 r 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 APPENDIX C. DETAIL RESULTS 78 avg m C [h] ] pax-trip avg / , i m min U [ ] pax-trip avg / , o m min U [ ] pax-trip / avg m min U [ i /β m z [*1000 h] m Table C.2: Optimal results for Stand-based Motorcycle Taxi service M [veh] m n 631938 9563 2624 87213 237.764 135 56.578 188 183.29 2542 22.48 31.135 129 31.252 42.79 138 53.02 40.1412 81 23.899 93 15.79 4.52 28.628 61 15.62 2676 4.13 13.14 10.26 5.395 19.01 166 11.6614 11.12 163 52.52 1.40 10.314 26.61 98 1.59 33.0311 13.26 1.51 129 38.66 32.90 1643 34.76 8.86 1.2411 10.73 19.62 17.79 111 1.34 14.38 22.72 869.44 20625 38.51 19.74 14.03 1.017 470.02 75 8.75 22.39 19.70 1595.89 204 0.97 42.08 10.42 375 0.85 21.74 1.85 540.84 27.86 8.97 13.12 19.57 74 42.05 1.81 758.56 12.25 90.21 2.24 220.11 26.33 24.70 7.89 221.08 1.83 9.88 16.28 15.94 2.06 118.56 24.19 2.08 27.34 17.93 318.53 23.30 1.62 20.15 2.44 78.70 14.13 19.91 465.22 102.40 25.80 1.30 2.80 17.49 287.94 3.16 285.84 24.71 22.26 1.08 169.52 522.83 22.89 142.97 24.55 20.14 445.14 362.55 13.05 296.95 361.23 335.28 62.41 r 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 APPENDIX C. DETAIL RESULTS 79 avg m C [h] ] pax-trip avg / , i m min U [ ] pax-trip avg / , o m min U [ ] pax-trip / avg m min U [ i /β m z [*1000 h] m Table C.2: Optimal results for Stand-based Motorcycle Taxi service M [veh] m n 272017 3998 8059 3706 96.296 448 144.0815 250 78.867 339 75.622 25.13 170 46.37 38.51 33911 56.8912 12.50 130 31.552 91 72.39 18.76 36711 3.50 13.00 4.58 27.09 2394 17.749 2.19 15.06 53 68.99 12.84 18719 12.77 50.46 2.4628 103 21.63 1.65 10.0514 33.92 9.39 264 40.16 2.31 3499 14.88 15.33 10.31 1.52 19.07 37325 2.27 11.47 16.30 46.88 24730 358.20 75.56 1.25 11.35 3404.86 2 12.84 151 91.25 9.91 15.43 412 1.08 2.35 327.03 53.12 12.40 11.32 472 1.80 10.50 1851.22 27.66 31.97 12.95 96 100.36 434.49 8.79 1.83 26.03 115.96 1395.90 0.80 13.79 12.28 12.98 1.19 294.08 16.32 300.16 9.67 2.18 11.53 28.04 1.96 28.86 111.41 3.35 11.01 9.11 359.67 1.72 650.27 11.22 18.63 1.50 208.87 4.19 25.48 10.99 4.19 163.15 22.69 88.58 10.56 175.66 1.46 1076.80 10.04 23.85 306.29 24.67 333.67 215.08 17.17 130.36 373.44 427.64 385.21 r 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 APPENDIX C. DETAIL RESULTS 80 avg m C [h] ] pax-trip avg / , i m min U [ ] pax-trip avg / , o m min U [ ] pax-trip / avg m min U [ i /β m z [*1000 h] m Table C.2: Optimal results for Stand-based Motorcycle Taxi service M [veh] m n 513353 112 46948 127 20.69 123890 84.094 96 21.464 309.17 135 297510 13.593 17.60 38.59 197 28.787 