Volume 24 Issue 2
Apr.  2024
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Article Contents
MA Qing-lu, WANG Xin-yu, ZHANG Shu, DUAN Xue-feng. Self-organizing method for traffic coupling between adjacent ramps in intelligent and connected environments[J]. Journal of Traffic and Transportation Engineering, 2024, 24(2): 207-220. doi: 10.19818/j.cnki.1671-1637.2024.02.014
Citation: MA Qing-lu, WANG Xin-yu, ZHANG Shu, DUAN Xue-feng. Self-organizing method for traffic coupling between adjacent ramps in intelligent and connected environments[J]. Journal of Traffic and Transportation Engineering, 2024, 24(2): 207-220. doi: 10.19818/j.cnki.1671-1637.2024.02.014

Self-organizing method for traffic coupling between adjacent ramps in intelligent and connected environments

doi: 10.19818/j.cnki.1671-1637.2024.02.014
Funds:

National Natural Science Foundation of China 52072054

Technology Innovation and Application Development Program of Chongqing CSTB2022TIAD-STX0003

Science and Technology Project of Department of Transportation of Ningxia Hui Autonomous Region NJGF(2020)0301

Graduate Research Innovation Project of Chongqing Jiaotong University CYB23256

More Information
  • Author Bio:

    MA Qing-lu(1980-), male, professor, PhD, qlm@cqjtu.edu.cn

  • Received Date: 2023-05-20
    Available Online: 2024-05-16
  • Publish Date: 2024-04-30
  • A self-organizing method for traffic coupling between adjacent ramps was proposed to improve traffic safety and efficiency in on-ramp merging areas in intelligent and connected environments. By establishing an optimal matching model between the mainline traffic flow gap and on-ramp vehicle speed, the overall headway of the outermost lane of the mainline was optimized and adjusted. On the premise of ensuring the safe merging of on-ramp vehicles, the traffic efficiency of vehicles between adjacent ramps was improved. Two adjacent ramps near the Donghuan overpass on the inner ring expressway in Chongqing were selected as the research prototype. Online map combined with drone aerial photography, fixed-point photography, and other data acquisition methods were used to conduct field investigations on the testing sections. In intelligent and connected environments, cooperative adaptive cruise control (CACC) and traffic coupling self-organizing (TCS) method were applied respectively, and Python, SUMO, and TraCI were used for co-simulation of vehicle operation on the test road. Research results show that compared with CACC, the lane changing number in TCS decreases by 19.87% from 65.52 to 52.64, which effectively alleviates the traffic conflict between adjacent ramps. The average delay decreases by 70.38% from 24.53 s to 14.39 s. To be specific, the average delay decreases by 77.71% in the off-peak period and 34.50% in the peak period, respectively. Compared with the peak period, the efficiency in the off-peak period is greatly improved. The time occupancy decreases by 53.86% from 18.70% to 8.63%. The time occupancy difference between different lanes decreases to 6.00%, that is, vehicles are more evenly distributed across different lanes. The average speed increases by 3.06% from 78.31 km·h-1 to 80.78 km·h-1, which effectively alleviates the deceleration near the on-ramp merging and off-ramp diverging areas.

     

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