Modelling and evaluation of reliability impacts in road networks: concepts and methods for traffic assignment models

In the last decade, there has been a strongly growing interest in measuring, modelling and predicting road network reliability, with major initiatives underway in the UK, Netherlands, US and Japan. A state-of-the-art review of the techniques now available is provided, to explain and illustrate their scope with simple examples, and to consider the extent to which theyare currently implementable with existing network assignment packages. Infact, the field of 'network reliability' has provided a diverse range of techniques, aimed at several different kinds of problem and application. Acommon theme running through such techniques has been the natural representation of (stochastic) uncertainty in the level of service provided by the network to the travellers using it, yet one may identify at least five classes of method that have arisen: (a) Connectivity reliability methods, whereby each link is assigned a failure probability and the objective to compute the probability of an origin-destination (O-D) movement being connected; (b) Travel time reliability methods, which explore the probability distribution of O-D or network performance measures under variations in the travel times, O-D matrix and/or link capacities; (c) Capacity reliability methods, where the aim is to determine the range or distribution of O-D demands that allow the capacity to function within its capacity, according to some given probability; (d) Behavioural reliability methods, whereby theeffect on mean network performance and/or economic appraisal measures is represented of drivers' behavioural choice response to travel time variability; (e) Potential reliability methods, based on identifying vulnerable elements of a network under pessimistic assumptions. Methods in classes (a)-(c), and to some extent (e), are similar in the sense that they are directly concerned with examining extreme, unusual or undesirable performance: from the point of view of a 'network manager' wishing to ensure a certain minimum level of service they therefore hold some considerable interest. For example, a city authority may adopt them to plan for, say, the impact of extreme weather events or just the normal effect of daily variation in demand. A similar applicability arises on an inter-urban level; and interestingly such example in the UK is the Public Service Agreement Target that has been set for the Highways Agency, in maintaining a stable level of service for the worst 10% of journeys. On the other hand, the methods in class (d) have attracted greater interest from those wishing to appraise the potential benefits of schemes that may improve reliability. In such cases, the interest is not so much in planning for unusual/extreme events but forlong-run average conditions. The difference comes in the fact that the travellers in the transport system (rather than the planner) are assumed to form their own views regarding unreliable or variable performance, and then this affects their mean behaviour. This pragmatic approach is convenientin that it allows us to make minimal changes to conventional economic appraisal methods. Through simple examples, the rationale and methodology behind these classes of method is explained. Where available, practical methods are described for resolving problems concerned with estimating performance distributions over stochastic networks (relevant to (a)-(c)), or for representing traffic assignment with variable or risky alternatives in the case of (d). For the covering abstract see ITRD E145999

Language

  • English

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 01220326
  • Record Type: Publication
  • Source Agency: TRL
  • Files: ITRD
  • Created Date: Oct 27 2010 10:06AM