Eco-driving control for connected plug-in hybrid electric vehicles in urban scenarios with enhanced lane change engagement

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dc.contributor.authorLi, Jie
dc.contributor.authorLiu, Yonggang
dc.contributor.authorCheng, Jun
dc.contributor.authorFotouhi, Abbas
dc.contributor.authorChen, Zheng
dc.date.accessioned2024-10-29T16:08:57Z
dc.date.available2024-10-29T16:08:57Z
dc.date.freetoread2024-10-29
dc.date.issued2024-11
dc.date.pubOnline2024-09-27
dc.description.abstractEco-driving control techniques have shown significant potential in reducing energy consumption in urban scenarios. The presence of slow-moving vehicles typically disrupts ecological velocity planning, leading to an increase in energy consumption. To solve it, this study proposes a hierarchical eco-driving control strategy, that integrates speed optimization and lane change decision-making in urban scenarios, to not only ensure traffic efficiency, but also save the energy consumption. Firstly, a data-driven energy model is leveraged in the upper level to estimate the energy consumption of candidate lanes and generate ecological lane change decisions. Then, in the lower level, the preceding vehicles and traffic lights are considered to plan an ecological velocity profile via deep reinforcement learning algorithm after transitions to the target driving lane, thereby enhancing the fuel economy and travel efficiency. A virtual driving environment model is established to verify the proposed method through numerous simulation cases. The results indicate that the proposed method effectively reduces energy consumption while maintaining favorable travel efficiency, compared with conventional benchmarks. Furthermore, the notable improvements are observed particularly in free traffic conditions.
dc.description.journalNameEnergy
dc.description.sponsorshipNational Natural Science Foundation of China
dc.identifier.citationLi J, Liu Y, Cheng J, et al., (2024) Eco-driving control for connected plug-in hybrid electric vehicles in urban scenarios with enhanced lane change engagement. Energy, Volume 310, November 2024, Article number 133294
dc.identifier.eissn1873-6785
dc.identifier.elementsID554013
dc.identifier.issn0360-5442
dc.identifier.paperNo133294
dc.identifier.urihttps://doi.org/10.1016/j.energy.2024.133294
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/23138
dc.identifier.volumeNo310
dc.languageEnglish
dc.language.isoen
dc.publisherElsevier
dc.publisher.urihttps://www.sciencedirect.com/science/article/pii/S0360544224030706?via%3Dihub
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject4005 Civil Engineering
dc.subject40 Engineering
dc.subject7 Affordable and Clean Energy
dc.subjectEnergy
dc.subject4008 Electrical engineering
dc.subject4012 Fluid mechanics and thermal engineering
dc.subject4017 Mechanical engineering
dc.titleEco-driving control for connected plug-in hybrid electric vehicles in urban scenarios with enhanced lane change engagement
dc.typeArticle
dc.type.subtypeJournal Article
dcterms.dateAccepted2024-09-26

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