727.45 167 41.55 18.19 5665 33.077 124 1.49 27.651 12.32 4.29 124 95.26 39.37 11.2310 68 7.47 1.56 20.7826 126 16.41 25.963 46 15.21 12.11 147 1.2010 14.16 17.10 8.01 34.30 1.32 26.88 32912 34.08 17.35 16.634 7.89 43 31.63 1.56 10.25 1953 79.32 1.42 192.79 28317 11.92 2.11 11.12 1975.21 31.35 11.53 9.91 9.06 101 39.11 1153.88 1.54 511.20 13.22 68 56.91 19.98 1.22 14.85 281 22.54 13.78 19.23 1.29 163.57 14.98 2789.22 1.45 115.89 12.62 22.69 66.69 11.99 15.82 1.66 24.71 1.07 795.07 9.02 2.69 669.45 14.96 10.62 2324.84 10.08 14.30 2.37 21.94 1.09 498.36 3.08 11.56 18.91 106.09 19.85 1.42 57.99 108.67 1.39 3.09 20.32 10.90 127.29 21.64 181.36 291.13 13.54 12.91 342.74 18.85 36.38 505.05 173.63 116.43 251.14 r 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 APPENDIX C. DETAIL RESULTS 81 avg m C [h] ] pax-trip avg / , i m min U [ ] pax-trip avg / , o m min U [ ] pax-trip / avg m min U [ i /β m z [*1000 h] m Table C.2: Optimal results for Stand-based Motorcycle Taxi service M [veh] m n 48124 1876 305 2335 31.434 168 53.992 91 50.821 74 28.024 60 17.681 19.04 31 30.1714 15.39 14.81 4410 12.19 57 17.403 6.43 40 1.81 1738 11.98 7.44 3.07 1169 11.55 2.42 11.6117 10.26 6.72 97 39.82 1.8621 144 26.84 11.39 15.87 1.5018 188 19.03 27.10 250 1.335 10.40 17.37 12.39 28.72 326 1.167 17.30 18.37 15.54 37.67 24616 16.98 0.96 58.57 759.05 21 10.48 172 1.09 77.88 1266.26 1.05 28.24 10.22 206.34 253 57.38 21.67 378 1.86 9.10 1.04 681.65 21.85 30.65 300 1.56 20.21 10.42 44.89 78.30 23.00 77.28 17.94 1.81 63.26 9.35 18.91 70.53 2.11 15.44 50.97 2.28 17.32 28.74 2.67 15.42 26.07 32.48 3.19 29.75 173.39 2.33 26.43 19.26 48.17 19.56 150.17 157.21 2.32 19.57 99.72 17.54 3.32 3.87 19.80 391.25 2.40 16.58 251.33 330.14 26.42 221.48 29.17 291.61 25.88 216.38 16.86 703.68 1052.50 681.78 264.55 r 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 APPENDIX C. DETAIL RESULTS 82 avg m C [h] ] pax-trip avg / , i m min U [ ] pax-trip avg / , o m min U [ ] pax-trip / avg m min U [ i /β m z [*1000 h] m Table C.2: Optimal results for Stand-based Motorcycle Taxi service M [veh] m n 9111011 411 2353 3715 73.34 2052 47.1717 91 65.7023 75 41.545 60 39.13 20517 16.33 21.67 3398 15.08 33.059 10.87 23.46 58 48.11 7843 80.42 4.855 28.69 2.30 2344 20.57 3.66 13.01 161 139.387 27.62 2.33 19.64 154 44.3113 22.03 126 34.29 33.47 1.773 116 19.37 26.03 37.78 1.318 14.13 202 29.39 23.06 238 1.227 2.21 21.12 14.86 21.7310 3.00 121 1741.07 10.31 37.899 26.92 413.22 140 50.52 17.91 4.92 0.98 19.27 1551.70 116 12.26 20.07 173 26.40 360.00 17.44 1.86 13.46 29.85 157 19.03 1.40 13.91 