Optimizing Bus Transfer Coordination Casestudy of Asia Jaya Bus Stop Klang Valley Region - Malaysia

Optimizing Bus Transfer Coordination Casestudy of Asia Jaya Bus Stop Klang Valley Region - Malaysia Ahmed Abdel Shakour Abdel Aziz Abdel Dayem April, 2005

Optimizing Bus Transfer Coordination Casestudy of Asia Jaya Bus Stop Klang Valley Region - Malaysia By Ahmed Abdel Shakour Abdel Aziz Abdel Dayem Thesis submitted to the International Institute for Geo-information Science and Earth Observation in partial fulfilment of the requirements for the degree of Master of Science in Geo-information Science and Earth Observation, Specialisation: (Urban Infrastructure Management) Thesis Assessment Board Dr. R.V. Sliuzas (Chair) Ir. M.H.P. Zuidgeest (External Examiner) T.G.Munshi, MSc (First Supervisor) Ing. F.H.M Van Den Bosch (Second Supervisor) INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION ENSCHEDE, THE NETHERLANDS

Disclaimer This document describes work undertaken as part of a programme of study at the International Institute for Geo-information Science and Earth Observation. All views and opinions expressed therein remain the sole responsibility of the author, and do not necessarily represent those of the institute.

Abstract In big metropolitan cities and large urban areas the demand for public transit is often widely spread and significantly varies over space and time. In such a situation providing a door to door trip between all pairs of origins and destinations is neither applicable nor cost-effective. An attractive and efficient alternative is to serve the passengers by an efficient intermodal system. In such a system, passengers may need one or more transfers to complete the journey to their final destination. Consequently, coordinating transit schedules to reduce transfer time can contribute significantly in improving the transit service quality and increasing the passengers ridership levels. Such coordination should be dealt with carefully to grantee the satisfaction of the inherently conflicting objectives of the passengers and the transit system operator. In the present research the benefits of coordinating the schedules of main stage buses with secondary feeder buses at a transfer stop is assessed and evaluated through a 3-stage optimization model. A total cost objective function that represents both the passengers and the operator objectives is formulated and optimized for each stage of the optimization model to determine the optimal coordination status among the coordinated bus route at the selected transfer stop. In the first stage the operating headways of both the stage and the feeder buses are optimized under uncoordinated service, the corresponding total cost is also obtained and compared with the total costs under the current existing situation. In the second stage all possible combinations of stage-feeder bus coordination at the stop are tested and corresponding total costs cost of each combination is also obtained. The results of the second stage are compared with the existing situation results as well as the first stage results and the coordinated combination resulting in the minimum total costs is identified. In the third and last stage the optimal slack time added to the schedule of the coordinated buses to increase the probability of a successful connection and overcome the stochastic arrivals of buses to the stop under the varying traffic conditions. Furthermore, the present research also explores and investigates the potential role that Advanced Public Transport Systems (APTS) fleet management technologies can play if deployed in enhancing and improving the handling of the transfer coordination problem in the real-time context as well as in the long run. Firstly, the APTS fleet management technologies that can play a role in improving the efficiency of coordinated transfers are identified. Then the integration of the out put data of these technologies is discussed and elaborated. Finally potential improvements to the handling of the transfer coordination problem in both the real-time context and the long run are cleared and emphasized. The concluded study is that coordinated transfers between the stage and feeder buses under a common headway is beneficial when the increase the in-vehicle and waiting time costs can be compensated by the savings in the transfer time costs. Also the desirability of coordinated transfers is highly dependent on the transfer passengers'volume, the standard deviation of vehicle arrivals to the stop. It was also found that the integration of APTS fleet management technologies specifically Global Positioning Systems (GPS), Automatic Passengers Counters (APC), Geographical Information Systems (GIS) and Communication Systems can play a very significant role in facilitating coordinated transfers in the real-time context making the bus system more dynamic and demand responsive. i

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Acknowledgements First and foremost, I would like to express my thankfulness to Allah God Almighty for giving me the strength and willingness to work in this research till it finally saw the light. I would like to express my sincere appreciation to both my supervisors. Firstly, to my first supervisor MSc.Talat Munshi, for his unlimited and continuous support and his critical comments aiming to enhance and improve the present research. Secondly, to my second supervisor Ing. Frans van den Bosch, for his help and assistance during the whole study period at the UPLA program and for his guidance as my second supervisor. In the hard times of this research which as I recall were many, both of them stood by me and supported me, for that I am very thankful and grateful. I am greatly indebted to Ir. Mark Brussel, UIM specialization coordinator. In the last three years, we have interacted in so many ways, firstly, as a colleague and partner in UTI, secondly as a lecturer in ITC and thirdly as a research proposal advisor. Throughout that time, I have gained a plenty of valuable experience from him. I hope that will not be the end of it. Special thanks go to Ir. Mark Zuidgeest for his help and support in the conceptualizing and solving some parts of this research, whenever I asked for his help he was there for me. Thanks are also due to Dr. Clement Atzberger for helping me to formulate my model in MatLab, it was really a necessity for my research to be completed. I would like also to pay tribute to Dr. Luc Boerboom for his help during the formulation of the proposal and for making it possible for me to do my fieldwork in Malaysia. I am also thankful to all those who assisted me in collecting the required data in Malaysia specially to the staff and the students of the transportation department at the Malaysian University of Science and Technology M.U.S.T, to the staff of the Malaysian Ministry of Federal Territory, to Mr. Kamalruddin Shamsuddin, Mr. Loga veeramuthu, and En. Mohd Razif. Needless to say, that I am grateful to all of my colleagues at the Urban Planning and Land Administration Program UPLA 2003 specially Sohel, Indra, Prat, Ilham, Pratima, Zack, Refat, Ai Ping and Abdel Aziz. With them, I shared many wonderful moments, thoughts and experiences and from each and every one of them I have learned something new. Special thanks and deep gratefulness to my friend, roommate and colleague both at work and at ITC Amr, together we have been through both good and bad times in the last one and half years. Thanks also to my fellow Egyptians, Aiman and Naser from the year before and Mohamed from the year after. Thanks to my newest friend Bakim from India for lending me his laptop in the last day before submission when mine unfortunately crashed Finally yet importantly, I would like torecognize the unrelenting long-distance support of my family back home in Cairo. Their prayers for me were the main source of inspiration, motivation and encouragement to continue this work. To my Parents, this work is dedicated for you. Ahmed Abdel Dayem April 2005 iii

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Table of contents 1. Introduction, Problem Statement and Research Methodology...1 1.1. Introduction...1 1.2. General Overview of Study Area and Justification...2 1.3. Problem statement...4 1.4. Main Objective...5 1.5. Sub objectives...5 1.5.1. Research Questions...5 1.6. Research Design...5 1.7. Overview of Research Methodology...6 1.7.1. Data Collection and Current Situation Analysis (Stage 1)...7 1.7.2. Optimization of Transfer Coordination (Stage 2)...7 1.7.3. Potential Role of APTS Technologies in facilitating coordinated transfers (Stage 3)...8 1.8. Outline of the Thesis...9 2. Public Transport Network Design A Transfer Coordination Approach...11 2.1. Public Transport Network Design Problem...11 2.1.1. Main Characteristic...11 2.1.2. Stakeholders Identification...11 2.1.3. Public Transport Optimization Problem Description...13 2.1.4. Intermodalism Main Concept...15 2.2. The Transfer Coordination Problem...15 2.2.1. Decision variables...16 2.2.2. Previous Models on Transfer Coordination...16 2.2.3. Important Issues in Transfer Coordination...19 2.3. Advanced Public Transport Technologies Potential Role in solving the Transfer Coordination Problem in the Real-time Context...20 2.4. Conclusions...24 3. Case Study Location, Data Collection, and Current Situation Analysis...26 3.1. Asia Jaya Stop Selection...26 3.1.1. Expert Knowledge...26 3.1.2. Quick Overview...26 3.1.3. Brief Description of the Stop Location...27 3.2. Data Collection...27 3.2.1. Primary Data Collection...27 3.2.2. Secondary Data Collection...28 3.3. Present Situation Analysis...29 3.3.1. Network Analysis...29 3.3.2. Transfer Demand Percentage...31 3.4. Selected Routes Passenegrs'Demand Calculations...32 3.4.1. Stage Buses Passengers Demand...32 3.4.2. Feeder Buses Passengers Demand...33 3.5. Headway Devation...34 v

3.6. Transfer Time Analysis...36 3.6.1. Passengers Transfer Times and Transfer Time Appreciation...36 3.6.2. Transfer Time Fluctuation...37 3.6.3. Value of Time...38 3.6.4. Transfer Time Losses...39 3.6.5. Transfer Time Financial Losses...40 3.7. Conclusions...40 4. ASIA JAYA - OPTIMIZATION OF TRANSFER COORDINATION...42 4.1. Problem Identification...42 4.2. Model Assumptions...42 4.3. Rationale of The Optimization Model...44 4.3.1. Transfer Direction...45 4.4. Demand Functions Formulation...46 4.4.1. Stage Bus Passengers Demand...46 4.4.2. Feeder Bus Passengers Demand...46 4.5. Building Blocks of The Optimization Model...46 4.6. Conclusions...75 5. APTS Provision Potential Role in the Transfer Coordination Problem...77 5.1. Technology Data Output...77 5.1.1. GPS Data Output...77 5.1.2. APC Data Output...78 5.1.3. GIS Data...79 5.2. GPS and APC Output Data Integration within a GIS Platfom...80 5.3. Potential Improvements in Coordinating Bus Transfers and limitations...82 Real-time improvement...82 5.4. Conclusions...83 6. Conclusions and Recommendations...85 6.1. Introduction...85 6.2. Results against research outline...85 6.3. General Conclusions...89 6.4. Study area Recommendations...89 6.5. Further Research Recommendations...90 References...93 Appendix (A): Value of time Calculation for the study Area...95 Appendix (B): Passengers Questionnaire...96 Appendix (C): MatLab Script...97 vi

