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:~ '° Regional hnsportation Authority Development Planning Office Chicago, Illinois August , 1980 Southwest Corridor Study Alternatives Analysis

DEMAND ESTIMATION METHODOLOGY FOR THE FINAL SCREENING OF ALTERNATIVES

The preparation of this report has been financed in part through a grant from the U.S. Department of Transportation, Urban Mass Trans­ portation Administration, under the Urban Mass Transportation Act of 1964, as amended.

Development Planning Office Regional Transportation Authority Chicago, Illinois August, 1980 Report written by:

Thomas A. Weaver Division of Public Transportation Illinois Department of Transportation RTA Southwest Corridor Study Project Manager, 1978-1980

Barbara F. Sloan Senior Planner Regional Transportation Authority author of the computer program for the Southwest Corridor Study CONTENTS

CHAPTER ONE: INTRODUCTION

• Overview of the Final Screening 1-1

• Methodological Needs and Constraints 1-1 • Generation and Distribution 1-2 • Mode Choice and Assignment 1-2 • Other Trip Destinations 1-2 CHAPTER TWO: FORMULATION OF THE NETWORKS • Geographic Areas of Analysis 2-1 • Highway Network and Auto Cost 2-1 • Transit Network 2-2 • Calibration of the Transit Network 2-3 • Station Coordinates 2-3 • Access Links 2-3 • Line Haul Travel 2-4 • CBD Egress Times 2-5 • User Costs 2-6 • Minimum Path Algorithm 2-6 CHAPTER THREE: OTHER COMPONENTS OF THE METHODOLOGY • Trip Tables 3-1 • Trip Distribution 3-1 1 Total Number of Trips 3-1 • Mode Choice Model 3-2 • Multipath Transit Assignment 3-3

1 User Benefit 3-4 CHAPTER FOUR: ANALYSIS OF RESULTS • Network Sensitivity and the Theta Value 4-1 1 Objective #1: Line Volume Accuracy 4-1 1 Objective #2: Replication of Bus-Rail Competition 4-2 • Objective #3: Significant Differences Among Alternatives 4-3 1 Objective #4: Realistic Prediction for Non-minimum Paths 4-3 1 Conclusion 4-4 • Analysis of Line Volumes in the Base Network 4-4 • Rapid Transit and Bus 4-5 • Commuter Railroad 4-5

Appendix: Acknowledgments CHAPTER ONE:

INTRODUCTION OVERVIEW OF THE FINAL SCREENING

The Southwest Corridor Study is being performed by the Chicago Department of Public Works, the Regional Transportation Authority, the Chicago Transit Authority, the Chicago Area Transportation Study, and the Illinois Department of Transportation to determine the pre­ liminary transit system design that is best able to improve travel between the Southwest Side of Chicago and the central business district (CBD). Four conventional technologies have been examined: rapid transit, light rail, busway, and commuter railroad. The total number of alternatives examined--approximately 600--is based on the number of alternative paths from terminus to terminus that the new line could take. The purpose of the Final Screening phase of the study has been to pare down the number of alternatives to approximately ten. This reduction is essential for a thorough evaluation of the best alter­ natives. The criteria used in the Final Screening include the costs of construction and rolling stock, predicted demand for the new line, changes in overall transit ridership, user time savings, operating costs, and a wide variety of non-user impacts. The means by which demand (ridership) and.user benefit were estimated are the subject of this paper. The demand for travel to the CBD and the potential user time savings were computed by means of a program written in Fortran IV for use on an IBM 3033 computer. The program used a CBD-oriented transit network, 1975 and 1990 trip tables (as input), a mode choice model, and a multipath transit assignment method. Each of these components of the program will be described in detail in this paper.

METHODOLOGICAL NEEDS AND CONSTRAINTS

Due to the high priority placed on this study by all partici­ pating agencies, it was considered necessary to develop, test, and apply a transit network and model(s) to the Southwest Corridor as quickly as possible. These steps were successfully completed within a seven month period (March-October 1979). The analysis began with the program and model of the RTA's recent Study of New and Replacement Rail Transit Alternatives (SONARRTA). However, in spite of the time frame, several changes were desired in the generation-distribution-mode choice-assignment process; these are highlighted below. 1-2

Generation and Distribution

In SONARRTA, the overall number of trips from all zones to the CBD is kept at a fixed number for a given forecast year. The study's simultaneous distribution-mode choice model allows that as accessi­ bility to the CBD improves for a given zone, its total number of trips will increase; however, the increase is deducted from other zones in order that the overall number of trips remain constant. This was viewed as undesirable for the testing of the Southwest Corridor alternatives. In the latter case, the important factors were considered to be travel time savings and usage of the new line in the short-term future; potentials for changes in land use and travel patterns were expected to be marginal and less predictable. Most importantly, however, the "deduction" phenomenon mentioned above was viewed as theoretically invalid in this case. For evaluating long-term travel impacts, the best approach would be for trip generation--and distribution to the CBD--to increase somewhat when a new transit line improves CBD accessibility. A second, and more short-term, approach would be to fix all zone­ to-CBD distributions. In this manner, improved accessibility could alter only mode choice--not generation or distribution--and the results would apply only to existing travel to the CBD. Since there was not enough time to develop, test, and apply new generation and distribution models, the second approach was used.

Mode Choice and Assignment

In order to use a fixed generation-distribution trip table, it was necessary to replace SONARRTA's simultaneous model with a mode choice one; fortunately, SONARRTA developed a mode choice model calibrated and successfully tested for the Chicago area. With only a moderate number of changes, SONARRTA's minimum path algorithm could be retained for use in this analysis, thereby saving consider­ able time.

A multipath transit assignment proces~ was considered necessary as a replacement for the typical all-or-nothing approach, to better reflect actual behavior, improve the accuracy of the estimated station and line riderships, and replace SONARRTA's logit-type "sub-mode choice" model for bus and rapid trans it. It was correctly predicted that the selected multipath assignment could be made operational within a very short period of time, i.e., approximately one week.

Other Trip Destinations

From the network tests performed as discussed in Chapter 4, 1-3 it was concluded that the network method predicts CBD-bound trips with considerable accuracy. The demand for two other trip types, however, was not computed as part of this effort. As trips passing through the central area but destined elsewhere ("through trips") were assumed to be in proportion to CBD-bound demand, there was no need to add such trips to the totals in order to discern differ­ ences among competing alternatives. "Local demand" (trips using the system but not reaching the CBD), however, will vary from alter­ native to alternative. Due to a lack of the time necessary to calibrate and validate an appropriate local demand model, accessi­ bility measures developed by DPW were used as surrogates. CHAPTER TWO: FORMULATION OF THE NETWORKS GEOGRAPHIC AREAS OF ANALYSIS

The Southwest Corridor Study focuses on the Archer Avenue­ Stevenson Expressway corridor in the City of Chicago. However, for purposes of estimating overall impacts, a much larger study area was defined, as bounded by Madison Street on the north, State Street on the east, lllth Street on the south, and the Cook-DuPage County Line on the west {see Exhibit 2-1). This area extends fifteen miles east­ west and thirteen miles north-south. 1 The central area of Chicago was defined to include both the 11 11 central business district ( Loop ) and adjacent areas. Its defined boundaries are Chicago Avenue on the north, Lake Michigan on the east, Roosevelt Road on the south, and Halsted Street on the west; the total land area is three square miles. For purposes of trip measurement, the study area was divided into 367 zones, excluding the central area. Most of the zones were either of square-mile of quarter-section in size; the latter were located in the area of principal interest. The central area was divided into twelve quarter-sections. Each zone was given a centroid location, which was coded by means of an electronic digitizer at the University of Illinois at Chicago Circle by UICC personnel. The centroid was placed in the center of each zone unless the land use patterns called for a different location.

