| DOI | Resolve DOI: https://doi.org/10.1007/978-3-031-07305-2_72 |
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| Author | Search for: Rahimi, Amir; Search for: Huang, Wei1; Search for: Sharma, Tarun; Search for: He, Yuping |
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| Affiliation | - National Research Council Canada. Automotive and Surface Transportation
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| Format | Text, Book Chapter |
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| Conference | 27th Symposium of the International Association of Vehicle System Dynamics (IAVSD 2021), August 17–19, 2021, Saint Petersburg, Russia |
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| Subject | multi-trailer articulated heavy vehicles; autonomous driving control; active trailer and dolly steering; nonlinear model predictive control; co-simulation |
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| Abstract | This article presents an autonomous driving control strategy for multi-trailer articulated heavy vehicles (MTAHVs). To design this strategy, a 5 degrees of freedom (DOF) yaw-plane model is generated to represent a MTAHV with the configuration of A-train double, and a nonlinear model predictive control (NLMPC) based controller is designed for direction and speed control of the MTAHV. Due to multi-unit structures, large sizes, and high centers of gravity (CGs), MTAHVs exhibit poor low-speed maneuverability and low high-speed lateral stability. Especially, MTAHVs often experience amplified lateral motions of trailing vehicle units in transient curved path negotiations. To enhance the safety performance of the autonomous driving control strategy, the self-driving A-train double design is featured with active trailer and dolly steering. To evaluate the effectiveness of the innovative autonomous driving control strategy, co-simulations are conducted by combining the integrated controller designed in MATLAB/ SIMULINK and a nonlinear A-train double model generated in TruckSim. |
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| Publication date | 2022-08-22 |
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| Publisher | Springer |
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| Series | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | a36e454d-5ecf-4db8-b06b-ed744bfab239 |
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| Record created | 2022-09-20 |
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| Record modified | 2022-09-20 |
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