List of figures Figure 1-1 Malaysia in The regional Settings...3 Figure 1-2 TheCase Study Location - Klang Valley Region - Malaysia...4 Figure 1-3 Structure of Research Methodology...6 Figure 2-1 Illustration of Passenger and Operators Optimal Design of the Public transport Network (Source: Van Nes 2000)...12 Figure 2-2 Structure of the Analytical Approach...13 Figure 2-3 APTS Fleet Management Technologies...21 Figure 3-1 Asia Jaya Stop Location...27 Figure 3-2 The Service Area of The Slected Bus Routes...30 Figure 3-3 Feeder Bus Route 904A & 904B...30 Figure 3-4 Overall Stage Bus Passengers Demand at Asia Jaya stop Survey Results...31 Figure 3-5 Percentage of Transfer to Non Transfer...31 Figure 3-6 Headway Deviation Stage Bus 47 - PM Peak Outbound Direction...34 Figure 3-7 Headway Deviation Stage Bus 47 - PM Peak Outbound and Inbound Direction...34 Figure 3-8 Headway deviation Feeder Bus 904B - AM Peak...35 Figure 3-9 Headway deviation Feeder Buse 904A - AM Peak...35 Figure 3-10 Average transfer time at Asia Jaya Stop...36 Figure 3-11 Bus Passengers Preference...37 Figure 3-12 Transfer Time - 47 and 904A - AM Peak - Outbound and Inbound Direction...38 Figure 3-13 Transfer Time - 47 and 904B - AM Peak - Outbound and Inbound Direction...38 Figure 3-14 Transfer Time Loss - Asia Jaya stop - AM Peak - Outbound Direction and Inbound Direction...39 Figure 3-15 Transfer Time Loss -Asia Jaya stop -PM Peak Outbound and Inbound Direction...39 Figure 3-16 Transfer Time Financial Losses - Asia Jaya Stop -AM Peak & PM Peak...40 Figure 4-1 Stages of the Optimization Model...44 Figure 4-2 Passengers Transfer Movement at Asia Jaya Stop- Outbound and Inbound Directions...45 Figure 4-3 Steps of the Optimization Model Stage (1)...47 Figure 4-4 Total Cost Structure - Stage (1)...47 Figure 4-5 The Headway - Passengers Cost Relationship...52 Figure 4-6 The Headway-Operators Cost Relationship...53 Figure 4-7 The Headway -Total Cost Relationship...53 Figure 4-8 Steps of the Optimization Model Stage (2)...57 Figure 4-9 Total Cost Structure - Stage (2)...58 Figure 4-10 Joint Probabilty of successful Connection Stage 2 -Outbound Direction...60 Figure 4-11 Joint Probabilty of successful Connection Stage 2 - Inbound Direction...60 Figure 4-12 Joint Probabilty of Missed Connection Stage 2 - Inbound Direction...62 Figure 4-13 Joint Probabilty of successful Connection- Stage 2 - Inbound Direction...63 Figure 4-14 Steps of the Optimization Model Stage (3)...67 Figure 4-15 Total Cost Structure - Stage (3)...67 Figure 4-16 Joint Probabilty of successful Connection - Stage 3 - Outbound Direction...70 Figure 4-17 Joint Probabilty of successful Connection Stage 3 - Inbound Direction...70 Figure 4-18 Joint Probabilty of Missed Connection Stage 3- Outbound Direction...72 vii

Figure 4-19 Joint Probabilty of Missed Connection Stage 3 - Inbound Direction...72 Figure 5-1 Traditional way of modeling public transport in a transport mode...79 Figure 5-2 GPS data collected for stage bus 13 - AM Peak...80 Figure 5-3 Schematic representation of relating the GPS data to the bus network data using (LRS)...81 viii

List of tables Table 2-1 Analytical and Numerical Solutions - Advantages and Disadvantages...14 Table 2-2 APTS Fleet Management Technologeis...20 Table 2-3 GPS Technology - Advantages and Disadvantages...22 Table 3-1 Data Survey Methds - Passengers Questionnare...28 Table 3-2 Selected buses operating headway...29 Table 3-3 Overall Selected Stage Bus Passengers Demand - Asia Jaya Stop...32 Table 3-4 Transfer Demand - Selected Stage Buses to Feeder Buses...32 Table 3-5 Overall Passengers Demand for Feeder Buses Asia Jaya Stop...33 Table 3-6 Stage to Feeder Bus Transfer Demand...33 Table 3-7 Transfer Demand - Selected Stage Buses to Feeder Buses...33 Table 3-8 Headway Standard Deviation / Mean Headway - Selected Stage Buses - Asia Jaya Stop...35 Table 4-1Optimal headway of stage buses - stage (1)...54 Table 4-2 Optimal headway of feeder buses - stage (1)...55 Table 4-3 Financial gains from resulting from stage (1)...55 Table 4-4 Total Costs Under Coordinated Service (RM) - Stage (2)...65 Table 5-1GPS survey Bus 13 AM Peak...78 Table 5-2 Manual Passengers Counting - Bus 13 - AM Peak...79 ix

