Reducing vehicle exhaust pollution and energy consumption is of great significance for improving the sustainability of social development. Currently, most energy-efficient and regenerative energy recovery methods are from a vehicle control perspective, ignoring the impact on the overall traffic environment. An important reason is that the transportation system's large scale, complexity and social nature restrict its energy-efficient development. Hence, this letter proposes energy-efficient and regenerative energy recovery schemes for sustainable intelligent transportation system using the Artificial societies, Computational experiments, Parallel execution (ACP) framework. The framework includes three parts: energy-efficient oriented intelligent road infrastructure design, transportation traffic flow and vehicle velocity profile planning co-design, and cloud-based vehicle engine parameter calibration. This letter is the second part of Distributed/Decentralized Hybrid Workshop on Sustainability for Transportation and Logistics (DHW-STL) and aims to enhance the sustainability of transportation system from the energy-efficient perspective.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    ACP-Based Energy-Efficient Schemes for Sustainable Intelligent Transportation Systems


    Contributors:
    Chen, Jicheng (author) / Zhang, Yongkang (author) / Teng, Siyu (author) / Chen, Yuanyuan (author) / Zhang, Hui (author) / Wang, Fei-Yue (author)

    Published in:

    Publication date :

    2023-05-01


    Size :

    727203 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Intelligent Transportation Systems: Enabling Sustainable Transportation and Efficient Traffic Management—A Review

    Rosario, Roberto D. / Alvarez, Arjel / Quinto, Ronnel C. et al. | Springer Verlag | 2025


    Transportation Internet: A Sustainable Solution for Intelligent Transportation Systems

    Li, Hui / Chen, Yongquan / Li, Keqiang et al. | IEEE | 2023



    Intelligent transportation systems for sustainable smart cities

    Mohamed Elassy / Mohammed Al-Hattab / Maen Takruri et al. | DOAJ | 2024

    Free access