CHAPTER 2 LITERATURE REVIEWS

Section describes the theory and research related to the research done earlier. There are Seventeen topics in this chapter such as, the real-time traffic, information models worldwide, traffic setting in Bangkok, real Time Traffic information in Bangkok, traffic condition reporting systems currently used in Bangkok , websites and applications reporting traffic information1, traffic information service fees, utility theory for explaining consumer behaviors, passenger traveling behavior model, travel decisions of travelers, route selection behaviors and variables, value of travel time, factors influencing travel behaviors, stated preference technique, binary logit model for analyzing travel options, cluster analysis, multiple regressions analysis, and literature reviews.

Real-Time Traffic Information Models Worldwide Concepts for utilizing information and communications technology to help solve traffic problems have originated in various countries around the world such as the following: 1. The United Kingdom

Figure 1 Real-time traffic information services in the United Kingdom. (The highway Agent National Traffic Information Service, 2009)

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Figure 1 is the real time traffic information in the United Kingdom; traffic information is presented by a system called “Traffic England” operated by the Highway Agency National Traffic Information Services. Traffic England is a system that reports traffic conditions for presentation to travelers. Information is presented and constantly updated. The system will report events occurring in real time on roads where users are traveling and predict traffic conditions. Travelers can know immediately whether the route travelers are using will have delays, how long and identify causes of delays. Furthermore, the system will recommend new alternative routes for route changing decisions of users instead of having to hopelessly remain in their vehicles, meaning travelers will have information to make travel decisions at different times and routes. This system is used by approximately 960,000 people per month and provides services through the website in Figure 1. 2. America and Europe

Figure 2 Real-time traffic information services in America (NAVTEQ Traffic.com, 2010)

NAVTEQ is a highly popular leading digital map service provider in America and Europe. NAVTEQ is a service provided by private organizations and the system with the most geographical databases in the world, thereby enabling provision of more data with greater accuracy than traffic information received from government agencies. NAVTEQ provides traffic information services in areas covering digital maps in seventy-eight countries worldwide. In the United States, NAVTEQ provides 9 traffic information covering fifty-one cities nationwide while also being the agency that presents the most information for car navigator systems in the world with a market share of 85%. Car navigator systems currently using information from NAVTEQ comprises Garmin Lowrance and NDrive. Furthermore, NAVTEQ also provides traffic information services via various web bases such as Yahoo! Maps and NAVTEQ is one of the applications in Nokia phones. NAVTEQ presents traffic information of regularly traveled routes together with recording travel information on that route. Reports on current traffic conditions, reminding systems when delays occur and advanced travel planning systems are shown in the NAVTEQ webpage traffic information sample in Figure 2. 3. Malaysia

Figure 3 Real-time traffic information services in Malaysia. (The Transport Management Centre, 2010)

The real-time traffic information system in Malaysia is used by the name of the Integrated Transport Information System or ITIS. This system was established with the goal of modifying transport system structures according to the City Hall Kuala Lumpur plan (CHKL), which emphasizes the development of transport system structures. The IT IS system collects and reports accurate and current traffic information to road users, drivers and passengers. This traffic information can help with decisions to use or avoid various routes in order to be able to reach destinations more easily, quickly and safely. This system is under the management of the 10

Transport Management Centre (TCM) and provides services in only the Klang Valley by reporting traffic information through websites. Traffic information system services provided by ITIS consist of journey planners, road congestion maps, real time traffic video streaming, latest traffic images and traffic announcements. Examples of websites which provide ITIS traffic information services are shown in Figure 3. 4. Hong Kong

Figure 4 Real-time traffic information services in Hong Kong. (Department of Transportation of Hongkong, 2010)

The real-time traffic information system in Hong Kong is operated by the government‟s transportation department which provides services by the internet on the Transportation Department website and links to traffic information systems worldwide. Traffic data is collected from CCTV cameras placed at various points throughout Hong Kong. Data is then sent to the data center and traffic information will be reported to travelers. The traffic information in this system consists of traffic conditions on major roads, journey time indication, traffic control and surveillance, traffic speed map, electronic parking meters and data provided for passengers who use Hong Kong‟s public transportation systems such as railways, buses, minibuses, taxis, ferries and trams. Dissemination of operating information was by the government of Hong Kong via websites as shown in Figure 4.

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5. Singapore

Figure 5 Real-time traffic information services in Singapore. (Intelligent Transportation & Vehicle Systems, 2010)

The real-time traffic information system in Singapore is called the Intelligent Transport Systems (Centre). ITS is a system for reporting traffic information twenty- four hours per day through signs installed on expressways and various locations. Information will be collected from various sources, such as cameras installed at various intersections, toll booths, taxis and drivers. Traffic situations will be reported to the ITS Center, making information displayed on signs current at all times. Information services are called “on the roads” telling traffic speed on expressways through colored line displays consisting of red, green and orange. The system also issues warnings, such as accidents, breakdowns, heavy traffic road work, traffic signal down, parking lot availability and various map searches as shown in Figure 5.

Traffic Setting in Bangkok Bangkok is Thailand‟s capital and suffers the heaviest traffic. This city is Thailand‟s most populous city and also serves as a center for government, education, commerce, communications and transportation while sharing borders with surrounding provinces. At the present, Bangkok has mainland communications and the beginning of Thailand‟s major roads, such as the Phahon Yothin road (Highway No. 1 – North Route), Thailand‟s main route for traveling north ending at Mae Sai, 12

Chiangrai, the Mittaphap road (Highway No. 2 – Northeastern Route), the main route for traveling to the northeastern region of Thailand ending at Nong Khai, the Sukhumvit road (Highway No. 3 – Eastern Route), which is the main route for traveling to the eastern region of Thailand ending at Trad, the Phet Kasem road (Highway No. 4 – Southern Route), the main route for traveling to the southern region of Thailand ending at Sadao, Songkla. In addition to being the origin of the country‟s major roads, Bangkok also has many special intercity expressways and various forms of public transportation such as buses, minibuses, BTS, MRT, taxis, boats and ferries. The growing capital has increasing numbers of automobiles every year while the increase of roads is slow, thereby making Bangkok one of the world‟s most traffic- congested cities.