1. Introduction, Problem Statement and Research Methodology 1.1. Introduction With the rapid growth of urbanization all over the world the demand for public transit is dramatically increasing. Providing a door to door public transit service in large cities and widely spread urban areas is neither applicable nor affordable for a number of reasons. Firstly the number of origins and destinations to be covered is huge and widely spread. Secondly in big cities the transport network for road based transportation is over congested and cannot accommodate the large volumes of public transit services resulting from providing a door to door trip from all origins to all destinations. Thirdly providing a door to door trip between all origins and destinations is not a cost effective approach because of the demand variations over space and time. Finally there are more environmental issues to be considered such as the air pollution resulting from large traffic volumes in big cities and large urban areas. An efficient alternative is to have a well designed intermodal transit network with acceptable transfer time for passengers. An intermodal network can be defined as an integrated transportation system consisting of two or more modes. In contrast to multimodal networks, modes on intermodal networks are connected through facilities which allow travellers and or freight to transfer from one mode to another during a trip from an origin to a destination. Intermodal networks aim to provide efficient, seamless transport of people and goods from one place to another (Boiler 2001). Unfortunately, transfers involve certain inconveniences connected with discomfort of boarding a new vehicle (necessity of passenger orientation and walking between vehicles on feeder and receiving lines), negative perception of waiting for arrival new vehicle and existence of some delay during a trip (Adamski and Bryniarska 1997).A well designed intermodal transit network should be able to facilitate the passengers'transfers between transit modes in order to reach their final destination. When facilitating passengers transfers there are more than one element to be considered such as transfer time, total trip time, number of transfers, comfort of transfers, and the fare of transfers. All theses elements should be considered and designed to balance and fulfil the interests of the stakeholders involved namely the passengers, the service providers and the authorities. Transfer time tends to be the common measure of intermodal systems performance (Miller and Tsao 1999). The transfer time is the time duration that passengers coming from one transit mode have to spend at a transfer stations waiting for the other mode to arrive to take them to their destination. Transfer time is one of the most important public transit service quality indicators. The higher the transfer time the lower the riderdhip and the service quality. One possible alternative to minimize the transfer time is to increase the service frequency or in other words decrease the service headway by increasing the number of vehicles operating on the transit line. Low operating headway, which can 1

substantially reduce transfer time, is not always cost effective due to variations of demand among transit routes over space and time (Chowdhury 2000). Aside from decreasing the service headway, a well designed and implemented passengers transfer coordination on the main transfer stops is a more attractive and effective solution to minimize the transfer time. In a bus transit system a timed transfer exists when multiple bus routes are scheduled to arrive on or about the same time at a transfer stop, with the goal of enabling short waiting times when transferring between routes (Dessouky 1999). Although a well designed and implemented transfer coordination might work perfectly in rural areas and uncongested urban areas that might not be the case for the large urban areas with high congestion rates. Public transit in those areas is subject to on street traffic environment and transit agencies may find it more difficult to maintain its vehicles as scheduled. To overcome such an obstacle a holding time at the transfer stop called the slack time is added to the schedule of the connecting vehicles to increase the probability of a successful connection in case one or more of the connecting vehicles are late. The determination of the optimal common headway and slack times for the connecting vehicles is a part of the design of the intermodal transit network. Both the common headway and the slack times should be determined in such away that satisfies the objectives of the threes stakeholders involved. In transit networks design three stakeholders are involved, each of them having their own point of view on the objective that has to be used for the design; the passengers, the service providers and the authorities respectively (Van Nes2000). In the case of transfer coordination passengers are mainly concerned with minimizing their travel time including their waiting, transfer and in-vehicle time while the service providers are concerned achieving an acceptable profit and revenue. All of this should be done taking into account the regulation and the constraints imposed by the responsible authorities. Still and even with an efficient design of the optimal common headway and slack times that satisfies the stakeholders'objectives the system reliability cannot be fully granted. In the absence of communication and tracking technology, timed transfer systems must rely on set schedules, combined with driver observations, for bus coordination. Buses can be held beyond their normal departure time if drivers observe that connecting buses are late. However, they can have no idea of how late the buses will be, or whether they will arrive at all (Dessouky 1999). With the deployment of Advanced Public Transportation Systems APTS such as Automatic Vehicle Location AVL, Automatic Passenger Counting APC and Geographical information systems GIS this problem can be better dealt with. With the help of these technologies the transit agencies will be able to monitor its whole fleet in the Real-time context and instruct the drivers to take certain actions to maintain the level of service and to keep the situation running as planned. In the case of transfer coordination, these technologies can be used to develop real-time control strategies at the main transfer stops for holding or dispatching the involved buses making the process of transfer coordination more efficient and demand responsive. 1.2. General Overview of Study Area and Justification Malaysia, Country of Southeast Asia. From the Mid-1970 to the Mid-1990, Malaysia had one of the world's fastest growing economies. As expected, the rapid of growth of the economy encouraged rapid urbanization and motorization all over the whole country. 2

