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  4. Ride the Tide of Traffic Conditions: Opportunistic Driving Improves Energy Efficiency of Timely Truck Transportation
 
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research article

Ride the Tide of Traffic Conditions: Opportunistic Driving Improves Energy Efficiency of Timely Truck Transportation

Xu, Wenjie  
•
Liu, Qingyu
•
Chen, Minghua
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February 22, 2023
Ieee Transactions On Intelligent Transportation Systems

We study the problem of minimizing fuel consumption of a heavy-duty truck traveling across the national highway network subject to a hard deadline. We focus on a real-world setting that traversing a road segment is subject to variable speed ranges due to dynamic traffic conditions. The consideration of dynamic traffic conditions not only differentiates our work from existing ones but also allows us to leverage opportunistic driving to improve fuel efficiency. The idea is for the truck to strategically wait (e.g., at highway rest areas) for benign traffic conditions, so as to traverse subsequent road segments at favorable speeds for saving fuel. We observe that traffic conditions and thus speed ranges are mostly stationary within certain duration of the day, and we term them as phases. We formulate the fuel consumption minimization problem under phased speed ranges, considering path planning, speed planning, and opportunistic driving. We prove that the problem is NP-hard, and develop a dual-subgradient algorithm for large-/national-scale instances. We characterize conditions under which the algorithm generates an optimal solution. We carry out simulations based on real-world traces over the US highway system. The results show that our scheme saves up to $20%$ fuel than a shortest-path based alternative, of which opportunistic driving contributes $13%$ . Meanwhile, opportunistic driving also reduces driving time by $6%$ as compared to only optimizing path planning and speed planning. As such, it offers a desirable design option to simultaneously reduce fuel consumption and hours of driving. Last but not least, our results highlight a perhaps surprising observation that dynamic traffic conditions can be exploited to achieve fuel savings even larger than those under stationary traffic conditions.

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Type
research article
DOI
10.1109/TITS.2023.3244757
Web of Science ID

WOS:000940204500001

Author(s)
Xu, Wenjie  
•
Liu, Qingyu
•
Chen, Minghua
•
Zeng, Haibo
Date Issued

2023-02-22

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Published in
Ieee Transactions On Intelligent Transportation Systems
Subjects

Engineering, Civil

•

Engineering, Electrical & Electronic

•

Transportation Science & Technology

•

Engineering

•

Transportation

•

energy-efficient transportation

•

timely transportation

•

opportunistic driving

•

dynamic traffic conditions

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variable speed ranges

•

vehicle fuel consumption

•

cruise control

•

emissions

•

path

•

optimization

•

algorithm

Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LA3  
Available on Infoscience
March 27, 2023
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/196496
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