HIGHWAY NETWORK AND AUTO COST

The highway network consists of a 367-by-12 matrix of auto travel times from each of the Southwest Side zones to the twelve CBD zones. These 11 highway 11 times are a product of the Urban Transportation Planning System network model for the Chicago region which is maintained and operated by CATS. The actual highway system on which the times are based is the base network which existed in 1970. These figures were then increased by a factor of ten percent to account for a more congested highway network in 1990. In validating the mode choice and assignment models, the 1975 base system was tested. It should be noted that in testing the 1975 network, the 10% congestion factor was excluded from the auto times in order to simulate a realistic situation. Where Southwest Side zones were divided into quarter-sections, each of the smaller zones was assumed to have the same auto travel times to the CBD as did the full section of which it is a part.

1However, in order to more clearly show differences among the various new alternatives, a "primary impact area 11 was defined, as shown in Fig. 2-1. ' ·~

Exhibit 2-1 MAP OF THE SOUTHWEST CORRIDOR STUDY AREA

The Primary Impact Area was developed for demand estimation purposes. 2-2

The cost of the auto line-haul trip to the central area was cal­ culated by multiplying auto travel distance (average distance from each zone to the four Loop zones) by a variable cost factor of 8.5 cents per mile; a $1.50 parking charge was then added. The parking figure was developed for the SONARRTA study and is the figure used in calibrating the mode choice model. The variable cost of 8.5 cents per mile is the sum of the following three items: maintenance cost = 1.10 cents/mile tire cost = .65 cents/mile gasoline cost = 6.75 cents/mile

The first two fig~res are 1979 estimates made by the American Automobile Association. The cost of gasoline was computed by dividing the estimated 1990 cost of a gallon of gasoline by the estimated average mileage in that year, estimated at 25 miles per gallon by the National Highway Traffic Safety Administration. The assumed 1990 cost per gallon of gasoline is 167.7 cents in constant 1979 dollars. This figure repre­ sents the average of two scenarios: a decontrol of 11 old 11 domestic oil and an embargo.3 However, this predicted increase in the real cost of gasoline was nearly offset by the assumed 67 percent increase (from 15 to 25 mpg) in fuel efficiency.

TRANS IT NETWORK

The transit network includes rapid transit, light rail (new alter­ natives), commuter railroad, and bus modes and represents the line-haul portion of trips to the CBD by transit. The network is constructed from a set of stations and links. The stations include all of those on existing lines, plus the envisioned stations on new alternative lines. The one exception was that on light rafl lines where quarter-mile station spacing was assumed, stations were coded at half-mile inter­ vals, as suggested by the size of the travel zones. In all uses of the network, the existing transit lines were assumed to be in operation. For rapid transit, these include the Lake Street Elevated, Congress, Douglas, Dan Ryan (via the State Street subway), and South Side/Englewood Elevated (via Loop El), as shown in Exhibit 2·-2. To represent current Archer Avenue and Stevenson Expressway bus routes (which carry the majority of Southwest Side transit riders), a generalized Archer Avenue Bus Line (AABL) was coded into the network with half-mile "station" spacing. Its running times are similar to those of the Archer Avenue Express route (62EXP). The included com­ muter railroad lines are the Chicago & North Western's west line, Burlington Northern, the ICG-GM&O line, Norfolk & Western, and the

. 2AAA, "Your Driving Costs," 1979 edition. 3RTA internal staff memorandum, Nov. 1977. Ci) .c ,..OJ ,..

- _ \_

Ex hi bit 2-2 TRANSIT LINES USED IN THE BASE NETWORK

111111111111111 bus rapid transit commuter railroad 2-3

main line and Beverly Branch stations of the former Rock Island lines. Stations south of lllth Street were not coded into the network. Stations on new alternative lines were coded in a like manner. When a line was to be tested with the existing system, its stations would be 11 opened" in the program and would thus become a functioning part of the network. At other times, the stations would remain 11 closed, 11 or non-operative.

CALIBRATION OF THE TRANSIT NETWORK

Station Coordinates

' ' Calibration of the network refers to the process by which the I travel times are computed among the various stations and zone centroids. The first step was to code the station locations. The UICC digitizer assigned x-y coordinates on a scale of ten units to the mile, as was · done with the zone centroid locations. The computation of distances and travel times for these links is discussed in the next two sections. .' I

Access Links I I,

To determine the range of access links, an array of all realis­ tically possible station choices for each zone was developed by per­ sonnel at RTA and UICC. The distances that these links represent were then computed on a right-angle basis to be consistent with the grid pattern of Chicago streets. The set of speed and time formulas, shown in Exhibit 2-4, was developed with varying assumptions of /, access mode split and bus operating speeds. These variations were made on a geographic basis, with four zone "types" as shown in Exhibit 2- 3. Zone Type I consists of most of the Chicago portion of the study area . The assumed bus speed was 6 minutes per mile (10 mph). Of those who arrive at transit stations by vehicular means, it is assumed that all suc·h trips would be by bus. For all zone types, station- zone pairs are assigned to the walking mode if the distance is less than, or equal to, one-half mile; no walk trips are assumed if the di stance is greater than that. Zone Type II includes areas with commuter railroad stations and a limited degree of usage of that mode. However, these areas have a strong CTA orientation for travel to the central area. As shown in Exhibit 2-3, Type II includes Oak Park, Cicero, Garfield Ridge, Summit, Brighton Park, Ashburn, and Beverly-Morgan Park. The assumed bus speed N rr1 0 x z :::::r rr1 CT ~ -< rl" -a rr1 N (/) I w Exhibit 2-4. TRAVEL TIME ASSUMPTIONS FOR ACCESS BY AUTO AND BUS

Ta = travel time by auto, in minutes Tb = travel time by bus, in minutes S = distance, in miles

Zone Type I (100% by bus)

Tb = 7.3 + 6 S bus speed= 6 min./mi. (10 mph) walking time= 3.8 min. waiting time = 3.5 min. Zone Type II (23% by auto, 77% by bus)

Ta = 4 S auto speed= 4 min./mi. (15 mph) bus speed= 5.5 min./mi. (11 mph) Tb = 10.5 + 5.5 S walking time= 6.5 min. waiting time = 4 min. Zone Type III (80% by auto, 20% by bus) Ta = 3 S auto speed= 3 min./mi. (20 mph) bus speed= 4.3 min./mi. (14 mph) Tb = 14.5 + 4.3 S walking time= 10 min. waiting time = 4.5 min. Zone Type IV (95% by auto, 5% by bus)

Ta = 3 S auto speed= 3 min./mi. (20 mph} bus speed= 4 min./mi. (15 mph) Tb = 12.5 + 4 S walking time= 7.5 mi. waiting time = 5 min.

