By Topic

Modelling drivers' en-route diversion behaviour under variable message sign messages using real detected traffic data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Xu, T.D. ; Inst. of Transp. Eng., Zhejiang Univ., Hangzhou, China ; Sun, L.J. ; Peng, Z.R. ; Hao, Y.

The study aims to develop a new method suitable for analysing en-route diversion behaviour. A corresponding probit model is used to analyse and quantify the impact of various variable message sign (VMS) messages and other factors involved in traffic diversion based on real-time detected traffic data in Shanghai, China. Traffic data from loop detectors, used since 2003, and vehicle license plate readers, used since 2008, are used to analyse the impact of VMS messages on the drivers' en-route diversion behaviour and develop an aggregated en-route diversion behaviour model. The results indicate that drivers are more sensitive to travel time information than traffic congestion information. Therefore drivers will benefit if they will be able to choose the right route if information suggesting alternate routes is provided and neighbouring VMSes are coordinated. Moreover, time factors, off-ramp conditions and visibility of downstream congestion significantly influence en-route diversion behaviour, which can elucidate the significant difference between the result from en-route diversion behaviour model based on stated preference survey and the real traffic system.

Published in:

Intelligent Transport Systems, IET  (Volume:5 ,  Issue: 4 )