TY - GEN
T1 - Speed Trajectory Optimization for a Heavy-Duty Truck Traversing Multiple Signalized Intersections
T2 - 2nd IEEE Conference on Control Technology and Applications, CCTA 2018
AU - Rodriguez, Manuel
AU - Fathy, Hosam
N1 - Funding Information:
This work was funded by the ARPA-E NEXTCAR program. The authors gratefully acknowledge this support.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/26
Y1 - 2018/10/26
N2 - This paper explores the fuel savings that can be achieved by optimizing the speed trajectory of a heavy-duty truck traversing a sequence of intersections, under the assumptions that the behavior of the leading traffic and the timing of the traffic lights is known. Specifically, we look at the impact of corridor topology (i.e. green cycle lengths, phase offsets) on the expected fuel savings of the optimized trajectories. This is an important area of research because vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) technology has the potential to allow autonomous vehicles to reduce fuel consumption, especially in urban and sub-urban driving scenarios. The literature tackles the problem of arterial corridor trajectory optimization, and shows the potential fuel saving benefits. However, previous research focuses primarily on passenger vehicles, and often limits its findings to specific case studies. The main contribution of this paper is to offer an estimate of the fuel saving potential - for heavy-duty trucks and under different corridor characteristics - of optimizing trajectories in an urban arterial with V2V and V21 capabilities.
AB - This paper explores the fuel savings that can be achieved by optimizing the speed trajectory of a heavy-duty truck traversing a sequence of intersections, under the assumptions that the behavior of the leading traffic and the timing of the traffic lights is known. Specifically, we look at the impact of corridor topology (i.e. green cycle lengths, phase offsets) on the expected fuel savings of the optimized trajectories. This is an important area of research because vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) technology has the potential to allow autonomous vehicles to reduce fuel consumption, especially in urban and sub-urban driving scenarios. The literature tackles the problem of arterial corridor trajectory optimization, and shows the potential fuel saving benefits. However, previous research focuses primarily on passenger vehicles, and often limits its findings to specific case studies. The main contribution of this paper is to offer an estimate of the fuel saving potential - for heavy-duty trucks and under different corridor characteristics - of optimizing trajectories in an urban arterial with V2V and V21 capabilities.
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U2 - 10.1109/CCTA.2018.8511446
DO - 10.1109/CCTA.2018.8511446
M3 - Conference contribution
AN - SCOPUS:85056844626
T3 - 2018 IEEE Conference on Control Technology and Applications, CCTA 2018
SP - 1454
EP - 1459
BT - 2018 IEEE Conference on Control Technology and Applications, CCTA 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 21 August 2018 through 24 August 2018
ER -