Estimating the Safety Effects of Congestion Warning Systems using Carriageway Aggregate Data

Estimating the Safety Effects of Congestion Warning Systems using Carriageway Aggregate Data

van Lint, J.W.C. (TU Delft Transport and Planning)
Nguyen, T.T. (TU Delft Transport and Planning)
Krishnakumari, P.K. (TU Delft Transport and Planning)
Calvert, S.C. (TU Delft Transport and Planning)
Schuurman, Henk (Ministry of Infrastructure and the Environment)
Schreuder, Marco (Ministry of Infrastructure and the Environment)

2020

Is it possible to use just aggregate carriageway data for the evaluation of congestion warning systems (CWS) in large networks—or any system affecting traffic safety for that matter? In this paper, two hypotheses related to this question are tested. The first hypothesis is that it can be done by comparing large-scale congestion patterns on road stretches with and without CWS. The underlying rationale is that heterogeneous congestion patterns with many disturbances, frequent wide moving jams, and large speed differences result in more potentially unsafe traffic conditions than more homogeneous congestion patterns. The second hypothesis is that it is possible to compare differences in average (maximum) deceleration distributions into congestion waves between road stretches with and without CWS. Both hypotheses have been tested for similar bottlenecks with similar demand patterns and the results suggest the first hypothesis must be rejected. Although the idea seems plausible (CWS result in more homogeneous congestion patterns) there were too many confounding factors in the data to make the case. However, persuasive evidence was found for the second hypothesis. Statistically significant differences were found between (maximum) deceleration distributions on road stretches with and without CWS that suggest CWS do—as expected—contribute positively to traffic safety. It thus seems to be possible to monitor safety effects using just average speeds. However, the method is limited to providing relative comparisons. Furthermore, to fully rule out the effects of unobserved factors, more evidence and validation with microscopic data are needed.

http://resolver.tudelft.nl/uuid:053f7b65-1dad-438b-b563-a1112353620b

https://doi.org/10.1177/0361198120945319

2021-02-27

0361-1981

Transportation Research Record, 2674 (11), 278-288

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

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© 2020 J.W.C. van Lint, T.T. Nguyen, P.K. Krishnakumari, S.C. Calvert, Henk Schuurman, Marco Schreuder