Lin, Lu (2015-08). Platoon Identification System in Connected Vehicle Environment. Master's Thesis. Thesis uri icon

abstract

  • Connected vehicle technology has the potential of drastically improving the safety and mobility of transportation system. Recognizing and identifying the vehicle platoons in a traffic stream has the potential of changing the arterial signal control logic and increasing the bandwidth of the signal coordination system. This thesis investigated the nature of traffic platoons and developed a platoon identification algorithm under the connected vehicle environment. In this thesis, definition and characteristics of vehicle platoons are investigated through past literature and simulation results. A real-time algorithm to identify vehicle platoons is developed based on the findings. The proposed algorithm is implemented and simulated using PTV VISSIM. Performance measures are identified and proposed based on past studies. Impacts of penetration ratio of connected vehicle on the proposed algorithm is also investigated. A similar platoon identification algorithm from the past research is also implemented in PTV VISSIM and evaluated. The evaluation result of the existing platoon identification algorithm is compared to that of the proposed algorithm. The proposed approach is found to be more robust and practical in platoon identification.
  • Connected vehicle technology has the potential of drastically improving the safety and mobility of transportation system. Recognizing and identifying the vehicle platoons in a traffic stream has the potential of changing the arterial signal control logic and increasing the bandwidth of the signal coordination system.

    This thesis investigated the nature of traffic platoons and developed a platoon identification algorithm under the connected vehicle environment. In this thesis, definition and characteristics of vehicle platoons are investigated through past literature and simulation results. A real-time algorithm to identify vehicle platoons is developed based on the findings. The proposed algorithm is implemented and simulated using PTV VISSIM. Performance measures are identified and proposed based on past studies. Impacts of penetration ratio of connected vehicle on the proposed algorithm is also investigated.

    A similar platoon identification algorithm from the past research is also implemented in PTV VISSIM and evaluated. The evaluation result of the existing platoon identification algorithm is compared to that of the proposed algorithm. The proposed approach is found to be more robust and practical in platoon identification.

publication date

  • August 2015