Figure 1-1 Malaysia in The regional Settings (Source: www.theodora.com) The highest urbanization and motorization is observed in the commercial capital city Kuala Lumpur and the Klang Valley region. Common to most towns in Malaysia, the existing public transport system in the Klang Valley region is dominated by buses (PTK report 2003). The bus services in Klang Valley consist of stage buses and express buses. The stage buses in the Klang Valley can be further divided into two categories namely the stage buses and the feeder buses. There more than 12 stage bus companies operating at the study area. The three main operators are IntraKota, MetroBus and City Liner. Apart from the stage bus, operators there are two feeder bus operators providing services to the passengers in the Klang Valley namely the PUTRA feeder buses and the STAR feeder buses. The feeder bus service is meant to provide the LRT passengers and stage bus passengers in the major public transport corridors with a trip to their final destination on the surrounding suburban areas after alighting the LRT or the stage bus or from the suburban areas to the nearest LRT station or stage bus stop. As stated in Schwarcz (2003) the bus ridership which is one of the main public transportation modes in the Klang Valley region in Malaysia is very low in general, representing approximately 20% of the total person trips in the region, as compared with other big cities in the neighbouring countries where it ranges from at least 40% to over 70%. One of the main causes of the low bus ridership levels in the region as mentioned in the study is that transferring between buses run by different operators represents a great difficulty since there is no coordinated service between them or even between buses ran by the same operator not to mention transferring between different modes. Another study was carried out in the year 2004 by the special task force for public transportation restructuring in the Klang Valley region. The study found out that 26% of the trips made by public bus in the region involve transferring to another bus to continue the journey to the final destination. The study indicates that this 26% is a very significant proportion and those transfers needs to be facilitated with efficient connectivity. The same study further implies that the maximum transfer time should not exceed time duration of 3.5 minutes and uses this value as the basis of their proposed public transportation network design. 3

1.3. Problem statement Figure 1-2 TheCase Study Location - Klang Valley Region - Malaysia In the klang Valley region transferring between buses operated by different companies with uncoordinated routes and schedules have made intermodality in the system unfavourable to the users (Zakaria 2003). The transfer coordination problem is inherently conflicting. Passengers are mainly interested in having their trip with the lowest possible transfer time, which implies a higher service frequency and consequently a higher operating cost. On the other hand the service provider is interested in having the lowest operating costs and the highest revenue which implies a lower service frequency. A trade-off solution is needed that provides the passengers with acceptable transfer times while interchanging between different buses and the same time provides the service operator with acceptable revenue that allows them to maintain their service quality and continuity of their business. 4

1.4. Main Objective The objective of this research is to evaluate and assess the benefits of coordinated transfers between the different bus providers at the study area and to emphasis the role that APTS technologies can play to support the desired coordinated transfers. 1.5. Sub objectives 1- To assess the current transfer situation between the selected bus routes in the study area 2- To optimize the transfer coordination between the selected bus routes in the study area 3- To explore, investigate and emphasis the role that APTS technologies can play to facilitate, control and improve the efficiency and of the desired coordinated bus transfers. 1.5.1. Research Questions To assess the current transfer situation between the selected bus routes in the study area 1- How important is the transfer time as one of the quality service indicators for the passengers at the selected stop? 2- How long is the transfer time between connecting buses at the study area under the current situation? And what are the equivalent financial losses to the lost time in transferring at the selected location? To optimize the transfer coordination between the selected bus routes in the study area 3- What are the major objectives (costs and benefits) of the passengers and the operators? 4- How can those objectives be formulated mathematically? 5- What is the approach for evaluating the optimal value of the optimization model decision variables? 6- What are the optimal values of the decision variables after solving the optimization problem and their corresponding financial gains? To explore, investigate and emphasis the role that APTS technologies can play to facilitate, control and improve the efficiency and of the desired coordinated bus transfers 7- What are the relevant APTS technologies that can play a role in solving the transfer coordination problem in the real-time context? 8- How to integrate these technologies to solve the transfer coordination problem? 9- How can the transit agency make use of the integrated data available from to facilitate the coordinated transfers in both the real-time context and the long term? 1.6. Research Design The present research has three main components, identifying the transfer Time losses and the subsequent financial losses for the study location, conducting a transfer coordination study at the study location to evaluate the benefits of coordination and finally exploring and emphasising the potential role of APTS technologies in improving and supporting the handling of the transfer coordination problem in the real-time context. The study is a pilot study since it cannot be carried out for the whole bus network of the study area due to time, manpower and equipment constraints and complexity of the problem. Hence a representative part of the bus network is selected and the study will be carried out for that part. 5

1.7. Overview of Research Methodology Figure (1-3) gives an overview of the methodology followed in the present research. The stages of the proposed methodology are discussed and highlighted one by one in the following sections. The steps followed in each stage are discussed as well as the tools used to conduct them and the expected output of each stage. Figure 1-3 Structure of Research Methodology 6