All of the above formulas do not apply to station access by walking. Sources 1 CTA operating schedules 1 CTA, 11 8us and Rail Systems--Operating Facts 11 11 11 1 Lee and Permut, CBD Demand Estimation Models , SONARRTA Working Paper #3, September 1976. 2-4 is 5.5 minutes /mile (11 mph), and the access mode split is 23 percent auto, 77% bus. The split was taken from Illinois Department of TraQs­ portation (IDOT) passenger survey results and was used in SONARRTA. 4 Zone Type III is primarily suburban but has some CTA service on its arterial streets. This includes Evergreen Park, Hometown, and parts of Bedford Park and Burbank near Ford City. These assumptions are a 4.3 min./mi. bus speed and an 80%-20% auto-bus access split. Zone Type IV includes suburban areas with no CTA service; how­ ever, some of the co1T111uter railroad stations have feeder buses. The assumptions are a 4 min./mi. bus speed and a 95%-5% auto-bus split. The access mode splits for Zone Types III and IV are based on com­ muter railroad passenger surveys taken in recent years. After computation of access times, access costs were converted to equivalent minutes (at a rate of four cents per minute) and were added to the times. The resulting figures were stored in an array, to be used in the computation of door-to-door times necessary for the use of the mode choice model.

Line Haul Travel

Distances between consecutive stations were computed on an air- 1ine basis. However, in a few cases where the routes were especially circuitous, distances were calculated by hand. Speed-and-time formulas were developed for the various modes and operating conditions, as shown in Exhibit 2-5. All rapid transit lines are assumed to have exclusive rights-of-way. A top running speed of 45 mph is assumed, together with thirty-nine seconds lost at each station due to deceleration, dwell times, and acceleration. As a result, the overall speed is considerably less than 45 mph. Exhibit 2-5 al so includes a formula for 1inks where the stations are less than 0.3 miles apart. This formula is only applicabl~ to the CBD, as the assumed station spacing on the Southwest Side generally is one mi 1e for rapid trans it and one-ha 1f mile for 1i ght ra i 1. Where light rail rights-of-way would be exclusive, their assumed speeds would be equal to those of rapid transit. It is assumed that no loss of running time would result in the fare collection process, as turn­ stiles and "paid areas" must be provided for light rail stations within such rights-of-way in a high demand corridor. Most of the light rail rights-of-way, however, would be in mixed traffic or on dedicated portions of street rights-of-way. The former would perform in a manner similar to that of a local bus and are assumed to operate at six minutes per mile. Ttie latter type, termed "semi-exclusive," would be separated from concurrent traffic but not

4Inwon Lee and Howard Permut, 11 SONARRTA Working Paper IV: RTA Regional Rail System Computer Network, 11 January 1977, p. 5. Exhibit 2-5. LINE-HAUL TRAVEL TIME ASSUMPTIONS

T = travel time, in minutes S = distance between stops, in miles Rapid Trans it

If station spacing is~ 0.3 mi.: T = 1.33S + 0.65 If station spacing is less than 0.3 mi.: 1 T = l.62S72 + 0.33 Light Rail A. Exclusive right-of-way: same as rapid transit B. Semi-exclusive right-of-way: T = 4S (V = 15 mph) C. In mixed traffic: T = 6S (V = 10 mph) Bus Busway cruise speed: V = 50 mph In mixed traffic (on street):

bus stop spacing T 0.125 mi. 6S (V = 10 mph) 0.25 5.5S (V = 11 mph) 0.5 5S (V = 12 mph) 1.0* 4S (V = 15 mph) (*primarily suburban operations) Commuter Railroad From CBD terminal to first station: T = 3.8S (V = 16 mph) Between all other stations: T = 2.4S (V = 25 mph) Sources Vuchic & Newell, Transportation Science (vol. II, no. 4, Nov. 1968) DeLeuw, Cather & Co., Light Rail Transit (USDOT, UT-50009, Spring 1976) Vuchic, Light ~ail Transit Systems: .fl Definition and _Evaluation (PB-213-447, Oct. 1972) Characteristics 0f Urban Transportation ?ystems, 1975 Commuter timetables for GM&O, N&W, C&NW, Milwaukee Road, and C&WI (abandoned in 1963) \ !' 2-5 from cross-traffic or int~~secting railroads. It would operate at an as surried rate of 4 min. /,mi . .. As shown in the exhi;bits, the fomulas for rapid transit and light rail were based on a variety of primary and secondary sources. To confirm their accuracy, the rapid transit formulas were applied to the CTA's West-Northwest system and the Howard and Dan Ryan lines. It was found that the predicted running times closely resemble those contained in the CTA operating schedules for those lines. Bus speeds were based on bus stop spacing, with an overall range of 4-6 min./mi. (10-15 mph) except in the central area. A primary source utilized in the development of the speeds was the CTA and suburban operating schedules for Southwest area bus routes. To estimate downtown bus speeds, CTA operating schedules and State Street Mall planning data were examined. It was found that even after completion of the mall project, peak bus rgnning times on State Street were predicted to be less than 5 mph. Commuter railroad speeds for new alternatives were estimated by first examining the schedules of current and recently-abandoned commuter railroad operations in the City of Chicago.6 In much of the Chicago portion of the new alternatives, a relatively slow speed of 3.8 min./mile was assumed because of the relative abun­ dance of major junctions, yards, crossovers, and terminals; current schedules of the commuter railroads do, in fact, reflect such slow speeds between the downtown terminals and the first outlying station. Throughout the remainder of the new alternative routes, operations were assumed to be at 2.4 minutes per mile. For the existing commuter railroad lines in the network, the program did not compute the travel times. .Instead, the existing schedules were used to assign travel times between the downtown terminals and each outlying station. ·

CBD Egress Times

The egress portion of the trip consists of the travel between a cordon point and a central area zone centroid. Three measurements were needed for each such trip. The first two were 1) the time from the cordon line to the appropriate CBD station on the line, and 2) the station egress time. For rapid transit, the cordon-to-station times were primarily based on the travel time formulas included in

5It was found later that this slow speed significantly affected the ridership potential of the busway alternatives. 6The last schedule of the Chicago &Western Indiana commuter operation, abandoned in the early 1960 1 s, was used because of its frequent stops within Chicago, as would be the case with a Southwest line. 2-6

Exhibit 2-5. Station egress time was set at 1.5 minutes. For light rail, a 6 min./mi. operation was assumed for State Street, with no egress time from these surface level vehicles. Three different speeds were used for buses: 15 min./mi. on a bus-only State Street Mall, 13.4 min./mi. on other streets in the Loop, and 7.5 min./mi. on streets outside the Loop (e.g., Grand Avenue, Canal Street, and Roos­ evelt Road). As with light rail, no egress times were needed for deboarding. The third measurement was for travel between the egress station and the zone centroid, i.e., the ultimate destination. A walking pace of 20 min./mi. was assumed. However, if this portion of the trip would be greater than one-half mile, it was assumed that the traveler would wait for the bus. Waiting times were assumed to be three minutes. if only one route were available for the trip; this was altered to 1.5 minutes if one of the high-frequency Loop express shuttle routes (e.g., #120, #121, #129) was available. However, if two or more routes were available, the waiting time was reduced to one minute. Once these computations were made, a matrix of total egress times was developed for 12 centroids X 24 cordon points. These values were stored in an array for use in the minimum path algorithm.

