Fuel-Saving-Oriented Collaborative Driving Strategy for Commercial Vehicles Based on Driving Style Recognition
Fuel-saving-oriented collaborative driving is a highly promising yet challenging endeavor that requires satisfying the driver’s operational intentions while surpassing the driver’s fuel-saving performance. In light of this challenge, the paper introduces an innovative collaborative driving strategy...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-08-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/16/17/6163 |
| _version_ | 1797582598819545088 |
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| author | Hongqing Chu Zongxuan Li Jialin Wang Jinlong Hong |
| author_facet | Hongqing Chu Zongxuan Li Jialin Wang Jinlong Hong |
| author_sort | Hongqing Chu |
| collection | DOAJ |
| description | Fuel-saving-oriented collaborative driving is a highly promising yet challenging endeavor that requires satisfying the driver’s operational intentions while surpassing the driver’s fuel-saving performance. In light of this challenge, the paper introduces an innovative collaborative driving strategy tailored to the objective of fuel conservation in the context of commercial vehicles. An enhancement to this strategy involves the development of a network prediction model for vehicle speed, leveraging insights from driver style recognition. Employing the predicted speed as a reference, a model-predictive-control-based optimal controller is designed to track the reference while optimizing fuel consumption. Furthermore, a straightforward yet effective collaborative rule is proposed to ensure alignment with the driver’s intention. Subsequently, the proposed control scheme is validated through simulation and real-world driving data, revealing that the human–machine cooperative driving controller saves 4% more fuel than human drivers. |
| first_indexed | 2024-03-10T23:24:38Z |
| format | Article |
| id | doaj.art-5b5fa3b0f5144904a4691e280a2bdc6e |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T23:24:38Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-5b5fa3b0f5144904a4691e280a2bdc6e2023-11-19T08:04:11ZengMDPI AGEnergies1996-10732023-08-011617616310.3390/en16176163Fuel-Saving-Oriented Collaborative Driving Strategy for Commercial Vehicles Based on Driving Style RecognitionHongqing Chu0Zongxuan Li1Jialin Wang2Jinlong Hong3School of Automotive Studies, Tongji University, Shanghai 201804, ChinaSchool of Automotive Studies, Tongji University, Shanghai 201804, ChinaState Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, ChinaSchool of Automotive Studies, Tongji University, Shanghai 201804, ChinaFuel-saving-oriented collaborative driving is a highly promising yet challenging endeavor that requires satisfying the driver’s operational intentions while surpassing the driver’s fuel-saving performance. In light of this challenge, the paper introduces an innovative collaborative driving strategy tailored to the objective of fuel conservation in the context of commercial vehicles. An enhancement to this strategy involves the development of a network prediction model for vehicle speed, leveraging insights from driver style recognition. Employing the predicted speed as a reference, a model-predictive-control-based optimal controller is designed to track the reference while optimizing fuel consumption. Furthermore, a straightforward yet effective collaborative rule is proposed to ensure alignment with the driver’s intention. Subsequently, the proposed control scheme is validated through simulation and real-world driving data, revealing that the human–machine cooperative driving controller saves 4% more fuel than human drivers.https://www.mdpi.com/1996-1073/16/17/6163collaborative driving strategycommercial vehiclesmodel predictive controldriving style recognitionfuel-saving |
| spellingShingle | Hongqing Chu Zongxuan Li Jialin Wang Jinlong Hong Fuel-Saving-Oriented Collaborative Driving Strategy for Commercial Vehicles Based on Driving Style Recognition Energies collaborative driving strategy commercial vehicles model predictive control driving style recognition fuel-saving |
| title | Fuel-Saving-Oriented Collaborative Driving Strategy for Commercial Vehicles Based on Driving Style Recognition |
| title_full | Fuel-Saving-Oriented Collaborative Driving Strategy for Commercial Vehicles Based on Driving Style Recognition |
| title_fullStr | Fuel-Saving-Oriented Collaborative Driving Strategy for Commercial Vehicles Based on Driving Style Recognition |
| title_full_unstemmed | Fuel-Saving-Oriented Collaborative Driving Strategy for Commercial Vehicles Based on Driving Style Recognition |
| title_short | Fuel-Saving-Oriented Collaborative Driving Strategy for Commercial Vehicles Based on Driving Style Recognition |
| title_sort | fuel saving oriented collaborative driving strategy for commercial vehicles based on driving style recognition |
| topic | collaborative driving strategy commercial vehicles model predictive control driving style recognition fuel-saving |
| url | https://www.mdpi.com/1996-1073/16/17/6163 |
| work_keys_str_mv | AT hongqingchu fuelsavingorientedcollaborativedrivingstrategyforcommercialvehiclesbasedondrivingstylerecognition AT zongxuanli fuelsavingorientedcollaborativedrivingstrategyforcommercialvehiclesbasedondrivingstylerecognition AT jialinwang fuelsavingorientedcollaborativedrivingstrategyforcommercialvehiclesbasedondrivingstylerecognition AT jinlonghong fuelsavingorientedcollaborativedrivingstrategyforcommercialvehiclesbasedondrivingstylerecognition |