Real Time Traffic Information in Bangkok Drivers in Bangkok receive traffic reports through various channels, especially main roads in the Bangkok area and main expressways in-out of Bangkok, where VMC signs with red, yellow and greed information displaying heavily congested traffic, moderate traffic and flexible traffic on two hundred major roads together with information showing traffic conditions on expressways and main roads in Bangkok and on highways from large numbers of CCTV cameras with displays of current and retroactive image data. Nevertheless, the agencies involved have plans to improve the effectiveness of real-time traffic report systems, which will be linked to other agencies such as by linking CCTV cameras in key areas of Bangkok such as the port, raised expressways, airports and department stores to collect and exchange traffic and transportation information. Data displaying the number of parking spaces for the public transportation system and department stores with real-time linkage will be increased to display the information of remaining parking spaces in each department store as data for accompanying the public‟s consideration of travel forms together with periodic predictions of future traffic conditions, such as traffic conditions in the next fifteen or thirty minutes. Real-time traffic information is automatically summarized through the SMS system or other systems such as reports of accidents or road closures for construction or repairs with increase of analysis to select proper routes and forms of transportation in line with the needs or behaviors of 13 each person by displaying routes from the beginning to the final destination, including travel modes by the public transportation system, namely, buses, electric trains and passenger boats or automobiles. The aforementioned actions have caused state agencies, private agencies and the public to show more interest in using and many agencies want to link and exchange information for dissemination and development in line with utilization needs. This system will be developed in the future with cooperation between the state sector and the private sector in reporting traffic conditions for public benefit in checking traffic conditions, selecting routes before traveling and enabling automobile users to avoid risky roads, such as roads with drilling, roads closed for bridge repairs, roads with accidents or mobs so travelers will have confidence in being able to reach destinations on schedule without hurrying and with knowledge of safe routes together with advanced travel planning. In 2011, a real-time traffic information system was developed in the country by having traffic information centers collect and process information. This project has been a joint effort between the Intelligent Transportation System Thailand Association and the National Electronic and Computer Technology Centre (NECTEC). The project‟s concept was to provide traffic information for travelers to select the best routes of travel in the Bangkok area. Information centers will receive information from suppliers and other allied information sources such as the Department of Highways, the Expressway Authority of Thailand, highway toll booths, traffic police, the Transportation and Traffic Policy Office and CCTV cameras installed throughout Bangkok. Information was also acquired from taxi drivers, who can be considered the largest group with the closest proximity to traffic. Information from various sources will be collected at the center and analyzed for transfer to travelers. Advanced estimations show this traffic information system will be successful and popular among business units which transfer information, such as mobile phone distributors who purchase information to provide services for customers who have purchased or used mobile phones. Furthermore, this information may receive interest from automobile manufacturers who want information to provide services in navigation systems of new automobile models. According to the aforementioned data, Thailand can be seen to have exerted efforts to develop real-time traffic information systems with efficiency resembling 14

various countries around the world with the main objective of providing traffic information for travelers to use in making travel decisions together with development into commercial service systems.

Traffic Condition Reporting Systems Currently Used in Bangkok At present, the development of traffic information systems has cooperation and coordination between various agencies, including advances in communications instruments with traffic information collection from various sources enabling calculations, information processing, real-time reports and multiple channels for accessing information. Most travelers in Bangkok receive traffic condition reports from the following sources: GPS Systems in Automobiles 1. Global Positioning Systems, or GPS, is a system for telling coordinates via satellites. These satellites transmit signals to network computers to tell the coordinates on the Earth‟s surface at all times, twenty-four hours a day. This technology has been developed to be included in other types of devices, such as cell phones. GPS has main roles involved with travelers in Bangkok, especially in private automobiles. The technologies of new-generation communications devices and in- vehicle GPS have been developed together for utilization as a road navigation system by installing on private automobiles to enable easy travel to unfamiliar places by entering the place name or coordinate information into the device, which will be able to display various routes and shortcuts in preparation of travel with voice navigation systems providing a high degree of convenience. This device can record all routes traveled on and convert the information into various map file formats. Furthermore, this device facilitates traffic information and can transmit traffic analysis information from various points, such as recommending roads where traffic is not congested, which will have many benefits, especially when traveling during rush hour in the capital. Most automobiles in Thailand have car navigators and can download traffic information from popular sources of information such as iTIC (Intelligent Traffic Information Center Foundation), Tom Tom Live Traffic, TSQUARE Traffic Information Service, BMA Live Traffic and Longdo Traffic.

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Figure 6: Global Positioning Systems in vehicle (Tom Tom International BV, 2012)

2. www.trafficpolice.go.th www.trafficpolice.go.th is a website created with the cooperation of the Thai Traffic Police and the Thai Intelligent Transport System Association or ITS Thailand as an intelligent traffic information operations center for managing traffic information from various related agencies comprising the Traffic and the Transportation Department (TTD), the Expressway Authority of Thailand (EXAT), the highway police, the Thai Traffic Police (TTP) and the National Electronics and Computer Technology Center. This center has developed systems for providing more traffic information services by increasing intelligent information displays in real-time traffic maps via www.trafficpolice.go.th to the provision of information via GPS devices installed in vehicles and portable GPS devices, which will help road users access traffic information more quickly with more benefits in traveling to solve traffic problems, In the past, increased numbers of citizens were found to have shown interest in viewing the website by increasing from the mean of approximately 1,500 times per day to a mean of 4,000 times per day and higher on rainy days, which is considered as a good response. Furthermore, it is also a positive sign that the public collected information before traveling, which can reduce traffic problems to a certain degree.

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Figure 7 Thai Traffic Police Web site (Traffic Police Division, 2012)

3. www.traffy.in.th www.traffy.in.th is a website developed by the traffic condition report and assessment project of the Network Technology Laboratory, Intelligent Transport System Program, National Electronics and Computer Technology Center, National Science and Technology Development Agency, which is a government agency, for dissemination and free use by the general public with expectations that the information will have benefits for travelers while also contributing to building networks and groups of persons interested in developing and sharing traffic information for benefits in easing current traffic problems.

Figure 8: Traffic information on NECTEC website (NECTEC, 2012)

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4. http://traffic.longdo.com The Longdo Traffic website is one of the services of longdo.com which provides the service of reporting traffic information and incidents such as accidents, rain, flooding, construction, mobs, events and other incidents with information received from various sources, such as information from the government by linking from the Thai Intelligent Traffic Information Center Foundation (iTic) with key information from government information sources, such as Bangkok, via Fort/Genius company (intelligent traffic signs along main roads, the Expressway Authority of Thailand, images from NECTEC CCTV cameras, private information such as from taxi companies with taxis providing services in Bangkok for twenty-four hours per day and volunteer information. This information will relay information on the latest incidents from volunteers using Longdo Mobile, which can jointly report traffic conditions. Longdo Traffic can be downloaded via http://mobile.longdo.com and supports all Smartphone systems whether in the form of iPhone, Blackbery, Windowsphone, JAVA or Adroid. In addition to checking traffic condition reports, Longdo Traffic also enables people to report incidents by volunteering.

Figure 9: Longdo Traffic website (Longdo Traffic, 2012)

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5. Maps.google.co.th Maps.google.co.th is a website enabling viewers to see routes and check traffic conditions from Google Maps by viewing traffic conditions in real time displayed in green, yellow and red lines indicating vehicle density on that road. The information is from cooperation between Google and land transport communication agencies in Bangkok consisting of the Office of Transport and Traffic Policy and Planning (OTP), the Bangkok Mass Transit Authority (BMTA), Bangkok Mass Transit System Public Co., Ltd., BTS and Bangkok Metro Public Co., Ltd., which provides MRT services.

Figure 10: Maps.google.co.th website (Tourism Authority of Thailand, 2012)

Mobile phone traffic information applications collect traffic information in Bangkok and present information to users. Travelers can view nearby traffic news and information on maps, closed-circuit cameras and traffic conditions from intelligent signs throughout the Bangkok area. 6. TSquare Traffic TSquare Traffic was developed by Toyota Tsusho Electronics (Thailand) Co., Ltd., a leading world-class automobile software company providing traffic information services for Toyota Smart G-book, Longdo traffic (iOS), i-mobile TSquare and traffic apps of Toyota Libra. This application has been mentioned by manufacturers for its ability to help travelers save an average of 30% on gasoline when traffic jams are not encountered, save time at a mean of forty-five days per year 19 in Bangkok and help reduce problems from stress and physical health caused by sitting in automobiles for long periods of time. TSquare Traffic has real-time traffic information functions conveying information on traffic conditions in the form of colored lines (red/yellow/green) covering every major road and shortcut of Bangkok and six surrounding provinces in high resolution with more than 25,000 sets of colored lines displaying traffic information every five minutes capable of telling traffic conditions with more than 70% accuracy, thus making this system the most accurate in Thailand. Traffic information is obtained from speed information through GPS systems installed in 10,000 taxis in Bangkok and other vehicles supported by information from the traffic cameras of the state sector and the Thai Intelligent Traffic Information Center Foundation. Traffic information is processed and displayed with technology meeting Japanese standards. TSquare Traffic is an application reporting traffic conditions in Bangkok on Android, which uses offline maps that are cost- effective and enable quicker viewing of traffic information than downloading online maps. This application can be used with every mobile phone network in Thailand, including AIS, Dtac and True Move.

