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

Analysing improvements to on-street public transport systems: a mesoscopic model approach

“…It is reasonable to describe reliability in terms of distributions (Ceder 2007), hence measuring reliability in statistical terms. The mean, variation and coefficient of variation are therefore useful measures for the degree of variation of the operation.…”

“…hour, day, week, season), number of passengers, and the habits of the individual driver (Ceder 2007). In traditional traffic assignment models the travel time on links can be estimated according to traffic flow theory (Ortúzar and Willumsen 2011).…”

“…When all passengers board and alight through the same door the dwell time can be estimated by a linear model of the form (Ceder 2007):…”

“…For vehicles with multiple doors where boarding and alighting passengers use different doors the dwell time can be calculated as (Ceder 2007):…”

Planning Public Transport Networks—The Neglected Influence of Topography

“…These include efficiency and optimization of resources such as vehicles and crew and can determine the minimum and maximum lengths of routes, and location of termini and interchanges. For instance, Ceder (2007) identifies the importance of vehicle scheduling, timetabling, and crew rostering and the interactions between these elements. These requirements also have an influence on patronage through their impacts on service reliability and customeroriented timetables such as memory headways.…”