TY - GEN
T1 - CoDrive
T2 - 9th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2018
AU - Zhao, Yiran
AU - Yao, Shuochao
AU - Shao, Huajie
AU - Abdelzaher, Tarek
N1 - Funding Information:
This work was supported in part by NSF grants CNS 16-18627, CNS 13-20209, CNS 13-29886 and CNS 13-45266.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/21
Y1 - 2018/8/21
N2 - This paper presents the design and evaluation of CoDrive, a cooperative speed advice system aiming at vehicular fuel savings by reconciling speeds of different vehicles with the timing of signalized intersections. Existing systems for speed coordination and platoon management primarily focus on safety, stability, and security issues. In the authors' own prior work, speed optimizations are discussed for minimizing fuel consumption by exploiting signalized intersection timing. In this paper, we recognize that vehicles whose paths diverge after the next intersection have different fuel-optimal speeds. Since slower vehicles will block faster ones from meeting their optimal speed in heavy traffic or on single-lane roads, we develop an algorithm for speed re-negotiation that arrives at a compromise speed for all vehicles involved. The resulting cooperative speed advice scheme minimizes the total fuel consumption of the involved vehicles, leading to a global optimum. An accounting scheme offers incentives that compensate for resulting inequity in savings distribution across individual vehicles. For evaluation, we use the SUMO simulator. We show that our cooperative scheme saves up to 38.2% in fuel over the baseline where no speed advice is provided, and saves up to 7.9% over prior work GreenDrive.
AB - This paper presents the design and evaluation of CoDrive, a cooperative speed advice system aiming at vehicular fuel savings by reconciling speeds of different vehicles with the timing of signalized intersections. Existing systems for speed coordination and platoon management primarily focus on safety, stability, and security issues. In the authors' own prior work, speed optimizations are discussed for minimizing fuel consumption by exploiting signalized intersection timing. In this paper, we recognize that vehicles whose paths diverge after the next intersection have different fuel-optimal speeds. Since slower vehicles will block faster ones from meeting their optimal speed in heavy traffic or on single-lane roads, we develop an algorithm for speed re-negotiation that arrives at a compromise speed for all vehicles involved. The resulting cooperative speed advice scheme minimizes the total fuel consumption of the involved vehicles, leading to a global optimum. An accounting scheme offers incentives that compensate for resulting inequity in savings distribution across individual vehicles. For evaluation, we use the SUMO simulator. We show that our cooperative scheme saves up to 38.2% in fuel over the baseline where no speed advice is provided, and saves up to 7.9% over prior work GreenDrive.
KW - Cooperative driving
KW - fuel consumption model
KW - fuel saving
KW - traffic signal timing
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U2 - 10.1109/ICCPS.2018.00037
DO - 10.1109/ICCPS.2018.00037
M3 - Conference contribution
AN - SCOPUS:85053494993
SN - 9781538653012
T3 - Proceedings - 9th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2018
SP - 308
EP - 319
BT - Proceedings - 9th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 11 April 2018 through 13 April 2018
ER -