Cited 0 time in webofscience Cited 0 time in scopus

Toward Mitigating Phantom Jam Using Vehicle-to-Vehicle Communication

Title
Toward Mitigating Phantom Jam Using Vehicle-to-Vehicle Communication
Authors
Won, MyounggyuPark, TaejoonSon, Sang H.
DGIST Authors
Son, Sang H.
Issue Date
2017-05
Citation
IEEE Transactions on Intelligent Transportation Systems, 18(5), 1313-1324
Type
Article
Article Type
Article
Keywords
3 Phase Traffic TheoryAdaptive Cruise ControlCongestionDetection AlgorithmFlowFuzzy InferenceFuzzy Inference SystemsImpactInference EnginesIntelligent SystemsIntelligent Transportation Systems (ITS)Mobile Telecommunication SystemsModelMotor TransportationPhantom JamsSignal ControlSimulationState of the Art ApproachStop and Go TrafficStreet Traffic ControlSystemsTerms Intelligent Transportation SystemsThree Phase Traffic TheoriesThree Phase Traffic TheoryTraffic CongestionTraffic ControlTraffic JamsTraffic JamsTransportationTravel TimeTunnelVehicle to Vehicle (V2V) CommunicationVehicle Actuated SignalsVehicle to Vehicle (V2V) CommunicationsVehicles
ISSN
1524-9050
Abstract
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.
URI
http://hdl.handle.net/20.500.11750/4184
DOI
10.1109/TITS.2016.2605925
Publisher
Institute of Electrical and Electronics Engineers Inc.
Related Researcher
  • Author Son, Sang Hyuk RTCPS(Real-Time Cyber-Physical Systems Research) Lab
  • Research Interests
Files:
There are no files associated with this item.
Collection:
ETC1. Journal Articles


qrcode mendeley

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE