Using connected vehicle technology to improve the efficiency of intersections |
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| Affiliation: | 1. Universidad de Murcia, Facultad de Informática, Departamento de Ingeniería de la Información y las Comunicaciones, 30100 Murcia, Spain;2. Centro Universitario de la Defensa de San Javier (University Centre of Defence at the Spanish Air Force Academy), MDE-UPCT, C/Coronel López Peña, s/n, Santiago de la Ribera, 30720 Murcia, Spain;3. Universidad Católica de Murcia (Catholic University of Murcia), Facultad Politécnica, 30107 Murcia, Spain;1. Center for Sustainable Urban Development (CEDEUS), Pontificia Universidad Católica de Chile, Chile;2. Department of Transport Engineering and Logistics, Pontificia Universidad Católica de Chile, Chile;1. Institute of Transportation Studies, University of California, Berkeley, McLaughlin Hall 416E, Berkeley, CA 94720, United States;2. Department of Civil and Environmental Engineering, University of Massachusetts, Amherst, 130 Natural Resources Road, Amherst, MA 01003, United States;1. Civil and Environmental Engineering Department, Washington State University, USA;2. Civil and Environmental Engineering Department, Washington State University, PO Box 642910, Pullman, WA 99164-2910, USA;1. NEXTRANS Center, Purdue University, 3000 Kent Avenue, West Lafayette, IN 47906, United States;2. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, Sichuan, China;3. Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI 48109, United States;4. University of Michigan Transportation Research Institute, University of Michigan, Ann Arbor, MI 48109, United States;5. National-Local Association Laboratory of Comprehensive Transportation Intelligentization, Southwest Jiaotong University, Chengdu, Sichuan, China |
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| Abstract: | Information from connected vehicles, such as the position and speed of individual vehicles, can be used to optimize traffic operations at an intersection. This paper proposes such an algorithm for two one-way-streets assuming that only a certain percentage of cars are equipped with this technology. The algorithm enumerates different sequences of cars discharging from the intersection to minimize the objective function. Benefits of platooning (multiple cars consecutively discharging from a queue) and signal flexibility (adaptability to demand) are also considered. The goal is to gain insights about the value (in terms of delay savings) of using connected vehicle technology for intersection control.Simulations are conducted for different total demand values and demand ratios to understand the effects of changing the minimum green time at the signal and the penetration rate of connected cars. Using autonomous vehicle control systems, the signal could rapidly change the direction of priority without relying on the reaction of drivers. However, without this technology a minimum green time is necessary. The results of the simulations show that a minimum green time increases the delay only for the low and balanced demand scenarios. Therefore, the value of using cars with autonomous vehicle control can only be seen at intersections with this kind of demand patterns, and could result in up to 7% decrease in delay. On the other hand, using information from connected vehicles to better adapt the traffic signal has proven to be indeed very valuable. Increases in the penetration rate from 0% up to 60% can significantly reduce the average delay (in low demand scenarios a decrease in delay of up to 60% can be observed). That being said, after a penetration rate of 60%, while the delays continue to decrease, the rate of reduction decreases and the marginal value of information from communication technologies diminishes. Overall, it is observed that connected vehicle technology could significantly improve the operation of traffic at signalized intersections, at least under the proposed algorithm. |
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| Keywords: | Connected vehicle Traffic control Intersections Traffic flow |
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