1.7.1. Data Collection and Current Situation Analysis (Stage 1) In the first stage the following procedure was followed in the data collection process and the assessment of the current situation at the study area. For Further detail on the data collection process and the assessment of current situation see chapter (3). 1) Data Collection Plan: Based upon the literature reviewed a fieldwork data collection plan was designed and followed to collect the minimal data required for the proposed research. 2) Expert Knowledge: An expert in public transportation modelling in the Klang Valley region was consulted for assistance in selecting a potential transfer stop to carry out the proposed research 3) Data Collection: A data collection process took place at the selected transfer stop. The data collection aimed to achieve the following three aims. Firstly to select the bus routes that are most suitable for a transfer coordination study based on criteria developed from the literature study. Secondly to collect the data required for the selected routes to assess the current transfer situation between them and the time and financial losses under the present uncoordinated situation. Thirdly to provide the data input for the proposed subsequent transfer coordination study. 4) Current Situation Analysis: Using the data collected in the previous step the transfer time losses are determined, quantified and analyzed for the selected bus routes under the present situation. There are three main outputs resulting from the first stage; The selection of the stop and routes that are most suitable for coordination based on expert knowledge and criteria identified through literature. The collection of the data required to pursue the remaining stages of the research The assessment of the current situation with respect to transfer time losses using both time and financial analysis. 1.7.2. Optimization of Transfer Coordination (Stage 2) In the second stage the following procedure was followed in the formulation of the optimization model For Further detail on the optimization process see chapter (4). 1) Problem Identification and Model Assumptions: Guided by the literature reviewed and complying with the data limitations, the problem is identified and the basic assumptions required to be able to model the problem are made. 2) Mathematical Formulation of Stakeholders Objectives: Guided by the literature reviewed the stakeholders objectives are formulated mathematically in terms of the problem decision variables and other involved parameters. 3) Stages of Coordination and Objective Function Formulation: In this step the approach and the stages to be followed for transfer coordination in the present study is discussed and explained. The corresponding objective function is formulated for each of the proposed coordination stages 4) Optimization of Transfer Coordination: In this step the solution technique to be followed for each of the proposed coordination stages is identified and followed. The results of the optimization process are obtained in terms of the problem decision variables. 7

5) Assessment of the Transfer Coordination Benefits: Using the results obtained from solving the optimization model the benefits of coordination are identified and highlighted compared with the current situation. 6) Sensitivity Analysis: In this step a sensitivity analysis is conducted to measure the sensitivity of the optimization model decision variables to the other parameters involved in the problem formulation. The sensitivity analysis is a good tool to understand the problem behaviour and to overcome the limitations and the unreliability of the data collection There are four main outputs resulting from the second stage; The identification of the best combination for transfer coordination among all possible combinations of the selected stage and feeder buses. The determination of the optimal values for the problem decision variables and their sensitivity to the other parameters involved in the problem formulation The determination of the financial costs of the proposed coordination for each of the stakeholders involved and for all of them as a whole. The determination of financial gains resulting from the proposed coordination when compared to the current situation. 1.7.3. Potential Role of APTS Technologies in facilitating coordinated transfers (Stage 3) In the third stage the following procedure was followed to explore and emphasis the role of APTS technologies in facilitating coordinated transfers. For Further detail on the APTS see chapter (5). 1) Review of Relevant APTS Technologies: Based upon the literature reviewed a number of APTS technologies related to the improving and dealing with the transfer coordination problem in the real-time context are to be identified. In this step a brief description of each of these technologies and its benefits is provided 2) Integration of the Selected APTS Technologies: Guided by the review of the related APTS technologies conducted on the previous step integration issues between these technologies are also discussed and presented 3) Potential Improvements and Expected Benefits: In this step the potential improvement and the expected benefits of using these technologies are discussed with respect to their role in handling the transfer coordination problem. There are three main outputs resulting from the second stage; The identification of the APTS technologies relevant to the enhancement of solving the transfer coordination problem in the real-time context The development of the proposed integrated methodology that improves the manipulation and the visualization of the transfer coordination problem in the real-time context The identification of the main benefits expected from the implementation of the proposed methodology 8

1.8. Outline of the Thesis Chapter 2: "Literature Review" The second Chapters provide detailed insight into the transfer coordination problem as one of the intermodal network design problems. Major stakeholders involved in the problem are identified with their interests. Solution techniques are also discussed as well as pervious models used to solve the problems. An overview of the relevant APTS technologies is also provided that can assist in solving the transfer coordination problem in the real-time context. Chapter 3: "Data Collection, Case Study Location and Current Situation Analysis" The fourth chapter provides a detailed description of the data collection process, the selection of the case study location and the assessment of the current situation with respect to the transfer time losses. Chapter 4: "Optimization of Transfer Coordination" The fifth chapter contains the development of the transfer coordination optimization model, the optimization model results, the evaluation of the benefits coordination study and the sensitivity analysis. Chapter 5: "APTS Provision Potential Role in the Transfer Coordination Problem" The sixth chapter provides a review of the related APTS technologies and their integration issues with the aim of emphasising the potential role and the expected benefits of the deployment of APTS technologies with respect to the handling of the transfer coordination problem in the real-time context. Chapter 6: "Conclusions and Recommendations" The seventh and the last chapter highlight the main conclusions of the research and provide recommendation for the study location as well as for future research. 9