24.66 366.44 11.49 36.43 1.68 32.86 127.46 13.15 1.39 16.44 33.88 237.22 179.39 1.42 12.17 13.01 302.19 1.69 11.87 8.91 1.65 11.41 16.24 3327.44 48.76 1.55 12.91 10.88 1.64 409.09 12.04 1.50 12.22 138.74 1.59 9.84 622.97 1.76 216.51 14.89 199.74 10.53 351.36 10.37 9.82 206.94 486.05 11.15 121.40 100.10 149.90 136.65 r 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 APPENDIX C. DETAIL RESULTS 83 avg m C [h] ] pax-trip avg / , i m min U [ ] pax-trip avg / , o m min U [ ] pax-trip / avg m min U [ i /β m z [*1000 h] m Table C.2: Optimal results for Stand-based Motorcycle Taxi service M [veh] m n 10315 32034 88 107128 59.973 687 180.58 16.37 165 647223 12.12 14.35 122 27.2914 208 142.55 20.34 11396 12.01 20.2513 79 39.06 21834 201.22 10.78 2.06 15.07 16.2710 113 3.50 243 1.0411 14.47 49.96 16.38 185412 35.82 13.52 22.34 476 0.963 12.30 52.20 1.41 3.08 61319 326.52 16.84 2123 12.32 10.98 17.25 81.34 1.5118 74 5.01 103.24 1.59 17.69 6048 9.83 563.10 12.83 44.63 35.37 13.665 13.19 77 4505.57 199 1.23 149.25 2.25 13.43 21.64 110.78 14.87 18.36 136 1.37 30.82 11.93 1.98 13.87 35.37 135 5.21 47.77 114.45 661.08 581.99 28.11 49.67 30.84 2.62 11.09 15.00 489.57 2.50 23.94 4843.66 360.92 16.31 28.89 3.77 23.48 10.85 30.17 28.08 5.15 1.58 134.73 191.72 19.01 29.60 15.86 193.30 1.50 2.60 213.20 31.60 7902.23 2.62 44.52 29.26 1970.21 2.26 2536.53 27.39 379.97 20.88 25.46 2560.17 295.76 27.35 307.20 175.08 239.38 549.79 r 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 APPENDIX C. DETAIL RESULTS 84 avg m C [h] ] pax-trip avg / , i m min U [ ] pax-trip avg / , o m min U [ ] pax-trip / avg m min U [ i /β m z [*1000 h] m Table C.2: Optimal results for Stand-based Motorcycle Taxi service M [veh] m n 411916 141 400617 317 25.34 3274 71.409 266 56.12 3703 65.966 104 31.80 45.413 32.65 137 74.401 114 28.99 19.354 23.01 152 29.312 167 2.57 21.34 18.808 3.29 23.08 49 28.165 117 2.76 13.22 28.2311 2.53 60 12.4310 8.34 145 2.37 15.51 29.23 21.647 2.69 123 29.36 13.05 3179 11.06 1.34 17.54 26.23 30.44 29532 20.48 1.55 22.9416 185 59.46 18.43 1.35 579.26 12.04 18.9739 1666.22 420 20.39 55.01 1.47 1322 11.60 1.70 1309.39 10.38 11.88 35.04 493 577.86 13.21 10.88 71.17 482 236.55 13.87 1.05 1.22 1093.94 14.16 656.36 13.05 88.70 11.58 0.90 117.25 1.30 178.33 14.92 15.84 38.28 1.34 118.35 19.09 1.80 17.38 454.75 10.81 1.65 33.55 262.09 23.81 10.70 1.71 676.87 9.08 4.68 2.19 11.88 12.08 193.27 200.09 3.05 11.39 2.87 100.97 13.21 124.50 33.60 210.98 16.90 553.74 513.33 30.50 20.94 321.59 5601.62 1724.21 2045.58 427.95 r 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 