Figure 11: TSquare Traffic on mobile phone (Toyota Tsusho Electronics (Thailand) Co., Ltd., 2012)

7. BMA Live Traffic BMA Live Traffic is a cooperative effort between Bangkok Metropolitan and the Thai Intelligent Traffic Information Center Foundation (ITIC) in collecting 20 traffic information from CCTVs in the Bangkok area for use with the “BMA Live Traffic” application to help road users check traffic conditions before traveling via smart phones and tablets by using information from 150 CCTV cameras of Bangkok on main roads and 50 CCTV cameras of the Thai Intelligent Traffic Information Center Foundation (ITIC). True Internet Co., Ltd. also supports high-speed internet networks to link information from the traffic system control centers of the Traffic and Transportation Department, enabling real-time traffic reports, while also providing server support at True Internet Information Center. At the same time, BMA Live Traffic is also uploaded to the Traffic and Transportation Department website to provide convenience for the public in knowing traffic conditions with coverage of areas with traffic congestion which must be avoided, locations where traffic is flexible, accident areas, etc., so the public can make plans before traveling and ease traffic problems. The “BMA Live Traffic” application will report traffic conditions via smart phones and tablets. Traffic reports in the beginning will be consecutive stationary images from CCTV cameras, which will be improved to real-time motion images. Traffic results are displayed in red lines for routes moving at speeds of less than fifteen kilometers/hour, yellow lines for routes moving at the speed of approximately fifteen to twenty-five kilometers/hour and green lines for routes moving at the speed of more than twenty-five kilometers/hour. This application displays results on smart phone and tablet screens as seen in the image. In addition, various channels are available with capability to receive traffic reports on information in the Bangkok area such as Twitter‟s Time Line, which can report traffic jams, accidents, mobs, hazards and allow users to report traffic conditions via Twitter such as Jor. Sor. 100 at http://twitter.com/JS100radio and http://twitter.com/Longdotraffic.

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Figure 12: BMA Live Traffic on mobile phone (Bangkok Metropolitan, 2012)

The researcher summarized forms of traffic information from collected data according to characteristics of information services provided as shown in Table 1.

Table 1 Summarization of the traffic information was collected

Information Information presented on

Basic information - Distance from the origin to the destination. - Time duration of the trip - Traffic condition - Road conditions - Weather Data application - The Searching the nearest path - An alternative route - The system recording the travel - Notification when delays Intelligent information - Travel forecasting system. - Trip planning system a specific individual. - Notifications in advance of travel.

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Traffic Information Service Fees Real-time traffic information service fees depend on the types of information and channels in receiving information. In the past, service fee calculations have generally used pricing criteria by considering economic principle guidelines or the “Customer Surplus” principle. This principle emphasizes customers‟ satisfaction in payment. Commercial traffic information services are new and usually included with communications devices or various types of data receiving instruments, such as necessity in installing car navigators to receive information, purchases of expensive smart phones and download information from various sources. Service development to respond to customer needs by real-time traffic information providers include free and paid downloads with service fees depending on types and reliability of information summarized in the table2.

Table 2 The channels for receiving information and service charge

Channels Price Remarks GPS Systems in Data update prices of 400- Customers must pay for the Automobiles 1,200 baht per year. device and car navigator installation at 2,000-10,000 baht. www.trafficpolice.go.th Free www.traffy.in.th Free Customers must have http://traffic.longdo.com Free communications devices Maps.google.co.th Free capable of supporting Free trial for two weeks information such as with the service fee of ten notebooks, smart baht per week or thirty phones, tablets or new baht per month and two car navigator models hundred and forty baht per capable of downloading TSquare Traffic year afterward. information. BMA Live Traffic Free Time Line on Twitter Free 23

Utility Theory for Explaining Consumer Behaviors In consuming products and services, consumers need to make decisions to select products and services from various types. In the 19th century, the Utility Theory was used to explain methods by which consumers decide to purchase products and services. Consumers will consider products or services providing maximum utility. Utility is the satisfaction consumers receive from products or services which can be assessed. If consumers receive high satisfaction from products or services, consumers will decide to purchase the products or services such as by choosing to travel on electric sky trains rather than buses, choosing to purchase automobiles rather than houses, which depend on utility from the products or services compared to other products. However, the utility concept has problems in that utility cannot be completely counted in units and utility cannot be compared between two persons. Nevertheless, utility will help us understand the process of choosing better goods. According to basic concepts of rational decision-making, the Utility Theory can be displayed as a basic theory according to economic theories and concepts. The basic concepts and theories of rational decision-making utility that can display the basic equations are the equations 2.1. (Wanichbancha, 2008)

Uin = Vin + in (2.1)

By Uin is the function of satisfaction for person who

prefer alternative i

Vin is the independent variables that affect satisfaction

in is the value of the variable is not observed

The people choose alternative i instead of alternative j in the All option (Cn), when alternative i make the maximum utility.

Uin V jn , j C n (2.2)

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By C n is all alternatives being considered Considering equation (2.1) and (2.2) alternative i will be selected over alternative j when

Vin V jn   jn  in ,  j  C n (2.3)

Because  jn and in are uncertain variables that do not consider. Utility can be used in analyses of behaviors or travel decisions of travelers. For example, when considering various modes of travel, travelers may choose the least time consuming mode of travel, the most convenient form of transportation or choose the route with the most flexible traffic, depending on which choice will create the most satisfaction for travelers.

Passenger Traveling Behavior Model According to economic principles, behavioral analysis models are popularly used to analyze the travel selection behaviors of passengers. The model is what humans create to explain how variables are related by testing facts with theories or hypotheses and analyzing basic data to determine whether the data is in line with beliefs from observations or theories. According to basic economic concepts, a person will make choices reasonably, meaning humans can establish their own order of preference and will usually have the most preferred option. Under economic and time limitations, this concept can be widely used to predict economic behaviors and become a base for modern economic analysis. The behavioral model is a model that reproduces decisions of service users when there are various options. Therefore, the behavioral model is an attempt to explain relationships between decisions to use services and services presented by service providers. One subject of interest is why decisions to use services change when various characteristics are different, which would enable predictions about how service users will decide upon selections of services to use when the qualities of service provision have changed. Researchers currently give importance to behavior theory in explaining human travel behaviors and have found the theory to be effective 25 and widely accepted. Therefore, the behavioral model is appropriate for use in searching for consumer reasons for making decisions because the theory can explain human travel behaviors and many researchers have been found to have implemented the theory as a guideline in studying travel behaviors (Piriyawat, 2010) , (Choocharkul et al., 2006). Passenger transportation demands will have the same general characteristics as product transportation demands. In terms of estimation, however, traveling demand will have less accurate estimations than product transportation demand estimations because factors concerned with abstract or subjective feelings, tastes and satisfaction are involved in setting travel demands. These factors are divided into the following three issues:

- Personal factors of travelers such as feelings, satisfaction, vehicle possession, convenience, transportation service frequency, accessibility and public service quality, etc. - Macro-economical factors such as economic growth, income per person, household income and population increase.