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2. Public Transport Network Design A Transfer Coordination Approach The present chapter provides an insight into the different aspects of the transfer coordination problem as one of the problems of the intermodal public transport network design. It starts with a definition of the public transport network design problem and the identification of stakeholders involved in it, their main interests, concerns, and its effect on the network design objectives. Then an overview of the transfer problem and all its related aspects is given with a specific emphasis on transfer coordination being the main element of concern in present research. The transfer coordination problem basic elements and variables are also discussed with available solution techniques. A review of previous models developed on the transfer coordination problem is then conducted with their advantages and the shortcomings. Finally, an overview of related Advanced Public transport technologies APTS is conducted with its potential role in improving the management of the transfer coordination problem in the real-time context. 2.1. Public Transport Network Design Problem 2.1.1. Main Characteristic The main characteristic of public transport network design is the balance between opposing objectives. A design that is optimal with respect to one objective is not optimal for the other objective, and vice versa (Van Nes 2000). While passengers are interested in a fully connected network between all origins and destinations with minimum travel times, fees and maximum comfort the operator or the service provider is interested on having the smallest network possible with the highest revenue and the lowest operational costs. Accordingly, Attention should be paid while selecting the network design objectives so that they satisfy, represent and consider the conflictive views and the opposing interests of the stakeholders involved. 2.1.2. Stakeholders Identification In public transport network design there are three parties involved, each of them having their own point of view on the objective that has to be used: traveller, operator, and authorities respectively (Van Nes 2000). The passenger s judge or value the public transport services by three main components: travel time, costs, and comfort. The major and the most crucial component to the passenger is the perceived doorto door travel time. The door-to door travel time consists of various time elements namely access time, waiting time, transfer time, in-vehicle time and egress time. Each of these travel time elements is perceived, weighted and appreciated differently for each passenger. A suitable network design objective for the passenger might to be to minimize one of theses time elements or to minimize the weighted total travel time. Using this objective for the network design will result in fully connected networks with very high public transport frequencies. This is obviously not a suitable design for the operators since the operational costs will be huge when compared to the revenue or the profit coming from operating the public transport system. 11

The operator s view of the system is very different; his main concern is the continuity and the of the profitability business. A suitable network design objective for the operator might be to maximize the profit, which is the revenue minus the operational cost or to minimize the operational costs. Obviously using this objective for design will result in poorly connected network with very long travel times and very low frequency public transport services. Ultimately, if such an objective is used in network design the ridership levels will decrease and as a result, the system profitability will decrease as well (Van Nes 2000). A - Passenger Optimum B- Operator Optimum Figure 2-1 Illustration of Passenger and Operators Optimal Design of the Public transport Network (Source: Van Nes 2000) The authorities, the third and the last stakeholder involved have their own different agenda. A suitable objective for the network design from the authority s point of view might be minimizing the total costs of the system including both the passenger s and the operator s costs. The authorities might also be interested on minimizing the subsidy given to the operator. Apart from defining design objectives, the authorities might play another role in public transport network design, namely setting constraints such as a maximum access distance or a minimum frequency. In that case the operator can use his own objective in the public transport network design as long as those constrains are fulfilled and satisfied (Van Nes 2000). In Conclusion, it can be clearly seen that the stakeholders objectives are mainly opposing and conflictive. With respect to figure (2-1) an optimum design of public transport network should be close to the operator optimum but with introducing transfer stops or hubs in intermediate locations where large passengers'volumes are generated. At those hubs various routes coming from different origins and going to different destinations should be connecting. Providing transfer passengers at those hubs with seamless mobility by coordinating the services of the connecting buses to minimize the time spent in transfers is a good alternative to the unrealistic door to door trip. A suitable analytical approach to reach this optimum design is mathematical optimization. The objective of optimization is to select the best possible decision for a given set of circumstances without having to enumerate all of the possibilities (Giordano and Weir 2001). 12

2.1.3. Public Transport Optimization Problem Description The goal of an optimization problem can be defined as follows: find the combination of parameters (independent variables) which optimize a given quantity, possibly subject to some restrictions on the allowed parameters range. The quantity to be optimized (maximized or minimized) is termed the objective function; the parameters, which may be changed in the quest for the optimum are called control or decision variables; the restrictions on allowed parameters values are known as constraints ((Giordano and Weir 2001). With respect to section (2.1.2) the goal of the optimization problem will be to find the optimal value of the design variables such as stop spacing, stop location and service headway that best satisfies the operators, the passengers and the authorities'objectives. Van Nes (2000) formulated an optimization based analytical approach that can be used for public transport network design (Figure 2-1). In his approach, he used the following terminology: Objective: The Criterion or set of criteria to be optimized, for instance minimizing travel time; Objective function: Mathematical formulation of the objective using the decision variables; Design Variables or Decision Variables: endogenous variables for which optimal relationships or optimal values have to be determined, in his case design variables are stop spacing and line spacing Design parameters: exogenously given parameters used in the mathematical formulation that are not determined by public transport system itself, for instance, the weights of different time elements ; System Parameters: exogenously given parameters used in the mathematical formulation that are determined by public transport system itself, for instance the costs of operating a bus Output: results of analytical model, for instance, the value of the objective function; Outcome: the total set of criteria used to judge a network design, such as travel time, Figure 2-2 Structure of the Analytical Approach (Source: Van Nes 2000) 13