APPENDIX C. DETAIL RESULTS 85 avg m avg j C [h] C [h] ] ] pax-trip pax-trip avg avg / / , , i j i m min min U U [ [ ] ] pax-trip pax-trip avg avg / / , , o j o m min min U [ U [ ] ] pax-trip pax-trip / / avg j avg m min min U [ U [ i i /β /β Table C.3: Optimal results for Jitney-lite service m j [*1000 h] z [*1000 h] z m j Table C.2: Optimal results for Stand-based Motorcycle Taxi service M [veh] M [veh] m j n 17 310n 63.4317124 24.92 4764 120103 116 192.47 2.513 48 67.71 2703 67.771 54 42.471 27.34 48 108.911 22.41 28.46 362 34.43 14 42.982 31.38 14 12.06 41.303 28.52 26.82 9 546.70 3 4.88 4.74 165 33.17 7.79 14 12.75 31.94 45 6.14 30.41 11.83 5.56 21.21 7.23 45 6.12 85 23.58 24.20 7.98 38.06 30.24 23.43 7.31 40.99 3423.86 29.47 20.62 5.68 22.96 45.90 19.94 349.05 5.85 18.89 23.65 25.18 370.58 6.35 23.15 24.63 1963.32 4.29 139.71 24.86 15.53 4.21 3.81 18.35 7.10 158.32 17.07 7.13 139.33 7.63 16.33 53.25 15.73 85.75 15.09 16.55 38.16 16.02 12.64 17.23 47.34 41.66 67.69 66.62 251.19 r 216 r 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 APPENDIX C. DETAIL RESULTS 86 avg j C [h] ] pax-trip avg / , i j min U [ ] pax-trip avg / , o j min U [ ] pax-trip / avg j min U [ i /β Table C.3: Optimal results for Jitney-lite service j [*1000 h] z j M [veh] j n 4244 565 2210 645 49.35 685 11.64 80 24027 56.6031 44.12 8010 22.09 65.32 125 101.21 4326 21.24 7447 23.86 64.82 136.02 3605 32.32 395.49 37.74 6.6211 23.73 108 301.84 5.336 252 142.36 7.3613 24.10 38.01 85 77.41 31.34 385 7.829 10.76 101.73 38.22 7.2512 15.47 114 51.88 3519 15.91 59.75 154.42 7.329 11.05 16.49 207 38.86 7.27 88.80 1204 24.50 51.54 369.05 26.98 10.572 82.27 16.48 189 15.51 131.86 49.83 61.61 35.89 144 102.94 26.96 94.47 16.77 72 8.12 37.22 77.84 40.83 24.07 201.82 15.51 18 1724.15 27.65 91.33 119.71 37.73 36.37 15.17 26.52 7.46 31.29 193.03 120.53 13.56 8.26 36.09 12.09 30.73 654.27 36.03 5334.71 31.89 10.12 2672.90 34.66 5.02 33.66 28.43 19.66 9.35 28.73 170.34 28.95 1860.65 7.32 27.61 2861.55 8.15 21.50 131.86 4.61 554.31 175.60 26.73 24.57 628.15 181.36 25.51 15.05 1323.62 423.18 478.35 26.17 r 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 APPENDIX C. DETAIL RESULTS 87 avg j C [h] ] pax-trip avg / , i j min U [ ] pax-trip avg / , o j min U [ ] pax-trip / avg j min U [ i /β Table C.3: Optimal results for Jitney-lite service j [*1000 h] z j M [veh] j n 2446 202 322 447 6.85 908 14.13 166 31.54 165 33.96 1334 5.24 112 19.743 19.50 10.27 96 86.575 20.56 105 96.133 22.57 725 79.72 57 4.77 18.51 43.83 4.0110 19.00 75 33.35 5.274 28.91 57 31.29 6.816 