User Costs

The assumed out-of-pocket costs for transit riders consist of the fares charged on the system. The CTA line-haul fare was assumed to be fifty cents, as it was during the time of the analysis. For the portion of riders who were assumed to use buses for access to outlying stations, the access link cost was ten cents. It was assumed that fare increases would equal the inflation rate; therefore, there would be no fare increases in real terms. The first RTA zone fare system (effective in 1976 on BN, MILW, and ICG, and on C&NW in 1977) was assumed for all commuter railroad lines. Per-ride costs were based on a weighted average of ticket types (monthly, weekly, one-way, etc.), as was developed for SONARRTA. 7 These prices were 70¢ for zone B, 81¢ for zone C, and 91¢ for zone D. As with rapid transit, it was expected that fare increases would equal the inflation rate. For persons arriving at outlying commuter railroad stations by bus, a 50¢ access cost was included.

MINIMUM PATH ALGORITHM

The minimum path algorithm developed for the Southwest Corridor demand model is based on the algorithm developed for the SONARRTA

7Howard Permut, "Specification of Inputs for Line Screening and System Optimization Demand Estimation," SONARRTA working paper, Nov. 1976. 2-7

study, 8 with modifications enabling a more detailed look at the study area. Each station in the network has a set of "nearest neighbors" in an outbound direction. For a given station, the nearest neighbor would be the next station reached when traveling away from the CBD on a certain line. Stations at the outbound end of the line would have no nearest neighbors; all other stations would have at least one. Minimum path computations start by searching out from the cordon line stations, which exist for the network being tested, to the nearest· neighbor stations. Station-to-station link times are added up as the paths are built. When a new station is reached, it is assigned a "station time" equal to the sum of the link times required to arrive there from the CBD, plus the egress time from the cordon line to the particular CBD zone (the algorithm runs through a complete cycle for each of the twelve central area zones). If a station is reached which has already been assigned a time from another path, the program com­ pares the two times and stores the shorter one along with the closest station inbound on the minimum path. At the conclusion of the algor­ ithm, a 432 X 12 matrix exists of minimum travel times fro~ each of the 432 stations to each of the twelve central area zones. At this point, every station included in the test network (i.e., the 11 open 11 stations) has assigned to it a travel time to each of the twelve central area zones. Associated with each of these travel times is the number of the next closest station toward the CBD. It should be noted that the algorithm is able to distinguish between rapid transit stations, light rail stations, commuter railroad stations, and bus stops, based on the assigned station number. A maximum of seventy-three zones were assigned to each station in the entire network. These assignments were based on logical service area demarcations for each station. There was no limit to the number of stations to which a zone could be assigned; however, each zone was coded to at least one station on the base (existing) system. Each station-zone pair had associated with it an access travel time from the zone centroid to the station, as discussed above. The next step in the algorithm is to add zonal access times onto the previously computed station times, with the resulting data referred to as "zone times." For each station in a particular network run, zone time is computed for each zone coded to that station. The algor­ ithm computes a zone time for every zone on the following basis: 1) commuter railroad--minimum path

8Alex Anas and Steven Arenson, "A Procedure for Computing Paths of Minimum Travel Times to the CBD--A Report and User's Manual," 1976. 9A11 station times are initialized at 999. minutes, so stations not included in a particular network run--and never reached in the path-building procedure--end up with a "station time" of 999. minutes. 2-8

2) Archer Avenue Bus Line--minimum path 3) rapid transit and light rail--minimum and second-to­ minimum path These times, along with the auto times, are stored for later use in the mode choice model, which is explained in Chapter Three. Exhibit 2-6. SCHEMATIC REPRESENTATION OF THE MINIMUM PATH ALGORITHM

sfa. 2.

I I I I I -.( I~-- ZOl!flj- I I I I I I I

~/0 II 1. Alternatives (circled numbers above) are specified, allowing the stations shown on the new line to be used in the network. 2. The specified alternatives determine the "cordon strategy, 11 which permits the CBD egress link between i and station 413 to be considered (the 11 strategy 11 is designed to reduce computation time in this step). Existing station #1 is also linked to centroid i. 3. The path through stations 413-89-90-91-92-93 is built with the use of the outbound nearest neighbor matrix.

4. Access links, such as that between station 93 and zone j, are pro­ vided for by another array. 5. The algorithm has built complete paths between i and j. In this case, there are four possible paths, each characterized by a different access station (8, 9, 92, and 93).

11 11 6. Overall travel times ( zone times ) are computed for the four paths. The quickest path will be used in the mode choice model; the three quickest paths (maximum of two by rapid transit and one by bus) will be used in the assignment phase. The slowest path is discarded in this case. CHAPTER THREE: OTHER COMPONENTS OF THE METHODOLOGY TRIP TABLES

Trip Distribution

As the Southwest Side has few undeveloped areas, it is expected that a new transit line would · not significantly alter population pat­ terns, regardless of the magnitude of travel improvement. Undoubtedly, there would be some land use changes at major stations, but there would be no reshaping of patterns of population density. Therefore, a fixed number of trips per zone could be utilized. This allows the use of a mode choice model, which is simpler to use than either the simul­ taneous distribution-mode choice model used in SO NARRTA or the sequen­ tial models typically used in other major planning studies. The best available data for developing a trip distribution matrix was the 1970 Urban Transportation Planning Package (journey-to-work data) of the U.S. Census, which used a fifteen percent sample of journeys to work. From this data, each zone's share of study area trips to the. central area was computed. To estimate quarter-section shares, section-level· zone totals were allocated in proportion to the populations of the four quarter sections. The UTPP data was also examined to determine whether different parts of the study area have different downtown trip-end distributions. It was found that no discernable pattern exists; therefore, each Southwest zone was given the same central area distribution as the overall UTPP pattern for all Southwest zones. The largest number of trips was allocated to the quarter-section zone bounded by the Chicago River, Lake Michigan, and Madison and State Streets.