In his study, the mathematical descriptions of these relationships were formulated and used as building blocks to define objective functions, which are mathematical representations of the formulated objectives. Those objective functions were then optimized with respect to the decision variables stop spacing and line spacing yielding the optimal relationships for these decision variables under certain fixed parameters and a set of constraints. General Structure Based on van Nes (2000) the general structure of the problem description for such an analytical model is as follows: 1) The Decision Variables 2) Objective Function: The main objective function used in literature is minimizing the total costs, either the sum of travel costs and operating costs, or the sum of travel costs, operating costs and capital costs that is investment costs and fleet costs. 3) Problem Constraints (Optional): The use of constraints in analytical models is limited. Capacity and budget constraints are the most commonly used constraints. Solution Techniques Van Nes (2000) furthers explains that there are two solution techniques for the optimization problems, the analytical approach and the numerical approach (enumeration). Table (2-1) shows the advantages and the disadvantages of both approaches Table 2-1 Analytical and Numerical Solutions - Advantages and Disadvantages (Based on Van Nes 2000) Method Advantages Disadvantages Analytical Approach Numerical Approach (enumeration) For each decision variable the optimal relationships with parameters and other decision variables are defined explicitly Can deal with mathematically less tractable objective functions The objective function must be formulated in such a way that is suitable for mathematical analysis Provides less insight into the main relationships of the decision variables Characteristics of the Results Based on Van Nes (2000), the main characteristics found in nearly all studies is that optimal relationships for the decision variables can be described using a square root or cubic route functions. This finding implies that the optimal values have a limited sensitivity with respect to the parameters and the variables used. Doubling the value of decision variables `or of a system parameter, results in an increase of the decision variable of 41% (square root relationship) or 26% (cubic root relationship) at most. Also the objective functions were found to be shallow around the optimum which allows for varying or rounding the values in planning practice, for instance to account for typical characteristics of an urban area, without serious consequences on the design objectives. However, for it was found that due to the square and cubic root relationships, lower values of the decision variables would have more impact on the value of the objective function than higher values. 14

2.1.4. Intermodalism Main Concept In the last two or three decade s an outstanding large increase in traffic congestion, air pollution, pressure on the infrastructure and passengers volumes has occurred. Having a well-designed public transport network that works individually without any coordination with the other modes of public transport was found not to be sufficient. As a result, the concept of intermodalism emerged. Intermodalism refers to a transportation system in which individual modes work together or within their own niches to provide the user with the best choices of service, and in which the consequences on all modes of polices for a single mode are considered (U.S.D.O.T 2000). There are many advantages of having an intermodal public transport system in place such as reducing fuel consumption, air pollution, pressure on the infrastructure and traffic congestion; increasing the accessibility to the infrastructure through better coordination of the scheduling process within the same public transport mode as well as between different modes. An efficient intermodal public transport system should be able to achieve all these benefits and at the same time maintain the attractiveness of the public transport network to all the stakeholders involved. The present research is limited to the transfer coordination problem as one of the intermodal public transport network design problems. The same optimization based analytical approach can be followed in the present research. The following sections provide a detailed description of the transfer coordination problem, main decision variables involved, objective functions, and constraints. A review of previous models in transfer coordination is also conducted with its advantages and shortcomings. 2.2. The Transfer Coordination Problem Transfers play significant role in daily transit operations in terms of ridership, cost-effectiveness and customer satisfaction. Riders usually have a negative perception of transfers because of their inconvenience, which can be thought of as a transfer penalty Understanding what affects transfer penalty can have significant implications for the transit authority. It can help in identifying which type of improvement to the system can most-effectively improve transfers, thus attracting new customers (Guo and Wilson 2004). There are many factors affecting the transfer penalty such as the transfer time, the total trip time, the number of transfer, the comfort of transfers (i.e. Landscape, weather...) and the financial costs of transfers. The level of service of an intermodal transit system is dependent significantly on transfer times (Chowdhury 2000). Indeed the transfer time between public transport modes or within the same mode is the most weighted and appreciated element for passengers when assessing the quality of transfers. Transfer time is the waiting time penalty encountered by passengers at a transfer stop or terminal while changing between public transport lines. The higher the transfer time the higher the passengers inconvenience and the lower the ridership rates. As mentioned in the previous chapter the transfer time can be reduced by increasing the service frequency or in other words decreasing the service headway. The service headway is the difference in time between two subsequent vehicles operating at the same line. Decreasing the service headway might be a suitable design objective from the passenger s point of view but not always cost effective from the operators point of view. Low operating headway, which can substantially reduce transfer time, is not always cost effective due to variations of demand among transit routes over space and time (Chowdhury 2000). Aside from 15