22.67 95 2002 32.77 59.50 3.97 14.97 37.34 4.063 15.50 34.48 80 8.486 35.22 15.29 67.38 168 165.49 6.683 37.15 15.77 34 7.134 33.05 39.09 42 129.80 8.99 14.54 101.81 91.83 38.05 14.94 60 24.87 36.96 7.87 65.03 40.40 12.75 33 24.61 8.30 586.27 16.12 36 6.77 45.38 25.64 46.38 45.47 104.17 28.36 8.27 23.47 17.36 394.38 8.66 8.16 23.97 27.35 25.75 172.89 21.99 28.85 8.37 145.75 18.78 11.60 26.28 696.72 19.20 29.78 7.26 28.30 482.91 18.49 32.24 6.55 386.66 4.98 33.87 114.38 37.01 5.19 166.49 306.84 4.62 146.55 16.71 15.43 501.45 240.44 13.80 14.01 210.19 13.88 271.32 88.25 92.71 53.75 r 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 APPENDIX C. DETAIL RESULTS 88 avg j C [h] ] pax-trip avg / , i j min U [ ] pax-trip avg / , o j min U [ ] pax-trip / avg j min U [ i /β Table C.3: Optimal results for Jitney-lite service j [*1000 h] z j M [veh] j n 2424 223 282 182 8.02 562 18.81 393 9.25 342 36.69 263 23.63 32 20.782 16.96 22.25 393 14.39 30 19.814 28.51 12.86 484 29.48 33.34 24 5.34 3.794 32.95 12.10 487 30.40 28.36 72 4.53 6.395 34.32 9.01 24 6.026 30.25 27.59 76 15.44 7.575 34.31 13.17 70.26 161 5.895 32.99 16.96 70 15.29 7.123 22.12 72.99 90 32.13 64.65 6.014 33.87 23.46 60 139.93 6.61 41.48 33.91 25.38 63.15 75 7.10 24.89 24.51 34.90 39 49.88 159.42 35.32 27.21 31.36 60 5.30 38.76 7.37 112.82 24.23 27.95 8.15 97.66 22.14 27.69 21.64 3.48 76.00 23.19 25.89 57.64 8.62 211.71 20.39 10.00 26.83 58.37 22.42 26.50 6.74 192.54 21.23 25.75 7.18 140.46 23.02 21.41 5.60 26.70 28.76 153.97 6.88 145.06 6.05 108.96 15.40 7.24 37.21 16.01 116.27 14.79 1130.87 15.54 103.80 15.19 614.60 15.78 170.76 508.79 109.56 88.73 r 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 APPENDIX C. DETAIL RESULTS 89 avg j C [h] ] pax-trip avg / , i j min U [ ] pax-trip avg / , o j min U [ ] pax-trip / avg j min U [ i /β Table C.3: Optimal results for Jitney-lite service j [*1000 h] z j M [veh] j n 4254 362 264 753 25.03 484 9.41 168 42.20 445 42.06 306 18.10 7.91 644 33.29 88 22.484 22.87 14.52 854 20.84 25.82 60 4.472 61.57 40 19.112 20.87 70.23 84 5.91 7.014 19.68 44.34 88 6.012 33.93 28.09 267 20.08 13.63 73.72 28 4.15 5.533 34.10 84.58 96 16.56 4.745 19.91 15.86 9.30 34 6.9914 19.51 14.83 14.87 231 5.173 52.96 36.64 38.91 27 14.95 7.65 38.45 15.33 12.36 40 161.95 201.05 476 5.02 220.45 14.94 22.22 4.87 71.24 22.98 26.94 13.14 45 9.37 40.22 14.90 26.23 458.15 44.98 9.79 66.55 25.06 26.44 47.71 84.50 14.89 17.35 5.98 6.25 415.62 19.25 14.64 47.43 10.30 129.63 18.48 27.27 7.21 130.93 14.01 28.66 89.15 22.99 16.25 4.57 59.05 16.73 14.66 29.93 4.14 131.35 33.70 