- Other factors influencing travel decisions, such as services which can compensate one another, passenger fare rates and routes.

Travel decisions of travelers are based on the following four Model These questions have led to the formation of models to predict the traveling demands of travelers. This study of demands is related to transportation planning, a process leading to decisions to use transportation policies and various programs appropriate for that area. To predict traveling demands in the study, the study will have planning processes, development of information regarding impacts, creation of transportation systems and feasible options in providing transportation services. This research guideline is popularly used and applicable in all areas with a population of more than 50,000 people while requiring databases used for consideration of the following:

- Population.

- Amount of travel. 26

- Finance: Population Income and Government Road Construction Budgets.

- Utilization of natural resources.

- Characteristics of land utilization.

- Communities and residential areas. - Economic activities. - Existing transportation systems.

- Laws and regulations of that area. Travel demand forecasting is divided into the following four models: 1. Trip Generation Model. 2. Trip Distribution Model. 3. Mode Choice Model. 4. Route Assignment Model.

1. Trip Generation Model The Trip Generation Model is a consideration of travel needs from ends, which may be considered from origins or destinations as dependent variables. When the number of trips is considered from origins, they are generally called the point of origin or production of service usage. However, when trips from destinations are considered, they are generally called attractions of service utilization. Trip production is the total number of trips leaving the origin zone in the time of consideration (per hour or day) under a travel objective without considering destination zones. Travel objectives consist of trip attractions of service utilization are the total number of trips entering a zone in the considered time under a travel objective without considering travel origin zones. Independent variables can be divided into the following three groups: 1.1The group of economic and social variables of consumers consists of population or family numbers in terms of growth, density, family size, income and consumption including the number of employed persons and automobile owners. 27

1.2 The group of transportation system characteristics variables consists of travel time, travel costs, service quality, convenience, frequency of service provision rounds and distance from the point of service to the center of the city, etc. 1.3 The group of variables concerned with the characteristics of areas and land utilization has been found to be closely related to the point of travel origins, such as land utilization concentration or intensity. This variable can be viewed in the image of the number of population per area unit, which may be in acres, square was, square meters or rais and the number of workers or employees. 2. Trip Distribution Model The Trip Destination Model is a consideration of travel needs from the number of passengers who used services along the route by considering from distribution of the amount of service utilization from Origin i to Destination j. 3. Mode Choice Model The Mode Choice Model is a model to which most economists give special interest from good applicability with various economic theories and variables. This model is a consideration of service utilization ratios in each mode of travel, such as consideration of vehicle utilization ratios to utilization of public transportation ratios. The Mode Choice Model was developed by economists and uses complex techniques, which can forecast travel demands well. In addition to the Linear Probability Model, there are also other Mode Choice Models which are popularly used such as the Probit and Logit Model. In cases with two modes of transportation for selection, the model is called Binary Logit and Binary Probit. Cases with more than two modes of transportation are called Multinimial Lognit and Nested Logit. 4. Route Assignment Model The Route Assignment Model is a model used to estimate the amount of each form of travel in each route linked between origins and destinations of each studied zone or service provision networks by selecting routes which use the shortest travel time. In selecting route assignments, advanced computer and mathematics programs are usually used in calculations more than using changes of various economic variables. Benefits from using route assignment are as follows: 4.1 Prediction of various routes which will support travel, leading to prediction of traffic intensity on road systems. 28

4.2 Prediction of the number of transportation system users requiring linkage to various transit systems with ability to plan where people will travel and how.

Route Selection Behaviors and Variables Travelers will consider travel decisions with reason by considering maximum benefit (Button, 1993). Decisions to select forms of travel will depend on the following factors: 1. Characteristics of travel consist of travel distance and objectives, whereby distance can be measured in the form of travel time. Travels nearby will not have much time difference while long-distance traveling will have effects on the rate of travel time and mode of travel selection. Concerning travel objectives, travels with beginnings at home to go to school or work were found to have higher rates of public transportation utilization than shopping trips. 2. The characteristics of travelers mean economic and social conditions of travelers. The variables involved comprise income, automobile possession, family size and structure, residence intensity, type of work and location of job sources. Income will determine mode choices. With regard to residence intensity, areas with low population intensity were found to have trends of being residential areas for people with high income, which is also related to high automobile possession levels, causing low levels of public transportation needs. To the contrary, areas with high residence intensity will have a high need for public transportation systems together with residents with low income, causing private automobile possession in this group to have low rates. 3. The characteristics of transportation systems comprise travel time, expenses, accessibility and convenience. According to studies on time used in traveling via public transportation systems and time used in traveling by automobiles, time used in traveling by public transportation was found to be higher than traveling by private automobiles if the aforementioned ratios are higher. And according to studies on the rates of travel expenses between public transportation systems and automobiles which compared factors of expenses and time, time reduction was found to have influenced the number of service users more than reduction of passenger 29 fares. Factors of convenience such as seats and air conditioning were also found to have influenced selection of modes of travel.

Value of travel time The value of travel time: VOT refers to the monetary value of the time savings from the use of trails. (Department of Highways, 2008) The value of travel time savings: VTTS mean value (equivalent to money) that lost in the journey. However, when the transportation network efficiency is improved, saving travel time and the user can use the travel time savings to other activities that create economic value to increase. The calculated value of travel time savings in the area of education need to known The Gross Province Product: GPP and the number of employed persons in the average number of hours worked. (Department of Highways, 2008) Time itself has no value, but the value is. Opportunities to engage in any activity during the time considered. The opportunity is dependent on location. Time and duration appropriate. In part of the word "Saving time" is the time spent doing certain activities. To be added to the activity otherwise undesirable, thus saving even more time in the real sense is to create opportunities for the use of time in a way that would have been even more. (Sahuntaluk, 1986) According to reports, the saving time in UK aspects of transport economics that the opportunity cost of the travel expenses for the trip. The key is to pay the costs of the trip. To obtain benefits over to save time in getting. (UK Department for Transport, 2003) In conclusion, value is the value of time or cost spent in the alternative to produce a better or more benefits, which will be more or less depending on factors relevant to the evaluation time. The main reason for the development of transportation systems is to reduce the travel time of the trip. The value of time and the interest has been in the transportation economic plan will be set up for the cost comparison. In particular, can save you time travel, which is part of the consumer surplus. Customer Surplus is the difference between the amount that people are willing to pay in exchange for saving travel time and amount to be paid at that time. 30

The value of time is different for each person depending on the purpose of each trip. According to the Ministry of Transport of the United Kingdom has identified the value of time is valued at the time at work and outside of work. Time during the value depending on the role or influence in determining the labor market and will be evaluated. By comparing behaviors to work is clearly a lost opportunity cost of the employer, which are typically paid in the form of wages for equal work for men. In practice, the time was spent on travel may have a certain pattern. Or travel to schedule the exact time as the train. The exact time schedule specified. In contrast, travel time might not be the exact model of the drive, so the time may not necessarily be based on the wage rate. Maybe not worth the time to work on a busy day or time period that is not working because there is no value in terms of labor market Evaluate it in different formats. State Preference Analysis Technique use for the fact or assumptions for the journey between the mode faster more expensive and a cheaper but slower which will be used to test or analysis to find out. It is difficult to measure the true value of time out in the choice of a trip (depending on the circumstances under general assumptions). In practice, in most cases often measure the value of your time at work and with the addition of Utility Theory.

