Modelling delay saving through pro-active incident management techniques

European Transport Research Review

Original Paper

Philippe Nitsche¹  Viktor Bernhardsson²  Johan Olstam³  Nicholas B. Taylor⁴ 

[1] AIT Austrian Institute of Technology, TECHbase Vienna, Giefinggasse 2, 1210, Vienna, Austria;Swedish National Road and Transport Research Institute (VTI), Olaus Magnus väg 35, SE-581 95, Linköping, Sweden;Swedish National Road and Transport Research Institute (VTI), Olaus Magnus väg 35, SE-581 95, Linköping, Sweden;Department of Science and Technology, Division for Communication and Transport Systems, Linköping University, SE-601 74, Norrköping, Sweden;Transport Research Laboratory (TRL), Crowthorne House, RG40 3GA, Wokingham, UK;

关键词: Traffic incident;    Delay;    Modelling;    Incident management;    Novel technology;    Intelligent transportation systems;   

DOI  :  10.1007/s12544-017-0265-5

 received in 2017-03-08, accepted in 2017-09-05,  发布年份 2017

来源: Springer

【 摘 要 】

PurposeRoad traffic incidents cause delay, affect public safety and the environment. The CEDR PRIMA project aims to extend practical guidance for traffic managers in pro-active Traffic Incident Management (TIM) techniques to reduce the impacts and associated costs of incidents.MethodsThe paper describes modelling methods used in the project for assessing the effect of different management techniques on incident duration and travel delay under various scenarios, including collision, adverse weather, heavy vehicle breakdown and other obstruction, assuming various management strategies and generic impacts of novel technologies. Macroscopic simulations of 178 variations of 13 basic scenarios have been performed using a flexible and computationally efficient macroscopic queue model, results being verified by simulation using a velocity-based Cell Transmission Model (CTM-v).ResultsThe results of the two modelling methods are broadly consistent. While delays estimated by the two methods can differ by up to 20%, this is small compared to the factor of 30 range of modelled delays caused by incidents, depending on their nature and circumstances, and is not sufficient to affect general conclusions. Under the peak traffic conditions assumed, the most important factor affecting delay is whether running lanes can be kept open, but quick clearance of carriageway is not always feasible.ConclusionsComparison of two very different modelling methods confirms their consistency within the context of highly scenario-dependent results, giving confidence in the results. Future research and data needs include further validation of the models, potential application to traffic flow and conflict prediction and incident prevention, and more complete and consistent recording of incident timelines and impacts.

【 授权许可】

CC BY   
© The Author(s) 2017