Maurice Aron

Effectiveness of travel time reliability indicators in the light of the assessment of dynamic managed lane strategy

ABSTRACT The aim of traffic management is to ensure a high quality of service for a maximum number of users by decreasing congestion and increasing safety. Uncertainty of travel times decreases the quality of service and leads end users to modify their plans regardless of the average travel time. Indicators describing travel time reliability are being developed and should be used in the future both for the optimization and for the assessment of active traffic management operations. This article discusses the efficiency of certain reliability indicators in an ex-post assessment of a traffic management strategy. Ex-post assessment is based on an observational before–after study. As some factors other than the studied management strategy may intervene between the two periods, and as most reliability indicators require knowledge of the full travel time distribution and not only its average, a methodology is developed for the identification of the impact of these exogenous factors on the whole distribution. Many reliability indicators are split into different parts allowing the identification of the part due to the management strategy impact. The methodology is tested numerically on a managed lane operation consisting of Hard Shoulder Running (HSR) at rush hour on a section of a French motorway. The variation of some reliability indicators appears misleading, whereas the splitting of the indicators increases our understanding of the strategy and highlights its impact. The paper gives the reliability assessment of the HSR field test and discusses different reliability indicators to identify their potential performances and shortcomings.

Power and Exponential Functions Relating Accidents to Traffic and Rain. Calibration on a French Network

Relations between the occurrence of road accidents, traffic and rainfall conditions are valuable in setting safety objectives for traffic management, and in assessing the safety impacts of new traffic management systems, prior to their implementation. Based on traffic, road accidents and rain data collected over one year, on a French urban motorway network, a set of safety performance functions were estimated; each of them provides the accident risk per vehicle-kilometer for a certain type of accident, according to the occurrence of rain, and to the level of a traffic variable (average speed, occupancy, percentage of tailgating…). Analyses were carried out separately by lane and for two types of accidents: single-vehicle accidents and multiple-vehicle accidents. The relationships, although statistically significant, have yet to be validated by the treatment of another set of accidents.

Some Bias in Road Safety Evaluation in Before/After Studies

New traffic management schemes – variable speed control, managed lane operations as Hard Shoulder Running, tidal flow, dedicated bus or taxis lane are nowadays developing. Their impact on traffic safety can be computed by means of Before/After studies. In these studies, the counts of accidents which occurred in the period after and in the period before the implementation of the new scheme are examined. As some contributing factors to accidents might have changed between before and after periods - due to the general safety policy, the betterment of vehicles or of the road, it is important to identify the impact of these changes on the accident number, in order not to confound this impact (called the “time effect”) with the one of the new scheme; this time effect is identified on a “reference” site as the difference between the accident risks between the before and the after period on this reference site. There is an implicit assumption that there are no or no important structural differences between the reference and the assessed sites (in terms of infrastructure, traffic, external conditions). If it is not the case, and if the time effect varies according to the elements of the infrastructure or of the traffic patterns, the “average” time effect computed on the reference site cannot be directly used on the assessed site, due to a bias. This bias is mitigated by splitting the reference site and its traffic into traffic scenarios or into infrastructure scenarios, and by computing the time effect on each element; then those time effects are used, with the appropriate weights, on the assessed site. The impact of this breakdown on the variance of the estimation is provided. A numerical application, for a French managed lane operation, is given to illustrate the interest of the method in road safety assessment.

A non dynamic model for ITS assessment

One of the elements of ITS assessment is the comparison of actual traffic conditions (after ITS has been installed) and traffic conditions which would have occurred, had no change happened. Apart from traffic simulation, which is the most appropriate tool to predict traffic conditions in the case of saturation by virtue of the dynamic (in time and space) equations included, a data driven traffic model is a credible alternative, particularly when congestion is not the core of the problem and when the closeness to initial data is important to compare indicators. Such a tool is outlined here, with its advantages and drawbacks. A very limited numerical application is given. Lines of future research to develop the model are proposed.

Time Headway on French Rural Roads

Abstract This paper presents some empirical time headways observed on rural roads in France, and proposes a model relating the time gaps to the traffic flow, to the percentage of long vehicles, to the number of lanes; the influence of the period of the day is discussed. The parameters of the models characterise either the random arrivals, or the drivers behaviour. Their evolution in the future will show how the new French legislation on time gaps (to drive at a minimum threshold of two seconds) is respected.

Using Operational Research and Advanced Informatics for Classifying: Application for Road Accidents

Abstract This paper presents a method for combining different sources of information - data file, expert knowledge, statistics, additional (possibly imprecise) information brought by the user- in order to classify an event (say a road accident) in predefined classes, which could be required before action. The interest of operational research algorithms, aiming at helping the operator is stressed. The application of the software “CRlQUE” on 35 road accidents is assessed.