Total Number of Trips

To the resultant 12 X 367 distribution was applied the total number of trips from the study area to the central area. The total for 1975 was estimated in the following manner: All Trips = (1970 Census work trips)(wk tp factor)( 1974 cordon count) · · 1970 cordon count Thus, the 1970 Census work trips were factored up to include all types of trips and were updated to 1975. The work trip factor of 1./.6417886 was supplied by the Chicago Area Transportation Study, based on the 1970 Home Interview Study results for the Southwest study area. The 1975 cordon count was unsuitable because of cordon line changes and the short-term impact of the recession; therefore, 1974 data was used to represent 1975. 3-2

The total number of study area trips to the central area was estimated at 194,236. After allocation to the 12 X 367 matrix, the total was 193,475, due to rounding. To produce a 1990 triptable, it was necessary to adjust the total number of trips from the study area to reflect changes expected to occur over the 1975-1990 period. In SONARRTA, the total number of trips between the six county region and the CBD was projected to increase during that period. Furthermore, because SONARRTA uses a simultaneous distribution-mode choice model, its trip distribution is not fixed; therefore, if accessibility to the CBD is improved by a new transit line in one corridor of the region (e.g., Southwest), that area's share of the region's CBD trips would increaset and its absolute number of trips would increase as well. This occurs in spite of the fact that SONARRTA holds constant the total number of CBD trips for any given year. In consideration of these growth factors, the 1990 SONARRTA net- . work was run with an assumed Franklin Street-Archer Avenue subway line. This new alternative was chosen because of its relatively central loca­ tion in the study area. The predicted total number of trips to the study area (by all modes combined) was then divided by the corresponding number for a 1975 run of the existing system. The resultant growth factor of 1.02889 was applied to the 194,236 trip level of 1975 to pro­ duce a 1990 total of 199,847. After all roundings were completed for the 12 X 367 matrix, the total became 199,063.

MODE CHOICE MODEL

The mode choice analysis was performed using the multinomial mode c~oice model developed and calibrated as part of the SONARRTA study. The model, as shown below, splits total CBD~destined trips from the Southwest Corridor into three modes: auto, commuter rail, and CTA (including both bus and rail}, based on the relative cost and travel time of each. The form of the model is as follows:

exp(-1.11237..lntijk - 0.60201.kz Cijk + 0.264X 1 - 0.203X 2 - 0.061X3) P(k) - ~------­ - ~exp(-1.11237.ktijk - 0.60201.h C,ijk + 0.264X1 - 0.203X 2 - 0.061X 3) f(:/

where: P( k) = probability of choosing mode k tijk = travel time between i and j by mode k (minutes) Cijk = travel cost between i and j by mode k (cents) dummy variable for auto (if k=l, then x =1, otherwise 0) x1 = 1 1Inwon Lee and Howard Permut, "CBD Demand Estimation Models," SONARRTA Working Paper #3, September 1976, p. 55. 3-4

e llt" P (x) = --==--e___ _ 2J -'!.. 8 At" all x where: P(x) =probability of choosing path x e = base of napierian logarithms (2.718) = time difference between path x and the minimum path, expressed as minimum minus x . e = diversion parameter The value of 0 used in the model controls the amount of diversion between alternative paths; a lesser value of theta results in a higher probability of using a path other than the minimum. As described in Chapter 4, numerous values of theta were tested on a base network in searching for the most correct value for the South­ west Corridor. Once the probability of using each of the transit paths has been computed, the probabilities are multiplied by total transit trips, as calculated in the mode choice model, to yield the number of trips assigned to each path.

USER BENEFIT

In order to evaluate the performance of alternatives being tested in terms of time savings provided to users, the network model calculates a measure known as 11 user benefit. 11 This is measured as total time savings accrued by trip makers from the Southwest Side as a result of the alternative(s) being tested. Such a figure is computed for both transit and commuter railroad modes. User benefit is computed for each of the two modes on a zone­ by-zone basis and then summed, by mode, for the entire system. In calculating user benefit .for a particular zone, the network model compares the minimum path travel time for that mode in the test net­ work with the minimum path travel time for the same mode in the base network. This difference can be called ~t. Then the model looks at the number of riders on that mode in the test network and again compares it to the base network. This difference in ridership is due to diver­ sion to or from other modes. Riders on a specific mode in the test network who were on the same mode in the base network receive the full benefit of the time savings, or ~t. Riders diverted from another mode to the mode for which user benefit is being computed receive only half the benefit 3-5 of the time savings. The reason for this is as follows: When a user changes from mode m to mode k due to time savings, there is some threshold of time savings at which he will make the change. This threshold will vary for each diverted rider between zero and tkB-tkT , where tkB is the time on mode k for the base network and txT is the time on that mode in the test network. We can, therefore, assume the average threshold to be the midpoint of this range, and the corresponding travel time at which the change is made is then (tkB + txr)/2. The diverted riders to mode k are given the benefit· of time savings from the average change-of-mode threshold to the new travel time, or (tkB + tkr)/2 - tkT , which equals~ (tkB - tkT). Therefore, the formula for computing user benefit for mode k is as follows: (UB)k = 2: (RkB + ~(RkT - RkB)) (tkB - tkT) ~all zone-to-zone pairs

where UB k = user benefit of mode k RxB "' ridership on mode k in base network RxT = ridership on mode k in test network txB = travel time by mode k in base network txT = travel time by mode k in test network 3-3

x = dummy variable for commuter rail (if k=2, then x =1, 2 otherwise 0) 2 x = dummy variable for CTA transit (if k=3, then x =1, 3 otherwise 0) 3 Travel times for corrmuter rail and CTA modes are calculated before­ hand in the minimum path algorithm. Three CTA paths and travel times were stored; however, for the mode split computations, the minimum of the three times is used .. All three CTA paths are used later in the program for the assignment process, as described below. Auto times for the model are computed as described in Chapter Two; the computations for the user costs of each mode are also summarized in the preceding chapter. Once the mode choice probabilities for each zone have been computed for each Southwest zone-to-CBD zone pair, these probabilities are multi­ plied by the corresponding elements in the trip table, described pre­ viously, to yield a 367 X 12 X 3 trip table broken down by mode.

MULTIPATH TRANSIT ASSIGNMENT

In order to more realistically assign transit trips to the network, a multipath assignment process was used to divide CTA trips among several logical paths. The mode choice model divided trips from each zone to the CBD among three modes--auto, commuter rail, and transit-­ based on the cost and minimum path travel time on each mode. The function of the multipath assignment is to look at the transit trips in more detail and split them among several alternative paths rather than assign them all to the minimum path. The multipath assignment method was originally developed for use on a highway network, where many links and modes are involved. For each link on the network, a likelihood of use is computed based on travel time relative to the minimum path. This procedure was greatly simplified for the Southwest Corridor network in that each path was assumed to consist of only one link. For each zonal pair, three paths were considered: minimum path Archer Avenue bus, minimum path rail, and second minimum path rail. The times for each of these paths were stored during the minimum path algorithm, with the minimum being used for the mode choice analysis. Under the assumptions described above, the link likelihood, or in this case, path likelihood, reduces to the following formula: CHAPTER FOUR: ANALYSIS OF RESULTS NETWORK SENSITIVITY AND THE THETA VALUE

The selection of a value of the theta parameter became an integral part of the network validation process because assignment and validation had overlapping objectives. Four such objectives are identified below, with the first one as the primary basis for the initial selection of a theta value. A number of tests were used for the various objectives; all used the 1975 trip tables and network.

