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Evaluation of the Effect of Connected Vehicles Speed and Acceleration Parameters on Freeways Safety and Efficiency

Kazemi, Mohammad | 2022

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55863 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Nassiri, Habibollah
  7. Abstract:
  8. Autonomous Vehicles have received much consideration in different trends in recent two decades. Autonomous Vehicles refer to vehicles that can drive without a driver and perform all driving tasks automatically, so eliminating the driver's role can affect various aspects. In this research, the effects of Autonomous Vehicles on the improvement of the traffic condition is studied. To this end, freeway’s performance parameters including travel time and traffic speed at the time of a traffic accident in mixed traffic conditions have been simulated. Considering that the braking behavior, acceleration, and speed changes of the Autonomous Vehicle are effective on the evaluation parameters, five car-following models including the Gipps model, Intelligent Driver Model (IDM), Enhanced Intelligent Driver Model (EIDM), Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) were examined. Among these models, Gipps model has been used to model the behavior of vehicles with a driver and others have been used to model the behaviour of self-driving vehicles. It was found that all the models lead to a decrease in freeway service quality. At a high penetration rate of Autonomous Vehicles, Intelligent Driver Model (IDM), Enhanced Intelligent Driver Model (EIDM), and Adaptive Cruise Control (ACC) model showed lower performance. The Intelligent Driver Model (IDM) model showed the worst performance, followed by Enhanced Intelligent Driver Model (EIDM), Adaptive Cruise Control (ACC), and finally, the Cooperative Adaptive Cruise Control (CACC) model showed the best performance. The Intelligent Driver Model (IDM), Enhanced Intelligent Driver Model (EIDM), Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) model have increased the delay time by 330, 270, 100, and 40 percent and decreased the traffic flow speed by 55, 51, 33, and 11 percent, respectively. The Cooperative Adaptive Cruise Control (CACC) model has shown better performance than other models due to its unique features, including modeling the communication between Autonomous Vehicles (also called Connected Vehicles) and platooning
  9. Keywords:
  10. Freeway ; Autonomous Vehicles (AVs) ; Car Following Model ; Mixed Traffic ; Traffic Flow Simulation ; Connected Vehicles

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