Factors Influencing Travel Behaviors The variables used in analyzing travel behaviors comprise quantitative and qualitative variables. Quantitative variables are variables which can be measured numerically, such as travel time, numbers of routes and travelers‟ income, etc. Qualitative variables are variables which cannot be measured numerically. Most researchers will analyze by setting qualitative variables as dummy variables before analysis consisting of gender, position, educational attainment and travel objectives. The division of variables influencing analysis of travelers‟ behaviors can be summarized as follows: (Litman, 2012) 1. The characteristics of drivers are variables showing the economic and social conditions of drivers influencing travel mode choices and routes. These factors 31 comprise gender, educational attainment, income ownership per person and family income. 2. Travel time from the origin to the destination of travels. This factor influenced vehicle selection behaviors and travel routes. 3. Traffic conditions are a qualitative variable. Routes with congested traffic conditions will influence route changing behaviors or selection of vehicles enabling accelerated travel. 4. Travel route characteristics may influence route choices. For example, most drivers select routes with better roads, even though drivers have to travel farther. 5. Attitude is a qualitative variable influencing travel mode selection and vehicle selection for trips. 6. Traffic information is considered as a new variable with high influence on trips at the present because, in the current age of information which can be passed on quickly and modern technology which can collect real-time information on roads, information can be processed to forecast traffic conditions and report to travelers before or during trips which influences travel decisions and modes of travel.

Stated Preference Technique Stated Preference (SP) methods have become important for assessing individuals‟ demand for non-market goods. (Green and Srinivasan, 1978) mention that the SP techniques originate from the marketing research and experienced widespread acceptance. Wardman discusses that marketing research is quick to exploit the potential of now techniques to forecast individuals‟ choice among consumer products. (Wardman, 1987) Stated preference techniques depend on constructed markets developed from interviews or surveys. These interviews or surveys ask people about the economic values they attach to environmental goods and services. Based on the responses, analysts and planners estimate people‟s willingness to pay for a particular benefit or their willingness to accept payment for bearing a particular loss. Stated preference techniques can estimate non-use values, values that people derive from something independent of whether they ever use it. Designs of stated preference surveys follow 32 two styles: contingent valuation and choice modeling. (Pearce and Özdemiroglu (2002). Contingent valuation broadly examines the nonmarket good or service. Analysts and planners limit the choices of the interviewee to primarily one option, asking questions such as “What are you willing to pay to insure that the Grand Canyon is left in its current state for another year?” or “Are you willing to pay $5 to insure that the Grand Canyon is left in its current state for another year?” “If yes, how about $10?” “If no, how about $1?” Other questions address whether the interviewee has visited the Grand Canyon recently or intends to visit it in the near future and whether these visits or other reasons influence the respondent‟s willingness to pay. Choice modeling surveys people‟s rankings and ratings of alternative characteristics or attributes of a non-market good or service. This technique assumes that the entire worth of the good or service equals the sum of its parts and it is less reliable when the rankings of different characteristics are strongly correlated. Various forms of choice modeling are choice experiments, contingent ranking, contingent rating, and paired comparisons. Choice experiments present a baseline scenario corresponding to the status quo and several alternative options and ask a respondent to choose among them. (“Choose A, B, or neither, where the choice of „neither‟ maintains the status quo.”). Contingent ranking proceeds in the same way but asks a respondent to rank alternatives in terms of desirability. Contingent rating asks a respondent to rate each alternative on a scale, for example, from 1 to 10. Pair wise comparisons ask a respondent to indicate strength of preference for one alternative over another. Surveys consistently show that indirect factors can influence people‟s preferences about environmental issues. (Gowdy, J. and J. D. Erickson, 2005). There are endowment effects (people value things they already possess more than those they will acquire), the scope issue (people value the parts more than the whole), loss aversion (people are more averse to suffering a loss than they favor receiving an equal gain), and hyperbolic discounting (people favor short- term payoffs over long-term ones and expect a higher interest rate for short term loans than for long-term loans). These tendencies may distort evaluations of environmental goods or services. (Getzner et al, 2005) 33

Sanko (2001) mentioned reference form Kroes (1988) that Stated Preference method refer to a family of techniques which use individual respondents‟ statement about their preference in set of transport option to estimate utility function. The family of SP includes experimental economists ‟”contingent valuation” and “hedonic pricing” marketing researchers‟ “conjoint analysis” and “functional measurement” and transportation researchers‟ “stated preference” Some factors we need to consider in the SP experiment design are as follows: 1. Response from ranking/rating/choice/degree of preference. 2. Available analytical method is related to the response form; for example Regression, Logit and Probit. 3. Data collection needs huge cost. After the analytical method has been determined, we need to decide the necessary number of samples. 4. What attributes is shown to respondent and how to express the level of attributes, especially for qualitative attributes, should be considered. 5. How many attributes‟ levels should be treated and how to set attributes (absolute value, percentage and so on) should be considered. 6. SP survey may be administrated by face to face/self-completed/ PC/ internet/ mail/ phone/ mail and phone and so on. Among these factors, how to set and combine attributes and attributes‟ levels in the actual design, so called, statistical design, is one of the most important works in the SP design. Therefore in this paper we discuss the statistical design assuming choice-based disaggregate analysis from now on. Although other factors, “number of samples” and “survey administration” are important, this paper treats them only with reference to statistical design.

34

Problem Setting

Pilot survey Attributes (Measurement) Statistical design Attributes‟ level

Response from Number of Survey Administration

samples Analytical Method Survey

Analysis

Required Output

Figure 13 SP Experiment Procedures

Binary Logit Model for Analyzing Travel Options Model specifications are highly important because the model studies systems. The model will be a symbol or item showing components of the real world or real events. Mode choice models usually analyze in the form of the Logit model consisting of utility functions of each mode of travel being considered. The selection between two choices is called the Binary Logit Model. Estimations of the Binary Logistic Regression model are estimations of the probability of the incident of interest. This technique is implemented to predict whether an incident will occur or what the chances of occurrence are by setting the variables influencing the occurrence of that incident, thereby enabling us to know the cause of the incidents occurrence or non-occurrence. Regarding the estimation concepts of the Binary Logistic Regression Model, the relationship will be in the form of regression equations with dependent variables (Y) containing dichotomous variables of 0 and 1. There may be only one or multiple independent variables. Independent variables may be continuous variables or categorical variables. The model uses mathematical regression equations (Wanichbancha, 2008).

Y0   1XXX 1   2 2  ..  pp   (2.4)

35

where Y is the categorical variable

12,  ,....,  p are independent variables or categorical variable ; p  1

0 - p are coefficients of independent variables  is random Variable

Factors that make people decide on the events in the event any one or more alternative choice. We consider a rational basis for decision making by economic concepts called “Utility Theory” which indicate that people choose the alternative that them get satisfaction. On the topic of interest in studying factors causing people to make decisions and choose any event or option, we must consider the concept of regression equations and the Utility Theory. When analyzing probability in selecting any event out of two choices, we can create models showing the relationships of each event as follows:

Ui 0   1  1   2  2 ....   p  p ) (2.5)

U j 1  1   2  2 ....   p  p ) (2.6)

By Ui is alternative i

U j is alternative j are categorical variable ; p  1

0 is constant

12,  ,...,  p are coefficients of independent variables

In the event that consists of two alternatives (event and no event) we are interested in the opportunity to study the event that the logit model of the basic functions follows. e(0  1  1   2  2 ....   pp  ) (2.7) P()event  1 e(0  1  1   2  2 ....   pp  ) 36

By P()event is the probability that the event occurred

12,  ,...,  p are parameters on the estimated value

12,  ,....,  p are the independent variables e is natural Logarithm (mathematical value =2.71828)