135.40 17.86 6.90 169.22 77.75 14.67 32.77 666.23 14.33 368.59 212.82 16.09 78.33 762.52 59.45 285.85 r 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 APPENDIX C. DETAIL RESULTS 90 avg j C [h] ] pax-trip avg / , i j min U [ ] pax-trip avg / , o j min U [ ] pax-trip / avg j min U [ i /β Table C.3: Optimal results for Jitney-lite service j [*1000 h] z j M [veh] j n 3824 422 1123 322 15.46 36 43.534 206 11.71 332 24.26 183 22.26 13.04 40 21.983 23.92 783 24.15 5.78 162 18.28 27.09 45 6.293 20.63 63.57 54 6.663 19.94 8.90 30 6.943 26.27 20 21.54 4.363 20.76 34.85 54 4.702 30.58 15.97 14.13 42 15.32 5.132 9.30 60 19.012 30.90 17.21 52.46 48 4.30 4.932 33.42 13.91 15.95 36 6.301 265.01 20.45 15.93 25.47 22 733.59 14.81 40.19 20 3.91 20.25 6.80 202.00 32.80 14.13 18 17.24 8.34 52.32 22.68 15.83 16.52 9 4.87 29.09 34.98 24.28 13.81 47.81 24.21 11.46 4.91 15.09 8.13 25.40 24.10 117.67 6.21 6.65 59.67 21.05 25.09 8.86 121.40 20.16 15.58 7.26 18.54 23.71 15.34 8.04 133.43 24.67 21.00 5.37 162.97 16.03 4.85 87.30 26.12 4.35 16.95 59.01 82.04 17.37 4.48 277.70 15.68 407.21 15.31 70.88 14.19 230.02 16.53 32.45 29.40 26.47 13.01 r 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 APPENDIX C. DETAIL RESULTS 91 avg j C [h] ] pax-trip avg / , i j min U [ ] pax-trip avg / , o j min U [ ] pax-trip / avg j min U [ i /β Table C.3: Optimal results for Jitney-lite service j [*1000 h] z j M [veh] j n 1214 153 162 142 5.10 442 10.99 303 4.73 264 35.41 324 24.81 36 25.622 19.38 10.15 483 19.91 68 25.513 27.25 25.18 525 27.64 47.48 38 6.26 4.223 30.65 60.69 573 32.29 47.81 69 5.97 5.314 33.70 16.00 65 4.943 31.58 22.51 78 19.36 6.072 32.53 15.16 45.26 48 7.073 29.30 58.33 80 19.54 8.092 34.86 21.94 32.25 45 7.454 34.53 22.71 31.23 26 92.82 7.81 23.68 38.53 24.58 31.85 24 6.38 29.10 25.22 27.82 22 87.08 8.20 66.85 40.81 25.61 9.89 48 8.43 45.07 31.54 24.13 12.66 10.08 175.78 35.31 24.72 7.99 6.34 91.94 32.34 22.92 40.59 11.27 102.76 26.66 31.01 7.28 72.63 29.95 26.09 28.45 8.87 105.16 32.80 6.98 79.98 29.29 22.77 29.54 248.43 5.93 4.18 398.51 24.26 206.04 26.44 4.87 5.91 100.11 25.36 552.02 25.08 139.39 25.77 562.24 27.94 132.74 23.38 174.61 70.89 141.14 74.05 r 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 APPENDIX C. DETAIL RESULTS 92 avg j C [h] ] pax-trip avg / , i j min U [ ] pax-trip avg / , o j min U [ ] pax-trip / avg j min U [ i /β Table C.3: Optimal results for Jitney-lite service j [*1000 h] z j M [veh] j n 4364 684 212 1503 63.45 522 14.32 40 61.074 365 28.72 332 32.46 29.90 283 25.60 13.73 48 39.373 16.54 554 22.02 15.41 30 7.713 