Objective #1: Line Volume Accuracy

The first step was to determine what theta value would yield predicted line volumes that closely approximate those actually observed in 1975. Due to its location in the primary impact area, the most important line for this test is the Archer Avenue Bus Line (AABL), whose purpose in the network is to represent 1975 service on routes #99, #62, and #62EXP. In 1975, the CTA's peak two-hour counts for these routes totaled 7,320 at the maximum load points (eastbound, A.M.). Based on other CTA counts on these routes, a peaking factor of 51% (relatively high for the CTA system) was determined. This produced an estimated 24-hour CBD-bound ridership of 14,176. Exhibit 4-1 indicates the results of the base system network runs with varying values of theta; each result is compared to the 14,176 figure. Of the theta values used, 0.10 produced the smallest deviation from 14,176--less than two percent--and was selected for further use. However, the values of 0.08 and 0.20 also produced predicted volumes within five percent of 14,176 and well within an acceptable range. The Congress and Douglas rapid transit lines also have commuter­ sheds that lie entirely within the study area; consequently, it was expected that a similar validation test for these lines could be made. The original source of observed ridership data was the 1975 twelve­ hour cordon count at Clinton Street, where 30,692 persons were counted. Based on other CTA rapid transit data, the ridership was divided by .835 to convert the count to a 24-hour figure of 36,757. 1 However, a further modification was necessary. These lines are heavily used for trips that are oriented to major West Side institutions such as UICC, the various medical centers and hospitals, and the Criminal Court complex. Many of these trips are initially generated in other parts of the city and pass through the CBD to the West Side. In the cordon count data, the return trips are indistinguishable from the trips generated on the West Side and destined to the CBD. As a means of accounting for these through trips, it was assumed that they are approximately equal to the ridership at the U of I station. Based

1Derived from CTA document OP-x74263, dated 5-29-74. 4-2 on observed 1975 station entering volumes, it was found that this station produces 16.6% of the total station volumes for Congress + Douglas. This proportion was then excluded from the 36,757 figure, with a resulting estimate of 30,667. As shown in Exhibit 4-1, a theta value of 0.10 would produce a network prediction for Congress + Douglas of 28,646, which is 6.6% less than the 30,667 figure. This degree of "error" is very reasonable, given the difficulty of predicting Congress + Douglas ridership. While significantly higher theta values would reduce the differential, the validation of the line volume and theta value for AABL is far more important; consequently, 0.10 was retained in preference to the higher theta values.

Objective #2: Replication of Bus-Rail Competition

Currently, virtually all CBD-bound CTA riders in the primary area use buses for this travel. If a rapid transit line were built in this corridor, one would expect that most of the current bus riders would switch to the faster mode. Nevertheless, for purposes of com­ paring alternatives and computing system costs, it is important to determine whether the network, mode choice model, and multipath assignment can accurately predict the respective bus and rail volumes. The first step was to produce the existing splits for other corridors in Chicago. As shown in Exhibit 4-2, the bus' share in the Northwest, West and South Side corridors is 3%, 16% ~nd 12%~ respettive­ ly.2 The low share on the Northwest Side occurs because the two modes (#56 bus &Milwaukee Avenue rapid transit) operate over v~rtually the sam~ alignment,3 whereas t~e West Side and South .Side buses can attract riders wijo do not wish to journey to a rapid transit line, For the Southwest Side, a new alternative was run on the 1975 network with various values of 8. The most spatially direct com­ petitor of AABL, i.e., the South Side El-Archer Avenue to Archer Road Line (code SA-AA) was used for this. As on the Northwest Side, one would expect a low bus share. However, the riders' long-term travel habits are an important differ­ ence between these two corridors. Whereas there has been Northwest Side rapid transit service since the beginning of the century, most Southwest Siders have been using buses for many years for their CBD trips. In addition, it is unlikely that CTA would reduce Archer Avenue bus service to the low levels of #56 Milwaukee Avenue. For these reasons, one would expect the Archer Avenue buses to maintain more than the three percent share found on the Northwest Side. Exhibit

2The South Lakefront (Jeffery Express and ICG) and North Lake­ front Corridors were not used because of their unique characteristics. 3Indeed, two other reasons for their direct competition are: 1) both terminate at Jefferson Park, and 2) both have good CBD dis­ tribution. Exhibit 4-1. LINE VOLUMES AND THE THETA VALUE

Archer Avenue Bus Line (AABL) CTA 2-hour count: 7,230 derived all-day total: 14,176

8 network prediction % of 14, 176 0.20 13,588 95.9 0.10 14,419 101.7 0.08 14,871 104.9 0.06 15,540 109.6 0.01 16,611 117 .2

Congress + Douglas CTA 12-hour cordon count: 30,692 derived all-day total (CBD-bound): 30,667

0 network prediction % of 30,667 0.20 29,155 95.1 0.10 28,646 93.4 0.08 28,509 93.0 0.06 28,343 92.4 0.01 27,689 90.3 Exhibit 4-2. BUS-RAPID TRANSIT SUB-MODE SPLIT--EXISTING LINES

Northwest Side Bus ( #56) 550 .03 Rapid Transit (Milwaukee Av.) 20,160 .97 20, 710 1.00

West Side Bus (#7, 16, 20, 60, 126, 131) 4,840 .16 Rapid Transit (Lake St., Congress, Douglas) 24,590 .84 29,430 1.00

South Side Bus (#3, 4, 24, 29, 38) 5,340 .12 Rapid Transit (Englewood, Dan Ryan, Jackson Park) 38, 310 .88 43,650 1.00

Total of Northwest, West, and South Sides Bus (12 lines) 10, 730 .11 Rapid Transit (7 lines) 83,060 .89 93,790 1.00

All ridership figures are A.M. two-hour maximum load counts, taken in Autumn 1978 by CTA. Exhibit 4-3.

BUS-RAPID TRANSIT SUB-MODE SPLIT~-SOUTHWEST SIDE

Directly Competing Archer Avenue Bus New R. T. Line* total 8 trips % trips % trips 0.20 780 2.8 26,999 97.2 27' 779 0.10 1,898 6.8 26,065 93.2 27,963 0.08 2,629 9.3 25,507 90.7 28,136 0.06 3,849 13.5 24,592 86.5 28,441 0.01 11,037 36.6 19' 126 63.4 30, 163

*South Side El-Archer Avenue to Archer Road (code SA-AA) 4-3

4-3 indicates that a theta value of less than 0.20 achieves such a split. Ate= 0.10, the',split would be 6.8 % for bus, which is rea­ sonable. Therefore, the ,theta value selected for Objective #1 satis­ fies this objective as well.

