Eco-driving at signalized intersections is a topical issue in CAVs technology and an important part of energy-efficient driving. In this paper, a robust eco-driving control method of vehicular platoon is proposed to address the uncertain traffic conditions, including traffic queuing effects and signal time variations. Firstly, an effective signalization model is established by estimating the traffic queue length and describing the uncertain parameters with the interval number. Then, taking fuel economy and vehicle safety as the objectives, the uncertain objective function is transformed into a deterministic optimization problem by using the order interval relation model. Finally, a model predictive control method is used to optimize the problem. The simulation results indicate that the proposed method can significantly improve the control robustness and fuel economy without the signal history data.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Eco-driving at signalized intersections under uncertain traffic conditions


    Beteiligte:
    Chen, Xinyu (Autor:in) / Qian, Lijun (Autor:in) / Wang, Qidong (Autor:in)


    Erscheinungsdatum :

    2024-02-01




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Driving Behavior at Signalized Intersections Operating under Disordered Traffic Conditions

    Chauhan, Ritvik / Dhamaniya, Ashish / Arkatkar, Shriniwas | Transportation Research Record | 2021


    Delay at Signalized Intersections under Mixed Traffic Conditions

    Saha, Arpita / Chandra, Satish / Ghosh, Indrajit | ASCE | 2017



    Saturation flow estimation at signalized intersections under mixed traffic conditions

    Saha, Arpita / Chandra, Satish / Ghosh, Indrajit | TIBKAT | 2018


    Calibration of Microscopic Traffic Simulation for Signalized Intersections Under Heterogeneous Traffic Conditions

    Katkar, Rushikesh / Venugopal, Anagha / Saikrishna, Chithra A. et al. | Springer Verlag | 2023