Alan Nicholson

DEGRADABLE TRANSPORTATION SYSTEMS: SENSITIVITY AND RELIABILITY ANALYSIS

This paper describes sensitivity analysis for a degradable transportation system, based on an integrated equilibrium model with elastic travel demand, to identify critical components and assist efforts to improve system reliability. A reliability model, involving practical measures of reliability, is also described. Algorithms for solving the reliability model are discussed.

Degradable transportation systems : An integrated equilibrium model

This paper discusses the need for analysis of transportation systems whose components are subject to degradation, and describes an integrated equilibrium model for a large scale, multi-mode degradable transportation system. The existence, uniqueness and stability of the solutions are discussed. Use of the model, to identify the socio-economic impacts of system degradation, the critical components and system reliability, is also discussed.

Ranking and selecting motor vehicle accident sites by using a hierarchical Bayesian model

Identification, ranking and selecting hazardous traffic accident locations from a group under consideration is a fundamental goal for traffic safety researchers. Few methods exist that can quantitatively, accurately and easily discriminate between sites that commonly have small and variable observation count periods. One method that embodies all these advantages is the hierarchical Bayesian model, the method proposed in this paper. The particular hierarchical Bayesian approach that we use incorporates expert knowledge about accident sites as a group believed a priori to be exchangeable, the Poisson assumption and a conjugate gamma prior. We then propose three natural strategies for ranking and selecting the most hazardous subgroup of accident locations. Also presented is an especially useful procedure that gives the probability that each particular site is worst and by how much it is worst. All proposed strategies are illustrated using previously published fatality accident data from 35 sites in Auckland, New Zealand.

ARE ACCIDENTS POISSON DISTRIBUTED? A STATISTICAL TEST

The common and convenient assumption in accident count analysis, that accidents are Poisson-distributed, is reexamined. Two statistical tests, for evaluating the assumption are described and compared. It is shown that a test based upon a combinatorial analysis is much more accurate than the alternative chi-square test when accident counts are expected to be small. The more accurate test is used to reinterpret data on accident count variability, the results indicating that the Poisson distribution is appropriate for the analysis of accidents at individual sites.

ASSESSING TRANSPORT RELIABILITY: MALEVOLENCE AND USER KNOWLEDGE

Abstract The objective of this paper is to give an overview of various reliability concepts that have been developed in the last decades. The paper first summarises various indicators that have been developed in order to measure the reliability of a network and then looks at techniques to calculate these indicators. The usefulness and limitations of the different indicators is discussed. The paper suggests that there is no single perfect indicator but that the choice of indicator and technique depends on several factors, including the viewpoint of the analyst and the type and range of interventions being considered. In order to assess the impact of incidents the authors propose to distinguish between three types of intervention, namely “benevolent”, “neutral” or random, and “malevolent”. Also discussed is why the provision of up-to-date information to the traveller has a central role to play when trying to minimise the impact of an incident.

DRIVER BEHAVIOUR AT HORIZONTAL CURVES: RISK COMPENSATION AND THE MARGIN OF SAFETY

A study involving unobtrusive observation of drivers at horizontal curves before and after realignment is described. The speeds and path radii adopted by drivers in the curves before and after realignment are compared, as are the levels of side friction demanded by each driver while negotiating the curves before and after realignment. The results reveal substantial variations between drivers (with respect to speed, path radius, and side friction demand) and between the path and curve radii. While vehicle speeds increased markedly, the side friction demand was reduced for all curves except one. It is concluded that the margin of safety was increased for all curves, and this is supported by the accident data.

The randomness of accident counts

Road accident occurrence is generally assumed to be governed by a random process. Experience analysing accident count series indicates a need for testing the randomness of such a series, and a simple statistical test is described. The test is a modified one-sample runs test, which can be used to assist the identification of three distinct patterns constituting non-randomness (namely, a trend, a discontinuity and over-correction). The test is designed for the preliminary analysis of accident count data, and its use is demonstrated, using both artificial and actual accident count series.

Analysis of spatial distributions of accidents

This paper discusses the need for spatial distributions of accidents to be analysed, as an aid to selecting the most appropriate type of accident reduction programme (e.g. site, route and area plans) and assessing the effectiveness of such plans after implementation. It is argued that current practice for assessing spatial distributions of accidents is insufficiently objective, and statistical analysis techniques for spatial data (including quadrat and nearest-neighbour methods) are reviewed. A new classification scheme for spatial distributions is proposed, such that detection of a particular pattern indicates which type of accident reduction programme is likely to be the most effective. The more promising statistical analysis techniques are assessed and implementation of those techniques is discussed.

INTERSECTION ACCIDENT ESTIMATION: THE ROLE OF INTERSECTION LOCATION AND NON=COLLISION FLOWS

This paper reviews models used in practice to relate accidents to traffic flows, with particular emphasis on the appropriateness of the model form and the statistical analysis technique employed for parameter estimation. The development of generalised linear models for predicting individual accident types at intersections in New Zealand is then described. The use of covariate analysis to identify the effect of intersection location, an investigation of the effect of non-collision flows, and the use of the models for predicting intersection accidents in three networks, are also described. It is concluded that generalised linear models for estimating different accident types (based on the conflicting flows) are better than models for estimating total accidents (based on the approach flows), especially when the cost of different accident types is known. It is also found that intersection location affects the number of different accident types, that it is important to consider the interactions between turning flows (to take better account of the mechanisms of accident occurrence), and that non-collision flows are sometimes important. Comparison of the predicted and observed numbers of accidents has shown that there is poor agreement for individual intersections, but fairly good agreement for networks.

RISK EVALUATION AND MANAGEMENT: A ROAD NETWORK RELIABILITY STUDY

Abstract Risk evaluation and management methods are used to assess the reliability of a New Zealand inter-urban road network, which is subject to closures due to snow and ice, earthquakes, volcanic activity and road accidents. Using the probabilities and consequences of closures of various durations, the expected annual costs of closures are determined for each hazard. The benefit-cost ratios for various risk mitigation options are also identified. The importance of considering both the probabilities and consequences of closures is discussed. It is found that a ‘high-frequency, low-consequence’ hazard (snow and ice) has the highest expected annual cost, and higher than for the ‘low-frequency, high-consequence’ hazards (earthquakes and volcanic activity). It is also found that not allowing for elasticity in the demand for travel (e.g. trips being cancelled or postponed because of road closures) leads to inaccurate estimates of the costs of closure. It is concluded that it is important to allow for the behavioural responses of network users when estimating the costs of closures, and that more attention should be given to ‘high-frequency, low-consequence’ hazards, in order to maximise the economic benefits of expenditure on risk mitigation.