Utilizing Model-Based Communication and Control for Cooperative Automated Vehicle Applications

• Published in: IEEE transactions on intelligent vehicles 2017-03, Vol.2 (1), p.38-51
• Main Authors: Moradi-Pari, Ehsan, Mahjoub, Hossein Nourkhiz, Kazemi, Hadi, Fallah, Yaser P., Tahmasbi-Sarvestani, Amin
• Format: Article
• Language: English
• Subjects: Adaptation models; connected and automated vehicles; cooperative adaptive cruise control; Cyber-physical systems; DSRC; hidden Markov model; Hidden Markov models; Mathematical model; Predictive models; Safety; stochastic model predictive controller; Vehicle dynamics; Vehicles
• ISSN: 2379-8858; 2379-8904
• DOI: 10.1109/TIV.2017.2708605

Connected vehicle applications rely on wireless communication for achieving real-time situational awareness and enabling automated actions or driver warnings. Given the constraints of the communication systems, it is critical to employ communication strategies and approaches that allow robust situational awareness. In this work, we utilize the recently introduced concept of model-based communication and design a new strategy based on small- and large-scale modeling of vehicle movement dynamics. Our approach is to describe the small-scale structure of the remote vehicle movement (e.g., braking, accelerating) by a set of dynamic models (ARX models) and represent the large-scale structure (e.g., free following, turning) by coupling these ARX models together into a Markov chain. The effect of this design is investigated for the case of cooperative adaptive cruise control application. Assuming model-based communication approach is used with the coupled model, a novel stochastic model predictive method is proposed to achieve cruise control goals. We use actual highway driving maneuvers to compare the proposed methodology with the conventional design of cooperative adaptive cruise control.