TY - GEN
T1 - An infrastructure based congestion detection and avoidance scheme for VANETs
AU - El-Sayed, Hesham
AU - Thandavarayan, Gokulnath
AU - Sankar, Sharmi
AU - Mahmood, Ishtiaque
N1 - Funding Information:
ACKNOWLEDGEMENT This research was supported by the Roadway, Transportation, and Traffic Safety Research Center (RTTSRC) of the United Arab Emirates University (grant number 31R058).
Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/19
Y1 - 2017/7/19
N2 - In urban areas, traffic congestion is a challenging problem which creates many complications to travelers. Unattended congestion in roadways will cause long waiting times and affects individual economy. It also creates environmental issues and affects personal health. In recent years, the development of Vehicular Ad-hoc Network (VANET) provides a promising solutions for handling the congestion in the roadways. In this paper, we adapt a VANET networking model and propose a novel congestion detection and avoidance scheme for urban areas. A light weight histogram model is utilized to compute the congestion for every lane using an infrastructure based system. By computing the probability density function for every lane, the proposed model predicts congestion in advance and the re-routing strategy is initiated on time. For optimizing the re-routing strategy, two different kinds of congestion avoidance scheme are proposed based on static and dynamic modelling. Various scenarios are created in the microscopic simulation environment and the effectiveness of the proposed algorithm is analyzed by measuring the average travel time. The simulation results show that the proposed model detects congestion in priori and initiates reroute strategy effectively.
AB - In urban areas, traffic congestion is a challenging problem which creates many complications to travelers. Unattended congestion in roadways will cause long waiting times and affects individual economy. It also creates environmental issues and affects personal health. In recent years, the development of Vehicular Ad-hoc Network (VANET) provides a promising solutions for handling the congestion in the roadways. In this paper, we adapt a VANET networking model and propose a novel congestion detection and avoidance scheme for urban areas. A light weight histogram model is utilized to compute the congestion for every lane using an infrastructure based system. By computing the probability density function for every lane, the proposed model predicts congestion in advance and the re-routing strategy is initiated on time. For optimizing the re-routing strategy, two different kinds of congestion avoidance scheme are proposed based on static and dynamic modelling. Various scenarios are created in the microscopic simulation environment and the effectiveness of the proposed algorithm is analyzed by measuring the average travel time. The simulation results show that the proposed model detects congestion in priori and initiates reroute strategy effectively.
KW - Congestion Avoidance
KW - Congestion Detection
KW - Histograms
KW - Re-Routing
KW - VANET
UR - http://www.scopus.com/inward/record.url?scp=85027884085&partnerID=8YFLogxK
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U2 - 10.1109/IWCMC.2017.7986428
DO - 10.1109/IWCMC.2017.7986428
M3 - Conference contribution
AN - SCOPUS:85027884085
T3 - 2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017
SP - 1035
EP - 1040
BT - 2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2017
Y2 - 26 June 2017 through 30 June 2017
ER -