An Eco-Driving Controller Based on Intelligent Connected Vehicles for Sustainable Transportation
The rapid increase in the number of vehicles has brought significant challenges to energy conservation and environmental sustainability. To solve these problems, various frameworks and models based on intelligent connected vehicles (ICVs) have been identified for road capacity improvement and fuel c...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/9/4533 |
| _version_ | 1797505635513794560 |
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| author | Pangwei Wang Rongsheng Ye Juan Zhang Tianren Wang |
| author_facet | Pangwei Wang Rongsheng Ye Juan Zhang Tianren Wang |
| author_sort | Pangwei Wang |
| collection | DOAJ |
| description | The rapid increase in the number of vehicles has brought significant challenges to energy conservation and environmental sustainability. To solve these problems, various frameworks and models based on intelligent connected vehicles (ICVs) have been identified for road capacity improvement and fuel consumption reduction. In this paper, an eco-driving controller with ICVs was first proposed by combining vehicular dynamics with wireless communication technologies, where the nodes that can implement perception and control in a simulated complex traffic environment have been deployed. Then, the information of the surrounding environment, including the preceding vehicles, was obtained through a wireless communication module based on the technology of vehicle to everything (V2X). Besides, the advanced model predictive control (MPC) strategy was integrated into the ICV controller with the objectives of minimizing the driving spacing and improving environmental sustainability. Finally, a co-simulation platform for ICVs based on a robot operating system (ROS) and PreScan software was constructed, and the dynamic characteristics of the controller were verified in three aspects, including car-following behaviors, fuel efficiency improvement, and carbon dioxide emission reduction. The proposed controller showed that it can reduce fuel consumption by 3.71% and reduce carbon dioxide emissions by 3.42%, in the scenarios of a preceding vehicle with constant velocity, and by 6.77% and 7.91%, respectively, in a preceding vehicle with variable velocity scenario. The demonstrated experimental results show that the proposed controller can effectively reduce fuel consumption and emissions during car-following. |
| first_indexed | 2024-03-10T04:21:26Z |
| format | Article |
| id | doaj.art-e9c3d3a636b44ba1b88d8ac8dcdfaf79 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T04:21:26Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-e9c3d3a636b44ba1b88d8ac8dcdfaf792023-11-23T07:50:21ZengMDPI AGApplied Sciences2076-34172022-04-01129453310.3390/app12094533An Eco-Driving Controller Based on Intelligent Connected Vehicles for Sustainable TransportationPangwei Wang0Rongsheng Ye1Juan Zhang2Tianren Wang3Beijing Key Lab of Urban Intelligent Traffic Control Technology, North China University of Technology, Beijing 100144, ChinaBeijing Key Lab of Urban Intelligent Traffic Control Technology, North China University of Technology, Beijing 100144, ChinaCollege of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QF, UKBeijing Key Lab of Urban Intelligent Traffic Control Technology, North China University of Technology, Beijing 100144, ChinaThe rapid increase in the number of vehicles has brought significant challenges to energy conservation and environmental sustainability. To solve these problems, various frameworks and models based on intelligent connected vehicles (ICVs) have been identified for road capacity improvement and fuel consumption reduction. In this paper, an eco-driving controller with ICVs was first proposed by combining vehicular dynamics with wireless communication technologies, where the nodes that can implement perception and control in a simulated complex traffic environment have been deployed. Then, the information of the surrounding environment, including the preceding vehicles, was obtained through a wireless communication module based on the technology of vehicle to everything (V2X). Besides, the advanced model predictive control (MPC) strategy was integrated into the ICV controller with the objectives of minimizing the driving spacing and improving environmental sustainability. Finally, a co-simulation platform for ICVs based on a robot operating system (ROS) and PreScan software was constructed, and the dynamic characteristics of the controller were verified in three aspects, including car-following behaviors, fuel efficiency improvement, and carbon dioxide emission reduction. The proposed controller showed that it can reduce fuel consumption by 3.71% and reduce carbon dioxide emissions by 3.42%, in the scenarios of a preceding vehicle with constant velocity, and by 6.77% and 7.91%, respectively, in a preceding vehicle with variable velocity scenario. The demonstrated experimental results show that the proposed controller can effectively reduce fuel consumption and emissions during car-following.https://www.mdpi.com/2076-3417/12/9/4533car-following modeleco-drivingintelligent connected vehicles (ICVs)model predictive control (MPC)sustainable transportation |
| spellingShingle | Pangwei Wang Rongsheng Ye Juan Zhang Tianren Wang An Eco-Driving Controller Based on Intelligent Connected Vehicles for Sustainable Transportation Applied Sciences car-following model eco-driving intelligent connected vehicles (ICVs) model predictive control (MPC) sustainable transportation |
| title | An Eco-Driving Controller Based on Intelligent Connected Vehicles for Sustainable Transportation |
| title_full | An Eco-Driving Controller Based on Intelligent Connected Vehicles for Sustainable Transportation |
| title_fullStr | An Eco-Driving Controller Based on Intelligent Connected Vehicles for Sustainable Transportation |
| title_full_unstemmed | An Eco-Driving Controller Based on Intelligent Connected Vehicles for Sustainable Transportation |
| title_short | An Eco-Driving Controller Based on Intelligent Connected Vehicles for Sustainable Transportation |
| title_sort | eco driving controller based on intelligent connected vehicles for sustainable transportation |
| topic | car-following model eco-driving intelligent connected vehicles (ICVs) model predictive control (MPC) sustainable transportation |
| url | https://www.mdpi.com/2076-3417/12/9/4533 |
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