Abstract

In-vehicle technologies and cooperative services are attracting a lot of attention for their potential to deal with congestion problems and improve traffic safety. This paper aims to investigate the impact of infrastructure-to-vehicle cooperative systems, case of COOPERS, at the aggregate level, on traffic performance. A factorial experiment is designed with two factors: traffic demand and penetration of the system with three levels each. In total, nine scenarios are investigated. To replicate driving behavior with and without the system, speed distributions from a simulator experiment are used. A motorway section of 4 km is built in VISSIM simulation software. Indicators such as speed, density, delays and travel times are chosen to evaluate and compare the motorway performance with and without the system. The results show that drivers driving with the system activated are more aware and alert to near future traffic conditions compared to driving without the system. Driving with the system activated is characterized by smoother and longer speed decelerations when approaching critical incident/accident events. The results show as well that the factors investigated significantly impact the motorway performance. Congestion reduces the impact of the system whereas higher penetration levels improve traffic operation on the motorway. Future research directions can include (1) investigating the impact of the system at the micro level such as lane changing or car-following behaviors; (2) levels of compliance with the system, which is an important aspect as well.


Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.2495/ut140361
https://www.witpress.com/Secure/elibrary/papers/UT14/UT14036FU1.pdf,
http://www.diva-portal.org/smash/record.jsf?pid=diva2:818367,
https://trid.trb.org/view.aspx?id=1315625,
https://academic.microsoft.com/#/detail/2092389658
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Document information

Published on 01/01/2014

Volume 2014, 2014
DOI: 10.2495/ut140361
Licence: CC BY-NC-SA license

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