International Journal of Computational Intelligence Systems

Volume 4, Issue 6, December 2011, Pages 1122 - 1130

Assessment of Expressway Traffic Safety Using Gaussian Mixture Model based on Time to Collision

Authors
Sheng Jin, Xiaobo Qu, Dianhai Wang
Corresponding Author
Sheng Jin
Received 6 July 2011, Accepted 25 November 2011, Available Online 1 December 2011.
DOI
10.2991/ijcis.2011.4.6.4How to use a DOI?
Keywords
Time to collision, Gaussian mixture model, Expressway traffic safety.
Abstract

Traffic safety is of great significance, especially in urban expressway where traffic volume is large and traffic conflicts are highlighted. It is thus important to develop a methodology that is able to assess traffic safety. In this paper, we first analyze the time to collision (TTC) samples from traffic videos collected from Beijing expressway with different locations, lanes, and traffic conditions. Accordingly, some basic descriptive statistics of 5 locations' TTC samples are shown, and it is concluded that Gaussian mixture model (GMM) distribution is the best-fitted distribution to TTC samples based on K-S goodness of fit tests. Using GMM distribution, TTC samples can be divided into three categories: dangerous situations, relative safe situations, and absolute safe situations, respectively. We then proceeds to introduce a novel concept of the percentage of serious traffic conflicts as the percentage of TTC samples below a predetermined threshold value in dangerous situation. After that, assessment results of expressway traffic safety are presented using the proposed traffic safety indictor. The results imply that traffic safety on the weaving segment is lower than that on mainlines and the percentage of serious traffic conflicts on median lane is larger than that on middle lane and shoulder lane.

Copyright
© 2011, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
4 - 6
Pages
1122 - 1130
Publication Date
2011/12/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.2011.4.6.4How to use a DOI?
Copyright
© 2011, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Sheng Jin
AU  - Xiaobo Qu
AU  - Dianhai Wang
PY  - 2011
DA  - 2011/12/01
TI  - Assessment of Expressway Traffic Safety Using Gaussian Mixture Model based on Time to Collision
JO  - International Journal of Computational Intelligence Systems
SP  - 1122
EP  - 1130
VL  - 4
IS  - 6
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2011.4.6.4
DO  - 10.2991/ijcis.2011.4.6.4
ID  - Jin2011
ER  -