18.95 25.37 33 3.534 24.67 42.98 30 10.803 19.75 10.99 44 6.248 22.15 25.37 36 4.923 20.84 24.75 21.53 64 7.723 20.06 22.07 31.71 27 28.57 5.197 23.00 28.46 168 6.272 20.61 15.78 37.75 21 5.744 103.33 19.87 14.04 12.95 42 70.67 5.34 30.88 19.79 16.95 1062.50 119 6.63 21.61 14.56 9.78 30 5.46 150.16 23.11 15.88 15.38 48 104.44 5.01 58.68 19.08 15.09 27.28 5.18 225.97 14.71 11.12 5.82 94.40 16.37 26.29 18.09 7.22 77.34 22.21 15.16 25.16 4.38 138.77 14.87 9.55 80.49 23.23 14.61 191.83 20.91 15.80 3.85 6.25 49.17 7.89 15.89 44.88 14.69 17.72 6.71 64.50 5.78 53.16 14.24 180.70 15.96 17.27 75.87 1142.53 16.52 15.13 61.72 264.45 179.37 191.24 136.84 r 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 APPENDIX C. DETAIL RESULTS 93 avg j C [h] ] pax-trip avg / , i j min U [ ] pax-trip avg / , o j min U [ ] pax-trip / avg j min U [ i /β Table C.3: Optimal results for Jitney-lite service j [*1000 h] z j M [veh] j n 9233 2164 2014 42 87.686 308 10.38 52 3222 42.342 17.21 102 37.904 42.74 120 134.482 19.70 48 38.014 29.02 26 46.512 26.81 132 10.53 37.532 21.80 28.64 26 5.052 9.45 52 25.44 53.25 6.724 34 22.96 4.904 9.59 34 27.37 10.48 6.204 43.85 39.23 343 14.65 19.19 80 35.65 7.56 53.194 22.30 13.42 68 7.122 21.91 13.47 1546.95 68 34.53 27.05 10.084 31.35 15.60 33.63 60 57.89 35.62 27.91 72 5.58 12.95 17.87 63.43 34.81 43.07 26 15.85 87.41 33.51 22.62 40 5.60 2328.77 33.77 6.23 76.83 36.20 47.32 7.44 32.79 14.04 40.24 30.07 669.76 7.37 32.63 25.92 811.69 7.57 27.36 28.93 141.45 8.93 33.07 25.13 7.73 22.09 28.18 873.45 168.38 7.49 19.89 27.44 8.50 25.94 167.52 7.97 81.28 27.27 5.96 100.36 25.06 4.76 225.63 25.13 232.14 18.86 546.35 25.10 464.88 16.13 196.46 15.14 385.51 208.60 72.12 59.07 r 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 APPENDIX C. DETAIL RESULTS 94 avg j C [h] ] pax-trip avg / , i j min U [ ] pax-trip avg / , o j min U [ ] pax-trip / avg j min U [ i /β Table C.3: Optimal results for Jitney-lite service j [*1000 h] z j M [veh] j n 2331 303 362 394 10.94 163 19.58 306 14.62 186 5.68 367 23.44 15.66 337 21.33 8.93 7211 21.42 27.36 667 16.85 56 26.19 6.5810 19.28 38.69 98 242 5.7610 36.17 19.53 6.21 18.78 25.14 119 120 21.09 35.16 6.82 98.87 90 4.98 20.93 16.85 45.76 20.20 15.57 4.46 91.15 4.67 19.93 15.21 44.31 5.24 23.32 38.26 19.37 5.73 188.00 14.30 36.58 5.49 101.95 30.49 15.07 4.09 259.41 14.11 30.02 6.28 9.57 15.85 98.29 85.77 15.20 7.13 5.58 14.71 50.33 53.16 15.83 4.31 92.86 17.04 28.69 205.60 29.46 189.82 24.92 162.09 25.71 626.95 1668.45 774.31 181.58 262.31 r 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216