When we know the probability of occurrence, after that, we can calculate the probability of no event that is:

(2.8) PP()()no event = 1- event

e(0  1  1   2  2 ....   pp  ) (2.9) Or P()no event 1 (      ....    ) 1 e 0 1 1 2 2 pp From equation (2.7) and (2.8), we can study the ratio between the event and no event is called “Odds Ratio”. This ratio can help explain changes in factors X 1 unit will change the Odds value which require the interpretation of the marks and the value were calculated. The Odds Ratio is calculated from

P()event Odds Ratio  (2.10) 1 P()event

Cluster Analysis The Cluster Analysis technique is divided into several types or minor techniques. However, the following two techniques are popularly used: 1) Hierarchical Cluster Analysis and 2) K-Mean Cluster Analysis. (Wanichbancha, 2008). K-Mean Cluster Analysis is a technique for categorizing cases into sub- groups and will be used when there are many cases. The desired number of groups or clusters must be set, such as by specifying k-groups. The K-Mean technique has multiple iterations. For each iteration, cases are collected in a single group by selecting the group which had a case with the least distance from the group‟s central value and the new group central value will be calculated until the group‟s central 37 value no longer changes or until the specified number of iterations have been completed. Differences between Hierarchical and K-Mean Cluster Analysis Techniques 1. The K-Mean technique is used when the number of cases or information is high. K-Mean is usually used when n > 200 because the K-Mean technique will be easier and require less calculation time than the Hierarchical technique when n is high. It can also be said that the Hierarchical technique should be used when the number of cases is not high. 2. In the K-Mean technique, users must set a definite group number in advance. In cases where analysts are uncertain how many groups are suitable, analysts may use one of the following methods: - Analyze multiple times by the K-Mean method and consider determining different group numbers and consider determining the appropriate group number. However, this method will be time-consuming when the amount of information is high. - Use some information to analyze by the hierarchical method to determine the necessary number of groups and then use the K-Mean Cluster Analysis technique. 3. In the hierarchical technique, analysts may or may not standardize information. However, in the K-Mean technique, the information must always be standardized first. 4. In the K-Mean technique, distance will be automatically determined by the Euclidean distance method whereas analysts have the right to select methods of calculating distance or similarity in the hierarchical technique.

Multiple regressions analysis Multiple regression is a statistical technique that allows us to predict someone‟s score on one variable on the basis of their scores on several other variables. One use of multiple regression is prediction or estimation of an unknown Y value corresponding to a set of X values. A second use of multiple regression is to try to understand the functional relationships between the dependent and independent variables, to try to see what might be causing the variation in the dependent variable The basic idea is that an equation is found, like this: 38

(2.11)

The Yexp is the expected value of Y for a given set of X values. b1 is the estimated slope of a regression of Y on X1, if all of the other X variables could be kept constant, and so on for b2, b3, etc; a is the intercept. Values of b1, etc. (the "partial regression coefficients") and the intercept are found that minimize the squared deviations between the expected and observed values of Y. How well the equation fits the data is expressed by R2, the "coefficient of multiple determinations." This can range from 0 (for no relationship between the X and Y variables) to 1 (for a perfect fit, no difference between the observed and expected Y values). The P-value is a function of the R2, the number of observations, and the number of X variables. When the purpose of multiple regression is prediction, the important result is an equation containing partial regression coefficients. If you had the partial regression coefficients and measured the X variables, you could plug them into the equation and predict the corresponding value of Y. The magnitude of the partial regression coefficient depends on the unit used for each variable, so it does not tell you anything about the relative importance of each variable. When the purpose of multiple regression is understanding functional relationships, the important result is an equation containing standard partial regression coefficients, like this:

(2.12)

Where b'1 is the standard partial regression coefficient of y on X1. It is the number of standard deviations that Y would change for every one standard deviation change in X1, if all the other X variables could be kept constant. The magnitude of the standard partial regression coefficients tells you something about the relative importance of different variables; X variables with bigger standard partial regression coefficients have a stronger relationship with the Y variable. Every time you add a variable to a multiple regression, the R2 increases (unless the variable is a simple linear function of one of the other variables, in which 39 case R2 will stay the same). The best-fitting model is therefore the one that includes all of the X variables. However, whether the purpose of a multiple regression is prediction or understanding functional relationships, it is often useful to decide which important or unimportant variables are. One way to choose variables, called forward selection, is to do a linear regression for each of the X variables, one at a time, then pick the X variable that had the highest R2. Next you do a multiple regression with the X variable from step 1 and each of the other X variables. The X variable that increases the R2 by the greatest amount is added, if the P-value of the increase in R2is below the desired cutoff. This procedure continues until adding another X variable does not significantly increase 2 the R . To calculate the P-value of an increase in R2 when increasing the number of X variables from d to e, where the total sample size is n, use the formula:

(2.13)

A second technique, called backward elimination, is to start with a multiple regression using all of the X variables, and then perform multiple regressions with each X variable removed in turn. The X variable whose removal causes the smallest decrease in R2 is eliminated. This process continues until removal of any X variable would cause a significant decrease in R2. Odd things can happen when using either of the above techniques. You 2 could add variables X1, X2, X3, and X4, with a significant increase in R at each step, and then find that once you've added X3 and X4, you can remove X1 with little decrease in R2. It is possible to do multiple regression with independent variables A, B, C, and D, and have forward selection choose variables A and B, and backward elimination choose variables C and D. To avoid this, many people use stepwise multiple regression. After adding each X variable, the effects of removing any of the other X variables is tested. This continues until adding new X variables do not significantly increase R2 and removing X variables does not significantly decrease it. (McDonald, 2009) 40

