Modelling traffic incidents to support dynamic bus fleets management for sustainable transport

Abstract

The continuous implementation of highly technological functions and specifically intelligent transport systems in public transport highlights the need of highly efficient, accurate and reliable bus operations network. Intelligent transport systems can support a variety of functions, including dynamic bus fleet management which has yet to be established in most bus fleets in the UK in a systematic way. In order to support dynamic bus fleet management by detecting the fundamental role of bus and traffic incidents in bus-based public transport, a microscopic simulation model capable of modelling the impact of the individual incidents? characteristics on bus operations has been developed and applied to a variety of scenarios.

This research draws on a review of existing literature on bus fleet management and available computer software in this field. It investigates research gaps in modelling the impact of traffic incidents on overall bus performance; it describes the design and development of the new simulation model, SIBUFEM (Simulating Incidents for Bus Fleet Management) for modelling bus operations during whole day periods in which incidents of different types can occur. The model simulates a high frequency bus service using existing field data and incorporates the continuous circulation of buses along the bus route. It uses journey time profiles, passenger-dependent bus stop dwell times and deterministic time-dependent queuing theory to model traffic incidents and the impact of their characteristics on the bus performance parameters.

The model results, presented in this thesis, focus on performance measures including but not limited to bus journey times, passenger waiting times and bus delays resulting from various bus and traffic incidents. Incidents vary from bus breakdowns, to traffic incidents such as road-works, traffic accidents, burst water mains, disabled vehicles and illegal parking; in SIBUFEM they are specified in terms of their location, duration and severity (i.e. loss of capacity). The model has been applied to a main bus corridor in Southampton, UK, with a base case of „normal? operations established, for comparison with results from 24 different incident scenarios, and using key model performance parameters of average bus journey time, bus speed and excess waiting time.

This PhD demonstrates the functionality of SIBUFEM with model results demonstrating the extent to which passenger waiting times increase with increasing incident severity and duration. The overall comparison of the simulation results showed that the more severe the level of severity or the longer the duration of an incident, the higher the expected impact of the event on the overall bus performance was. In terms of the incident location parameter, the effect is greater when the incident occurs in the middle of the bus route than when it occurs at the end. The effect of incident location is especially evident in the case of traffic incidents such as roadworks, traffic accidents and illegal parking. Findings from this research also demonstrated that these incidents are usually more severely affected by a change in an incident parameter than by bus breakdown incidents. The thesis concludes with a discussion on potential dynamic bus fleet management strategies and how SIBUFEM can be further developed to allow these strategies to be evaluated.

SIBUFEM is capable of modelling traffic incidents to support dynamic bus fleet management and, thus, encourage the use of intelligent transport systems applications in bus operations. This offers great potential in the field of bus-based public transport as part of a guidance tool for bus operators, as well as the way to increase bus level service thereby increasing customer satisfaction and thus the development of a sustainable transport system.

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Identifiers

ORCID for P.J. Shaw: orcid.org/0000-0003-0925-5010

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