Objective #3: Significant Differences Among Alternatives

This objective was addressed in terms of the question: To what· extent does the location of a rapid transit line in different sub­ corridors affect the usage of the new line and the remaining bus service? This test was necessary to determine whether the network, model, and 8 together can produce meaningful differences among alternatives. Selected for testing were three lines: 1) a centrally located South Side El-Archer Avenue option (code SA-AA); 2) one of the nor­ thernmost alternatives--South Side El-ICG-Stevenson (SG-VV); and 3) the southerly Dearborn Street-Loomis Street-IHB East and West (DR-II). Alternative theta values were set at 0.10 and 0.20. An examination of the data in Exhibit 4-4 indicates that compared to 8 = 0.20, the 0.10 value produces somewhat greater ridership dif­ ferences among the alternatives. Perhaps more importantly, the results indicate that the demand methodology can produce meaningful differences in overall ridership levels. This is in spite of the similarities, for all three lines are in the same general corridor, all extend to Archer Road, and all are of similar length. For 0 = 0.10, ridership of the high volume alternative (DR-II) was more than 25% greater than that of the low one (SG-VV). With this test, confidence was gained that the 1990 network runs would produce similar meaningful differences.

Objective #4~-Realistic Prediction for Non-minimum Paths

The final test uses a more 11 micro 11 view, i.e., that of the indi­ vidual travel zone. The question raised is: For various theta values, to what extent do riders use the second and third quickest paths? The sample zones used to measure this were selected on the basis of 1) assignment to two rapid transit stations, preferably to two lines in the process; 2) a significant level of total trips by transit (generally 100 to 700); and 3) location in or near the primary impact area. Ten such zones are utilized in Exhibit 4-5; six are assigned to two rapid transit lines, and eight are assigned to AABL as well. Theta was set at 0.20, 0.10, and 0.08. Most of the computed time differences between the two rapid transit paths were small, usually one or two minutes. With 9 = 0.20 ------· ------··------·-· •··-····--·--- -

Exhibit 4-4. TEST OF SIGNIFICANT DIFFERENCES AMONG ALTERNATIVES

Archer Av. Bus Rapid Trans it total trips % trips % trips 8 = 0.20 SG-VV: South Side El- !CG-Stevenson 1,022 4.4 22,324 95.6 23, 34 6 SA-AA: South Side El- Archer Av. 780 2.8 26,999 97.2 27' 779 DR-II: Dearborn St.- Loomis St. -IHB E & W 1,379 4.7 28,078* 95.3 29,457*

8 = 0.10 SG-VV: South Side El- I CG-Stevenson 2,482 10. 5 21,157 89.5 23,639 SA-AA: South Side El- Archer Av. 1,898 6.8 26,065 93.2 27' 963 DR-II: Dearborn St. - Loomis St.-IHB E & W 2,569 8.7 26,978* 91.3 . 29,547*

All alternatives were tested with the 1975 network.

*Excludes boardings of Southwest trains at existing West Side stations. Exhibit 4-5. SENSITIVITY ANALYSIS FOR NON-MINIMUM PATHS

Trie Assignment (in eercentages) g = 0.20 g = 0.10 Overall Travel Times Total g = 0.08 zone # R. T. l R.T.2 Bus Tri-ps R. T. l R. T.2 Bus R.T.l R.T.2 Bus R. T .1 R.T.2 Bus 27 42 44 314 60 40 55 45 54 46 37 33 34 51 153 52 47 1 47 45 8 45 44 11 62 44 44 63 119 51 48 1 48 45 7 46 45 9 64 44 45 66 152 52 47 1 49 46 5 47 45 8 66 45 46 69 165 55 44 1 49 46 5 49 44 7 68 46 48 72 143 61 39 54 42 4 51 43 6 70 43 44 75 155 56 44 52 46 2 50 46 4 98 36 41 726 74 26 63 37 60 40

99 41 42 79 467 61 39 55 44 1 53 44 3 209 68 72 95 78 69 31 58 38 4 55 39 6

R.T.l =minimum path by rapid transit R.T.2 = rapid transit path of second shortest travel time; may be the same as R.T.l, but not the same station 4-4

and a time difference of one minute, the share for the minimum path varies from five to twelve percentage points greater than that of path #2. As the time difference increases to five minutes (as in the case of zone 209), the split becomes approximately 70%-30%. However, if 8 = 0.10 or less, the differences are considerably smaller. The results do show a diversion of trips to non-minimum paths in all cases, but they do not pinpoint the optimal theta value for this purpose. Throughout Exhibit 4-5, both rapid transit paths are significantly faster than that of the Archer Avenue bus. The assignment results indicate that ate = 0.20, the network predicts virtually no bus usage. However, at 8 = 0.10, AABL was predicted to carry up to eight percent of the transit riders; at 8 = 0.08, up to eleven percent are so assigned. Most of these zones are located in Bridgeport, McKinley Park, Gage Park, Auburn-Gresham, and South Lawndal4. In most cases, one would expect significant bus ridership levels, although rapid transit lines offer faster service. Therefore, a theta value of 0.20 is clearly too high here, while 0.10 and 0.08 are probably acceptable in this case.

Conclusion

The four objectives served as the means for 1) establishing the theta value to be used forall testing of 1990 networks, and 2) vali­ dating the entire network methodology. To satisfy objective #1, the theta value was set at 0.10. Other values were tested in relationship to the other three objectives; however, 0.10 was either the preferred value, or at least an acceptable one, in all cases. Consequently, it was selected. The remaining task was to examine the line volume predictions for the other rapid transit and commuter railroad lines in the 1975 base network. These validation tests are discussed in the remainder of the chapter.

ANALYSIS OF LINE VOLUMES IN THE BASE NETWORK

After the selection of a theta value and the attainment of the four objectives, the last step was to check the overall line volumes for the 1975 base network.

4Indeed, bus usage in Bridgeport is undoubtedly greater than the estimated share, due to the Wallace St.-Racine Av. route that was not included in the base network. Such inclusion was largely unnecessary for analysis in the primary impact area. 4-5

~~_Qj__9__J_j'ansit and Bus

The volumes for the Archer Avenue Bus Line and the Congress and Douglas Lines were checked as part of the initial selection of a theta value. However, Exhibit 4-6 also indicates the 1975 base network predictions for three other rapid transit lines . For the Lake Street Elevated, the network estimates only 3,691 daily CBD-bound riders; this is approximately sixteen percent of the estimate derived from CTA counts as shown in Exhibit 4-6. Since this line lies several blocks north of the edge of the study area, most of its commuters hed is not included in the trip tables. Although the study area ' s share of Lake Street's ridership may approx imate the six­ teen percent level, this cannot be verified from available data. The network's estimate for the Dan Ryan Rapid Transit Line is 37,903 dai ly CBD-bound riders, which is approximately 72 % of the estimate derived from CTA counts. Because the east (i .e., east of State St.) and far south (below lllthSt.) service areas are excluded, the network prediction may actually be somewhat high. One reason for this is that the network data includes the Roosevelt Road subway station; this station will be served by the proposed Howard-Dan Ryan through service, but its riders currently use Englewood-Jackson Park trains. More significantly, the network prediction includes some persons who are currently using other modes -- buses in Bridgeptirt and commuter railroad trains in Beverly, for example. Overall, how­ ever, the estimate is reasonable.

