By Topic

A Fixed Sensor-Based Intersection Collision Warning System in Vulnerable Line-of-Sight and/or Traffic-Violation-Prone Environment

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
$33 $13
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

3 Author(s)
Jeong-Ah Jang ; Electronics and Telecommunications Research Institute, Daejeon, Korea ; Keechoo Choi ; Hanbyeog Cho

This paper proposes a cooperative intersection collision warning system (CICWS) model that uses fixed traffic sensors to provide warning information to drivers at unsignalized intersections in a real-time manner. The CICWS model is useful for vulnerable line-of-sight and/or traffic-violation-prone environment since it determines whether the situation is really dangerous or not. More specifically, the model is for unsignalized intersections without STOP/YIELD signs, where drivers do not tend to stop. The situation forecast model uses vehicle location, speed, and time data obtained from multiple sensors located at intersection approaches, together with obstacle position and sight distance relationship. More specifically, the model has a real-time sight-distance triangle module and a collision-time prediction module. Using a microtraffic simulator called VISSIM, the validation and evaluation of the model are performed based on different scenarios with different parameters, such as inflow volume, locations of traffic sensors, design speed, and obstacle placement. The results show that the model successfully forecasts dangerous situations up to 94.3%, which may imply the deployment of the model in such an environment where vehicle-to-infrastructure (V2I) or vehicle-to-vehicle (V2V) communication are possible. Some limitations and a future research agenda have also been discussed.

Published in:

IEEE Transactions on Intelligent Transportation Systems  (Volume:13 ,  Issue: 4 )