Literature reviews Guidelines in Solving Traffic Problems Future concepts of travel driven by the world‟s energy crisis and global warming with severe impacts on human life, the environment and natural resources compels us to revolutionize in the direction of more sustainable travel and transportation. The guidelines we view contain suitable vehicle and energy choices consistent with sustainable transportation trends, implementation of modern technology to help manage travel and transportation systems, including development of future modes of transportation emphasizing the most convenience, speed, safety, energy conservation and environmentally-friendliness. There are multiple guidelines for solving traffic problems which emphasize travel convenience and reduction of travel time, distance and expenses (Levinson, 2003). One of the current guidelines for solving traffic problems is to use economic concepts to solve problems. The aforementioned concept is an attempt to manage supply and demand in using roads and vehicles. Cervero (2000) stated that traffic problems on roads occur as a consequence of inadequate correlation between demand (the number of vehicles used on roads) and supply (the number of lanes and road distance). If we manage balance on both sides, we will be able to help reduce traffic problems. Demand management will have factors involved such as the number of routes used, the distance to be traveled, fuel prices, personal characteristics (gender, education and occupation), income level, route status or events obstructing travels. These factors all influence automobile usage. In terms of supply, the factors with influence comprise the number of travelers, specific characteristics of travelers, route conditions, government policies and events obstructing trips (such as construction). The factors influencing supply and demand will be developed into a database for use in forecasting route utilization needs and the number of supporting routes for consistency. This guideline is consistent with the concept of Goodwin (2004). Management of supply and demand in using roads will be a guideline in partially solving traffic problems. However, there are problems regarding how supply and demand amounts can be managed when there are funding and time limitations in increasing road supply while demand increases uncontrollably, as evident in the 41 findings of Phil, who found the need to use roads to have increased by 5% per year while the amount of roads increased by only 0.05% per year. Road pricing is another form of economic concept for managing traffic systems. This concept is to collect money from using roads and conveniences in traveling in the forms of parking taxes, tolls, congestion charges and collection in other forms which may not be directly related to roads, such as fuel taxes and license fees. Collection of the aforementioned taxes or fees will be flexible according to time in each day for specific routes or types of vehicles. In this study, the researcher would like to further state that congestion charges will involve the collection of fees from automobiles passing on routes specified by the government during rush hours, a concept demonstrating that automobile drivers driving through that area must be responsible for parts causing traffic congestion and environmental impacts. This concept is currently practiced in various cities such as London, Stockholm, Milan and Singapore. In another problem-solving guideline, information officers hold the opinion that modern news, information and communications systems will become a new guideline for solving the aforementioned problems (Waadt, 2009). However, from implementation of traffic information systems, information efficiency problems continue to be encountered. If information can be developed for accuracy, modernity and use in making decisions, this guideline will have the highest efficiency in solving traffic problems in the future. Traffic information is widely used with many studies to support concepts, necessity and need for real-time information together with guidelines on development into commercial information service systems according to the following researches on travelers‟ behaviors in Thailand. The route choice behaviors and values involved in willingness to pay for route recommendation systems of drivers in Bangkok using the RP and SP technique. In addition to, summarized the factors to which travelers gave importance are travel time, distance and safety. Drivers will change routes only when confronted with congested traffic on regular routes and when drivers have business on other routes. Furthermore, he studied the utilization of traffic information and found travelers to mostly check traffic information while traveling in order to help drivers reach 42 destinations without getting lost, check for information concerning the best distance and route, including accidents on routes. (Kongsutthi, 1999) According to the pilot survey, people in Bangkok have been found to have traveled (round trip) at an average of 55.93 kilometers per day with the mean travel time of 77.67 minutes and the mean travel expense of 165.33 baht per day. (Potipun et al., 2010) The aforementioned findings are similar to the findings of a survey conducted by Bangkok Thanakom Co., Ltd. (2005) for the travel behaviors of people in Bangkok, which found the population of Bangkok to have used a walking time of 90 minutes per day and the daily travel expense of 150 baht per day. Furthermore, people in Bangkok were found to have confronted traffic congestion at the longest mean time of 70.33 minutes per day and most of the people did not know the reasons for the congestion while most of the people who knew the reasons were from accidents. Confrontation with traffic congestion was found to have caused travelers to be willing to pay an additional of 30% of travel expenses in order to be aware of traffic information for use in making decisions. Travelers in Bangkok (100%) were found to have confronted traffic congestion and most travelers were found to have thought the aforementioned problem to be unsolvable. A cause of traffic congestions in Bangkok stems from the fact that most citizens in Bangkok use habitually use private automobiles as a habit and see traffic congestions as normal. In Thailand, a researcher in this field, found most travelers in Bangkok to disagree with fee collections or congestion prices at more than 70% from opinions that the aforementioned fee collection will cause vehicles to be congested on other routes because the number of vehicles did not decrease. Furthermore, drivers in Bangkok also have another reason in that fee collections or congestion prices are not fair to travelers with low income together with thinking that management systems by this method will be effective. Most travelers in Bangkok are used to the aforementioned problem and think to solve the problem only on a day-to-day basis. (Kunchornrat et al, 2007) According to this concept, Bangkok travel advisors, such as Cassandra in 2010, have recommended travel guidelines in Bangkok to avoid traffic congestion, stating that travelers should avoid traveling at 7:00 – 10:00 a.m. or 3:30 p.m. – 09:00 a.m. and 3:30 pm and 9:00 pm on normal days because those times are rush hours with the highest amount of traffic during the day and recommended travelers to 43 change modes of travel from automobiles to electric sky train or underground railways which cover 20% of the Bangkok area. Furthermore, travelers should avoid using taxi services during rush hours, which will help travelers travel faster. Travelers should study small alleys in Bangkok or shortcuts and travel by motorcycle, which will help travelers travel faster and cheaper than using taxis. Moreover, travelers should avoid traveling on rainy days if possible because Bangkok traffic is most congested on rainy days. (James, 2010)

Table 3 The characteristics factors affecting traveler‟s behavior in foreign countries

Researcher Year Research Description Asad et al. 1991 Gender, age and personal habits were found to 1993 have influence on travel behaviors and traffic information was found to have influence on route changes. Polydoropoulou et al. 1996 Drivers have trends of changing routes when receiving information recommending routes and want secondary information more than primary information which was received. Lotan 1997 Route changes. Persons unfamiliar with routes will have trends of changing routes after receiving traffic information more than persons familiar with routes. Abdel-Aty et al. 1997 Route changes, time, distance, delays, traffic information received and drivers‟ characteristics.

The travel information to help support the decisions of drivers by studying the characteristics of information most sought by drivers. This study categorized drivers into three categories according to travel routes comprising commuters, drivers in familiar areas and drivers in unfamiliar areas. According to the findings, each category of drivers was found to have different traffic information needs. Commuters 44 were found to seek traffic information on the route, such as congestion levels and travel time. Drivers in familiar areas were found to seek traffic information on the route and other alternative routes whereas drivers in unfamiliar areas sought information on recommended routes. Commuters and drivers in familiar routes were also found to have used longer waiting times than drivers in unfamiliar routes in order to change routes. (Richad , 1993) Asad researched the value of willingness to pay for real-time information services via telephone called “Traveler Advisory Telephone System” (TATS) by using the Revealed Preference (RP) technique and the Stated Revealed Preference (SP) technique with comparisons of current services and customized services together with setting service prices per time at three rates consisting of twenty-five cents, fifty cents and one dollar. The findings are in the table4. (Asad et al. (1997)

Table 4 The willingness to pay for the traffic information

Fee per call Average usage, current Average usage, customized service service $0.25 4.12 ( = 5.37) 7.09 ( = 6.62)

$0.50 2.55 ( = 4.23) 4.36 ( = 4.23) $1.00 1.03 ( = 2.76) 1.75 ( = 3.79)

From: Asad et al.,(1997)

According to the table 4, the value of willingness to pay can be concluded to increase when information services have higher quality and the number of times services are used is reduced when service fees increase. Furthermore, this study also found the value of willingness to pay to be related to personal factors in that persons with high income will be willing to pay for services at higher prices than persons with low income. Travel behaviors are found to be related to willingness to pay. In other words, persons with long travel time are willing to pay at higher values than persons who use less travel time and travel objectives are also related to the value of willingness to pay in that persons who travel for work are willing to pay at values 45 higher than persons who travel with other objectives. Furthermore, most service recipients used services via mobile phones rather than telephones installed at homes or offices. Louis conducted a study on the value of willingness to pay for real-time traffic information in San Francisco and found many channels of real-time traffic information service provision to exist whether in the form of commercial radio stations, highway advisory radio stations, changeable message signs, vehicle devices or the internet. This information came from government investment in data collection, processing and dissemination with the main objective of reducing traffic congestion and pollution problems. Concerning benefits to travelers from using information to make travel decisions, high quality travel information or the “Advanced Traveler Information System” (ATIS) will motivate travelers to be willing to pay for the information. The research stated the ATIS to have characteristics different from existing traffic information services comprising the following: 1) remind users automatically when delays occur on normal routes; 2) delay time estimates; 3) propose other alternative routes in the congested area and 4) estimate delay time compared to other proposed routes. According to the findings, most travelers who use traffic information services, or approximately 56%, chose to pay for each time travelers used services, 17% of travelers chose to make monthly payments, 22% of travelers believe traffic information should be a free service and 5.2% of travelers answered that they were not certain. With regard to the value of willingness to pay, travelers were found to be willing to pay a minimum of one dollar per time of receiving services and a maximum amount of seven dollars per month. (Wolinetz et al., 2001) The value of passenger willingness to pay in order to reduce travel time to an airport in Athens, Greece, by setting travel time reduction ability at 25% from the regular time and found the mean value passengers are willing to pay for to be 1.6 Euros by dividing consideration into three traveling characteristics. Most passengers (72%) were found to have chosen private automobiles and taxis for traveling to the airport because of convenience in moving baggage. This group of passengers was found to have a mean value of willingness to pay in order to reduce travel time at 1.80 Euros. Only a minority (28%) chose public transportation services with willingness to 46 pay 1.60 Euros. In cases where travel objectives were considered, passengers with business travel objectives were found willing to pay an average of 1.80 Euros while persons who traveled with other objectives were willing to pay at a mean value of 1.40 Euros. When travel origins were considered, passengers with travel origins in Athens were found to be willing to pay at a mean value of 1.20 Euros, which was less than passengers with travel origins at other cities in Greece who had a value of 6.00 Euros because different travel distances caused persons required to travel farther to be willing to pay more in order to reduce travel time to the airport. (Dimitrios, 2008)

