Improving traffic management through consideration of uncertainty and stochastics in traffic flow

Improving traffic management through consideration of uncertainty and stochastics in traffic flow

Calvert, S.C. (TU Delft Transport and Planning)
Taale, Henk (TU Delft Transport and Planning; Ministry of Infrastructure and the Environment)
Snelder, M. (TU Delft Transport and Planning; TNO)
Hoogendoorn, S.P. (TU Delft Transport and Planning)

Transport and Planning

2018-03-01

In a bid to cost-effectively tackle congestion, traffic management is often seen as a key option to utilise road capacity. Prior to the application of traffic management measures, a-priori analysis allows the effectiveness of measures to be judged and where necessary adapted. However, current approaches do this without considering the effects of stochastic uncertainty and fluctuations in traffic flow. These stochastic effects have been shown to substantially influence the evaluation of traffic management measures. In this contribution, a methodological framework is proposed and demonstrated in a multi-part case study, applying approaches that explicitly consider stochastic variations and applications for traffic management. The results of the case study demonstrate the effectiveness of the models and highlight the necessity to consider uncertainty and fluctuations when a-priori evaluating traffic management measures.

Homogeneity
Traffic flow
Traffic management
Uncertainty modelling

http://resolver.tudelft.nl/uuid:83b2e436-a573-48d5-91be-722379cea3e0

https://doi.org/10.1016/j.cstp.2018.01.003

2020-03-01

2213-624X

Case Studies on Transport Policy, 6 (1), 81-93

Institutional Repository

journal article

© 2018 S.C. Calvert, Henk Taale, M. Snelder, S.P. Hoogendoorn