Predictive road safety impact assessment of traffic management policies and measures

Autor: Niv Eden, A. Tsakarestos, Pierre Schmitz, Peng Liu, Susanna Hauptmann, Suzanne Hoadley, Ioannis Kaparias
Rok vydání: 2020
Předmět:
Zdroj: Case Studies on Transport Policy. 8:508-516
ISSN: 2213-624X
DOI: 10.1016/j.cstp.2019.11.004
Popis: In recent research the CONDUITS performance evaluation framework for traffic management and Intelligent Transport Systems (ITS) was developed, consisting of a set of Key Performance Indicators (KPIs) for the strategic themes of traffic efficiency, safety, pollution reduction and social inclusion. Follow-up work has concentrated on integrating the developed CONDUITS KPIs with microscopic traffic simulation. The outcome has been a predictive evaluation tool for traffic management and ITS, called CONDUITS_DST, in which two of the four KPI categories have been integrated previously: pollution and traffic efficiency. The objective of the present study is to further extend the predictive evaluation framework to include the theme of traffic safety. Contributing to the development of the CONDUITS_DST traffic safety module, the paper identifies and proposes relevant models and metrics linking traffic characteristics with road safety impacts. In doing so, it enables the extraction of the necessary input data for each of the three CONDUITS KPIs for traffic safety (accidents, direct impacts, and indirect impacts) directly from microscopic traffic simulation models. The proposed models and metrics are tested in conjunction with the relevant CONDUITS KPIs for safety using data from simulation models before and after the implementation of a bus priority signalling system in Brussels. Testing takes place both at the network level, but also at the level of individual links, and the results show that the framework is able to capture the expected safety impacts adequately well, paving the way towards its implementation is the traffic safety module of CONDUITS_DST.
Databáze: OpenAIRE
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