The prediction for South Side El-Englewood is 13,603 ~ which is 47.8% of the estimate based on the maximum load counts. If the Roosevelt Road ridership were added to the network prediction,' this percentage would increase somewhat. With this adjustment, the stations included in the network--South Side Main Line to 58th Street, plus the Englewood Branch--accounted for 74 % of the entering volume s on the South Side elevated system in 1975.5 However , based on the fact that a majority of the Main Line commutershed is outside the study area, it was estimated that the base network stations and study area commutershed should capture approximately 40% of the South Side elevated system ridership. When compared to this number, the 47.8% share is a reasonable estimate.

Commuter Railroad

The commuter railroad ridership figures used for validation pur­ posed are primarily based on the railroads' counts or estimates taken during the 1974-77 period. On the Chicago & North Western, the Rail­ way's 1975 estimate of ridership for the study area stations was l ,020.

5"Rail System Nov. 1975 Traffic," CTA Report Op-x76332. r···---·· ----·· i Exhibit 4-6 LINE VOLUME TESTS FOR RAPID TRANSIT AND BUS 1975 base system, with e = 0.10 ( l) (2) ( 3) (4) CTA 2-hour adjusted figure network col. 3 as O' max. l oada (24-hour) ~rediction 7o of col. 2 comments Archer Av. bus 7,230 14,176 14,419 101. 7 most important line for validation

Congress + Douglas n.a. 30,667 28,646 93.4 Lake Street 9,360 23,400 3,691 15.8 line is outside the study area Dan Ryan 21,210b 53,025 37,903c 71.5 study area excludes the eas and far south service area South Side El - ll,390c 28,475 13 '603b 47.8 study area excludes the Englewood Jackson Park branch and much of the service area

aSpring 1975 data, per CTA ilOperating Facts," OP-y76002. bExcluding Roosevelt Road subway station cincluding Roosevelt Road subway station n.a. = not applicable Exhibit 4-7 LINE VOLUME TESTS FOR COMMUTER RAILROAD 1975 base system, wi~h 8 = 0.10

( 1) (2) ( 3) independent net~vork col. 2 as 0/ calculation ~diction IC' of col. 1 comments

C&NW West 1,020 .. 1, 393 136.6

BN 8,585 6,068 70.7 some BN riders were assigned to GM&O

II :I ,, GM&O 726 1, 601 220.5 Ii II II N&W 3,840 3,452 89.9

RI 5' 776 2,274 39.4 model cannot account for strong or~ en­ ta ti on of Bevery area to RI line

Independent Calculations C&NW: Railway's estimate of i975 boardings, multiplied by 1.062 to account for cash fares. BN: Railroad's March 1976 a.m. rush-hour counts, multiplied by 1 .15 for all-day ridership GM&O: 1974 figures for a single train were multiplied by six to approximate full rush-hour service. N&W: 1973 and 1977 counts were averaged, then multiplied by six to approximate full rush-hour service. RI: Railroad's estimate of 1975 boardings, based on ticket sales. · 4-7 per·iphery, only the BN··GM&O disparities are significant in the 1975 base network analysis. However, they are rendered irrelevant when the 1990 test networks are used with the assumption of full service on the GM&O. Therefore, the 1990 network produces satisfactory results for commuter rail. 4-6

The prediction yielded by the base network is 1,393, which is 36.6% greater than the Railway's estimate. Since this line is outside the study area, this differential--less than 400 riders--has virtually no impact on the predicted demand for the new alternatives. For the Burlington Northern, the March 1976 rush-hour station counts were factored up to approximate all-day boardings; the resul­ tant total for Cicero to Western Springs, inclusive, is 8,585. The network prediction is 6,086, for an underprediction of 29.1%. The 1974 counts at four stations for the single inbound ICG-GM&O train were multiplied by six trainloads to approximate full rush-hour service, with a resulting estimate of 726. The network prediction is 1,601, or an assumed overprediction of 121%. The GM&O ridership is difficult to predict because of the low level of service in the 1970's and the potential for commutershed shifts. The network uses many of the same commuter rail station assignments for the 1975 and 1990 base networks and all test networks. Some areas, including Lyons, McCook, Countryside, and Indian Head Park were assigned to the GM&O because they would logically belong to the line if full service were provided. However, these assignments largely created the BN underprediction and GM&O overprediction on the 1975 base network. Norfolk & Western station ridership data is not available for the 1974-76 period. Train counts indicate that ridership on the line grew 56% between 1973 and 1977. To estimate 1975 ridership, half of this growth (i.e., 28%) was added to available 1973 station counts. To estimate demand for full rush-hour service, the figures were then multiplied by six, yielding a figure of 3,840. The network prediction is 3,452; at 89.9% of the estimate based on counts, the prediction is more than satisfactory. The "independent cakulation" for the Rock Island lines is the Railroad's 1975 estimate, based on ticket sales, and includes Main Line and Beverly Branch stations south to lllth Street. However, only one­ hal f of the lllth Street-Morgan Park ridership is counted, because much of its commutershed is outside the study area. Therefore, the resultant total Rock Island ridership is 5,776. The 1975 base network produced an estimated 2,274 riders, which is approximately 40% of the modified ticket-sale estimate. The principal reason for the disparity appears to be that the mode choice model cannot account for the unusually strong orientation (compared to most other parts of Chicago) of the Beverly and Morgan Park communities to commuter rail service. Predicting commuter railroad demand in an area with rapid transit is difficult; certainly, the accuracy of prediction is less than that for the rapid transit lines. However, it was found that in the testings of new alternative lines, very few riders were diverted from the com- 11111ter railroad lines--in virtually all cases, no more than 1,000, or six percent. Because the C&NW and Rock Island lines are on the ACKNOWLEDGEMENTS

The authors wish to thank the following persons, whose contributions either to the Southwest Corridor Study or SONARRTA made this report possible.

Prof. Alex Anas and Steven Arenson, Northwestern University-­ minimum path algorithm for SONARRTA. Dr. Inwon Lee--mode choice model, SONARRTA computer program. RTA, 1976-1978. Prof. Siim S66t and Margaret Esser, University of Illinois at Chicago Circle--station and zone coordinates, station commuter­ sheds. Lawrence Bubel, RTA--development of travel time formulas for transit modes, CBD egress times. Howard Permut--project supervision and timely advice. Steve Wojtkiewicz, RTA--data processing consulting. Bruce Mainzer, IDOT--consultation on the applications of SONARRTA and the user benefit concept to the Southwest Corridor Study. RTA, 1977-1979.