Behaviors and the Value of Willingness to Pay Previous studies have shown traffic information to begin to have more roles in solving problems. The original channels for receiving news and information familiar to people in Bangkok are radios. The most popular radio stations reporting traffic conditions to people in Bangkok are Jor. Sor. 100 and Happy Station. The popularity of receiving traffic information by radio stems from a desire to know current or real-time information. At present, in addition to radio stations reporting real-time traffic information, we also see intelligent traffic signs with displays of traffic movements in colors, which are another form of real-time information system encountered in Bangkok. At the present, the automobile industry has developed navigation systems to facilitate drivers. The aforementioned devices can effectively link information from various sources together with receiving real-time traffic information for use in making decisions while traveling. Therefore, the development of automobile capacity with communications and information technology systems can be seen to be a part of traveling in the new era. The use of communications technology to receive real-time traffic information began in many countries and became more popular. Government and private agencies in some countries have developed the aforementioned system for providing services to the public and some systems have been commercially developed with devices on automobiles (Haithan, 1998), such as mobile phone systems developed in the GSM network and developed to support the same information systems as news and information services, music or image downloading through cell phones (Waadt, 2009). However, traffic information is considered to be detailed and 47 requires accurate processing systems together with quick reports through various media. Therefore, data collection costs for presenting service provision may be high, whether concerning government investing and service provision to traveling citizens or private commercial operations. In the beginning, monopolies cannot be avoided (Rong, 2006). However, regardless of who presented the aforementioned services, the issues to be considered involves who will use the information, which traveler groups are interested, what their travel behaviors are and what factors will enable travelers to benefit from the information. Furthermore, if information systems were commercially developed as a service, the questions of how and how much will buyers be willing to pay for this new form of service must be considered. According to the literature review, many factors have been found to be related to real-time traffic information utilization. Mannering (1994) found males and persons with high income to use traffic information and change routes more frequently than females. Furthermore, the times when these persons want to use information will be when traveling from the workplace back home. (Mannering, 1994) In 1995 Abdel-Aty found different genders to have different characteristics of information utilization. Females were found to have mostly checked information before traveling while males were found to have mostly used information while traveling. (Abdel-Aty (1995) In 1996 Englisher found that, out of the 61% of persons who use traffic information services through telephone channels, more than 75% were persons who traveled to work regularly and persons who travel long distance will use traffic information more than persons who traveled nearby with willingness to pay per time rather than make monthly payments. (Englisher, 1995) and traffic information developed to support in-vehicle navigation systems to have helped travelers know the fastest route from where they were to the destination.(Pearce, 2002) According to economic studies, the real-time traffic information changed travel demands in routes. According to the survey in 2003, 66.4% of travelers used traffic information and, of this number, 33% had changes in travel behaviors by using the aforementioned information in making decisions to change or avoid that route. Traffic information currently in use mostly comes from radio channels. In the near future, however, growing cell phone and internet markets will be important channels in supporting these information services. (Asad, rt al, 2003) The real-time traffic information to be a new technology will have roles and 48 support to travelers in the new era. However, real-time traffic information requires the development of forms and various characteristics to respond to user or traveler needs as much as possible in terms of time and information display. (Dziekan, 2006) Although there have been studies confirming personal factors and economic factors to influence choices to use real-time traffic information services; however, according to additional reviews, many studies have been found to have indicated that, in addition to the aforementioned factors, factors related to information quality have also been found to influence decisions about using real-time traffic information such as Asad who studied the value of willingness to pay for real-time traffic information services by comparing current services with customized services and setting service rates per time, finding the value of willingness to pay to increase when information services had higher quality and the number of times in using services to be reduced when service prices increase. (Asad et al, 1997) This was found to be consistent with Louis who conducted a study on the value of willingness to pay for real-time traffic information in San Francisco by setting ATIS (Advanced Traveler Information System) to have characteristics different from existing traffic information services consisting of the following: 1) remind users automatically when delays occur on normal routes; 2) delay time estimates; 3) propose other alternative routes in the congested area and 4) estimate delay time compared to other proposed routes. According to the findings, most travelers who used traffic information services or approximately 56% chose to pay, indicating that information levels or quality also influence decisions to use services. (Wolinetz et al., 2001) The use of communications technology to receive real-time traffic information began in many countries and has been growing in popularity. Government and private agencies in some countries have developed the aforementioned system for providing services to the public and some systems have been commercially developed with devices on automobiles (Haithan, 1998) and mobile phone systems were developed in the GSM network to support information systems (Waadt, 2009) in the same way as news and information services, music or image downloading through cell phones. However, traffic information is considered to be detailed and requires accurate processing systems together with quick reports through various media. Therefore, data collection costs for introducing service 49 provision may be high, whether it was the government investing and providing services to traveling citizens or private commercial operations. In the beginning, monopolies cannot be avoided (Rong, 2006). However, regardless of who introduces the aforementioned services, what must be considered is who will use the information, which traveler groups are interested, what their travel behaviors are and what factors will enable travelers to benefit from the information. Furthermore, if information systems are commercially developed as a service, the questions of how and how much buyers are willing to pay for this new form of service must be considered. According to the literature review, many factors are related to real-time traffic information utilization comprising the following:

Table 5 Summarization of the willingness to pay for the traffic information

Author Year Research Findings Mannering 1994 Males with high income will use traffic information and change routes more frequently than females. The time for using information will the time spent in making the trip from work back home. Abdel-Aty 1995 Different genders will have different characteristics of information utilization. Most females will usually check information before traveling while males generally use information while traveling. Englisher 1995 Of the 61% of persons using traffic information services via telephone channels, more than 75% were travelers who travel to work regularly. Persons who travel far will use traffic information more than close-range travelers with more willingness to pay per service than making monthly payments.

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Table 5 (Continue)

Author Year Research Findings

Wolinetz et 2001 Traffic information developed to support in-vehicle al. navigation systems helped drivers know the fastest route from their current position to the destination. According to economic researches, real-time traffic information changed travel demand on routes. Asad et al. 2003 According to a survey of travelers, 66.4% used traffic information and 33% of the aforementioned modified travel behaviors by using the aforementioned information to make decisions, such as in changing or avoiding routes. Most of the traffic information currently used was from radio channels. In the near future, however, growing cell phone and internet markets will be important channels in supporting information services.