Public Transit Planning and Operation

Abstract

Preface xiii Chapter 1 Introduction to Transit Service Planning 1.1 Motivation 1.2 The operational planning decomposition process 1.3 Service and evaluation standards and their derivatives 1.4 Viability perspectives 1.5 Outline of other chapters References Chapter 2 Data Requirements and Collection 2.1 Introduction 2.2 Data-collection techniques 2.3 Data requirements 2.4 Basic statistical tools 2.5 Literature review and further reading References Chapter 3 Frequency and Headway Determination 3.1 Introduction 3.2 Max load (point check) methods 3.3 Load profile (ride check) methods 3.4 Criterion for selecting point check or ride check 3.5 Conclusion (two examples) 3.6 Literature review and further reading Exercises References Chapter 4 Timetable Development 4.1 Introduction 4.2 Objectives, optional timetables and comparison measures 4.3 Even headways with smooth transitions 4.4 Headways with even average loads 4.5 Automation, test runs and conclusion 4.6 Literature review and further reading Exercises References Chapter 5 Advanced Timetables I: Maximum Passenger Load 5.1 Introduction 5.2 Even max load on individual vehicles 5.3 Optimization, operations research and complexity 5.4 Minimum passenger-crowding timetables for a fixed vehicle fleet Exercise References Chapter 6 Advanced Timetables II: Maximum Synchronization 6.1 Introduction 6.2 Formulating an OR model for synchronization 6.3 The Synchro-1 Procedure 6.4 The Synchro-2 Procedure 6.5 Examples 6.6 Literature review and further reading Exercises References Chapter 7 Vehicle Scheduling I: Fixed Schedules 7.1 Introduction 7.2 Fleet size required for a single route 7.3 Example of an exact solution for multi-route vehicle scheduling 7.4 Max-flow technique for fixed vehicle scheduling 7.5 Deficit-function model with deadheading trip insertion 7.6 Depot-constrained vehicle scheduling 7.7 Literature review and further reading Exercises References Appendix 7.A: The maximum-flow (max-flow) problem Chapter 8 Vehicle Scheduling II: Variable Schedules 8.1 Introduction 8.2 Fleet-size lower bound for fixed schedules 8.3 Variable trip-departure times 8.4 Fleet-size lower bound for variable schedules 8.5 Fleet-reduction procedures 8.6 Experiences with bus schedules 8.7 Examination and consideration of even-load timetables Exercises References Appendix 8.A: Deficit-function software vi Contents Chapter 9 Vehicle-type and Size Considerations in Vehicle Scheduling 9.1 Introduction 9.2 Optimization framework 9.3 Procedure for vehicle scheduling by vehicle type 9.4 Examples 9.5 Vehicle-size determination 9.6 Optimal transit-vehicle size: literature review Exercises References Chapter 10 Crew Scheduling

Integrated Optimization of Bus Line Fare and Operational Strategies Using Elastic Demand

“…According to Figure 4(a), some of the pairs which have achieved high service levels can be identified. For instance, the fare for pair (2, 16) is higher than that for pair (2,17) in Figure 4(a), though its travel distance is shorter than for pair (2,17). This is adequate explanation that pair (2,16) needs to be offered a high service level.…”

“…For instance, the fare for pair (2, 16) is higher than that for pair (2,17) in Figure 4(a), though its travel distance is shorter than for pair (2,17). This is adequate explanation that pair (2,16) needs to be offered a high service level. Interestingly, Figure 5 indicates that O-D pairs located in those areas with difference values between their two fares beyond $0 must be offered high quality service in the transit system which considers the use of strategies.…”

“…An efficient transit system matches the complex relationship between supply and demand from the users' and operators' perspectives [1,2]. Users pursue better service while the operator attempts to maximize operating profit.…”

“…Aside from the fact that the increased number of private cars could obviously not efficiently cover these increasing trips, they generate urban concerns such as traffic congestion and air pollution, as well as health and safety problems, and so on. Compared with the performances of private cars, public transit clearly can perform in an environmentally friendly, efficient, and sustainable manner [1,2]. However, in practice, full advantage is not always taken of public transit resources to meet such increasing and imbalanced travel demand, due to the fact that a common full route operation strategy is provided.…”

Reverse $k$ Nearest Neighbor Search over Trajectories

“…(ii) Furthermore, by taking the temporal factor into consideration, i.e., user transitions at different time periods, it can help further adjust the frequency of planned vehicles on the planned routes, in order to save running cost for either individual vehicle drivers or public transportation authority [5].…”