Cited 0 time in
Cited 0 time in
Toward Mitigating Phantom Jam Using Vehicle-to-Vehicle Communication
- Toward Mitigating Phantom Jam Using Vehicle-to-Vehicle Communication
- Won, Myounggyu; Park, Taejoon; Son, Sang H.
- DGIST Authors
- Son, Sang H.
- Issue Date
- IEEE Transactions on Intelligent Transportation Systems, 18(5), 1313-1324
- Article Type
- 3 Phase Traffic Theory; Adaptive Cruise Control; Congestion; Detection Algorithm; Flow; Fuzzy Inference; Fuzzy Inference Systems; Impact; Inference Engines; Intelligent Systems; Intelligent Transportation Systems (ITS); Mobile Telecommunication Systems; Model; Motor Transportation; Phantom Jams; Signal Control; Simulation; State of the Art Approach; Stop and Go Traffic; Street Traffic Control; Systems; Terms Intelligent Transportation Systems; Three Phase Traffic Theories; Three Phase Traffic Theory; Traffic Congestion; Traffic Control; Traffic Jams; Traffic Jams; Transportation; Travel Time; Tunnel; Vehicle to Vehicle (V2V) Communication; Vehicle Actuated Signals; Vehicle to Vehicle (V2V) Communications; Vehicles
- Traffic jams often occur without any obvious reasons such as traffic accidents, roadwork, or closed lanes. Under moderate to high traffic density, minor perturbations to traffic flow (e.g., a strong braking motion) are easily amplified into a wave of stop-and-go traffic. This is known as a phantom jam. In this paper, we aim to mitigate phantom jams leveraging the three-phase traffic theory and vehicle-to-vehicle (V2V) communication. More specifically, an efficient phantom jam control protocol is proposed in which a fuzzy inference system is integrated with a V2V-based phantom jam detection algorithm to effectively capture the dynamics of traffic jams. Per-lane speed difference under traffic congestion is taken into account in the protocol design, so that a phantom jam is controlled separately for each lane, improving the performance of the proposed protocol. We implemented the protocol in the Jist/SWAN traffic simulator. Simulations with artificially generated traffic data and real-world traffic data collected from vehicle loop detectors on Interstate 880, California, USA, demonstrate that our approach has by up to 9% and 4.9% smaller average travel times (at penetration rates of 10%) compared with a state-of-the-art approach, respectively. © 2017 IEEE.
- Institute of Electrical and Electronics Engineers Inc.
- Related Researcher
Son, Sang Hyuk
RTCPS(Real-Time Cyber-Physical Systems Research) Lab
There are no files associated with this item.
- ETC1. Journal Articles
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.