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BSC Faculty Member's Research into Computer Adaptive Method for Minimizing Traffic Congestion Published by Industrial Engineering Journal

  • Created
    Wednesday, January 25 2012
  • Created by
    Jim Nelson/Media Relations - (304) 327-4103 jnelson@bluefieldstate.edu

bowling shannon(Bluefield)—A Bluefield State College faculty member's collaborative research into vehicles' onboard computers to minimize traffic congestion was published recently by a major industrial engineering journal.

Dr. Shannon Bowling, an Assistant Professor/Electrical Engineering Technology at BSC, and George Arnaout, a graduate student/Department of Engineering Management & Systems Engineering at Old Dominion University, considered the impact of Cooperative Adaptive Cruise Control (CACC) on relieving traffic congestion and improving overall traffic flow. "CACC-equipped vehicles have sensors and communication devices that permit them to communicate with other CACC-equipped vehicles and adjust the speed of each vehicle to an optimal value that will maximize the flow of traffic," Bowling explained.

Their research utilized "agent-based modeling," a process that combines microsimulation and macrosimulation. "There are just a handful of researchers in the world studying the effects of CACC who are applying agent-based modeling—it's the latest modeling paradigm," the BSC faculty member added.

"Most people have little idea what causes traffic jams," he said. "They might think it is probably just a single incident or one driver's error that causes things to stop. Actually, the cause is very complicated and it results from many drivers' actions that get magnified over time. Simply tapping your brakes in a heavily congested zone can cause a traffic jam long after you are gone."

Because of the "real world limitations" of actually injecting CACC vehicles into an actual traffic jam, the researchers created a computer simulation that accurately models the behavior of drivers and also models the behavior of cars equipped with CACC. CACC vehicles react in a traffic jam in a manner that promotes a reduction in congestion and an increase in traffic flow.

"The algorithm is actually trying to simulate the behavior of an older type of transportation vehicle—a train," Bowling continued. "All cars in a train are mechanically linked and, as a result, there is no variance in the speed of each car. It is the speed difference that actually causes a traffic jam. The CACC can create a virtual mechanical link among all the vehicles to reduce variance of speed for each vehicle. This reduces or eliminates traffic congestion."

Their research was featured in the Journal of Industrial Engineering and Management.