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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 51128 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Haeri, Mohammad; Ramezani, Moshen
- Abstract:
- The emergence of Autonomous Vehicles (AVs) provides the opportunities to ameliorate traffic congestion while increasing safety. AVs, using the vehicle to vehicle and vehicle to infrastructure communication, can gather and infer the information of adjacent vehicles and traffic flow. The objective of this article is to develop a cooperative control method to manipulate AVs longitudinal and lateral movements in order to enhance macroscopic features of the mixed traffic flows. In this paper, we propose a potential function to control longitudinal movement of AVs considering their physical constraints. The developed controller provides an optimal, collision-free car following by minimizing the distance to the leader vehicle with respect to a safe distance. The stability investigations result in stability of the equilibrium point of the system. In addition, we propose new safety and incentive criteria for lane changing of AVs. AVs lateral movement is controlled as a minimum time optimization problem. Simulation results demonstrate the advantages of the proposed potential function over a quadratic programming method in terms of relative tracking error and the variations of acceleration. Furthermore, the simulation results of the mixed traffic flows with various penetration rates of AVs on a freeway demonstrate that the proposed cooperative AVs controller reduces freeway total travel time and the decrease in time mean speed at the ramp merging section
- Keywords:
- Cooperative Control ; Potential Function ; Intelligent Transportation System (ITS) ; Stability Analysis ; Autonomous Vehicles (AVs) ; Incentive-Based Lane Changing
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