Abstract
Truck platooning has several benefits over traditional truck mobility. Platooning improves safety and reduces fuel consumption up to 15%, depending on platoon configuration. Although platooning benefits are quantifiable, platooning routes are not identified. Many factors are relevant to identifying these routes. For efficient platooning, a truck platoon needs to travel at a constant high speed for an extended distance. In addition, platoon integrity should be preserved from interfering vehicles and frequent ramps that may compromise the robustness and safety of the operation. This study presents an easy to implement approach to determine platoonable routes based on platoon configuration, speed, roadway volume/capacity, and number of highway exit and entry conflicts. Based on this approach, each roadway section is assigned a level of platoonability from one to five, where one is the most platoonable. This approach was used to analyze the highway network in Illinois. According to this approach, 89% of the interstates and freeways in Illinois are platoonable under average traffic conditions.
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Data Availability Statement
All data used during the study are available in a repository or online in accordance with funder data retention policies (http://apps.dot.illinois.gov/gist2/). All code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This study was supported by Illinois Department of Transportation (IDOT) project R27-203, Truck Platooning on Illinois Flexible Pavements. The authors acknowledge their guidance and support of this work.
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Journal of Transportation Engineering, Part A: Systems
Volume 147 • Issue 10 • October 2021
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© 2021 American Society of Civil Engineers.
History
Received: Dec 15, 2020
Accepted: Mar 23, 2021
Published online: Jul 27, 2021
Published in print: Oct 1, 2021
Discussion open until: Dec 27, 2021
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- Sudha Chaturvedi, Dr. Tapsi Nagpal, Vishnu Shankar Tiwari, Lempel-Ziv-Welch (LZW) based Horizontally Scalable Route Prediction, 2022 International Conference on Futuristic Technologies (INCOFT), 10.1109/INCOFT55651.2022.10094463, (1-6), (2022).