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The Impact of AV and CAV Vehicles on Capacity and Traffic Flow with Cooperative Lane changing in Mixed Traffic Environment

Zanjani, Fatemeh Sadat | 2024

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57806 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Nassiri, Habibollah
  7. Abstract:
  8. Autonomous vehicles, as an integral part of intelligent transportation systems, will play a significant role in the future of transportation services. These vehicles have a high potential to improve road traffic capacity and the efficiency of transportation systems. One type of autonomous vehicle is the connected and autonomous vehicle (CAV), which can communicate with each other, roadside units, traffic control signals, and other infrastructures or devices. This study investigates the impact of autonomous vehicles and connected and autonomous vehicles on the traffic flow of the Tehran-Karaj freeway and vice versa, under various penetration rates and in a mixed traffic environment. In this study, real traffic data from the Tehran-Karaj route, obtained from the Ministry of Roads and Urban Development, was used, and conventional, autonomous, and connected autonomous vehicles were modeled with their respective parameters. Additionally, two different car-following models, Cooperative Adaptive Cruise Control (CACC) and Adaptive Cruise Control (ACC), were examined for autonomous vehicles. Traffic parameters such as the average travel time and the average waiting time for each scenario were analyzed and assessed. The results showed that with an increase in the number of autonomous vehicles in the network, the average travel time decreased. The higher the penetration rate of autonomous vehicles, the greater the reduction in average travel time. Similarly, the average waiting time followed a similar trend, so that at 100% penetration of autonomous vehicles, the average waiting time almost reached zero. A comparison between the performance of the two car-following models was also made. The results indicated that the CACC model performs better in improving traffic flow. For connected and autonomous vehicles, a reduction in average travel time was observed as their penetration rate increased. Furthermore, the results showed that the reduction in average travel time was greater when vehicles were connected and autonomous, compared to not connected and autonomous vehicles. Overall, it can be concluded that autonomous vehicle technology can significantly help improve the traffic conditions on this busy route
  9. Keywords:
  10. Travel Time ; Autonomous Vehicles (AVs) ; Traffic ; Car Following Model ; Mixed Traffic ; Lane Changing ; Connected Vehicles

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