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Car-Following Strategy Involving Stabilizing Traffic Flow with Connected Automated Vehicles to Reduce Particulate Matter (PM) Emissions in Rainy Weather

Author

Listed:
  • Renjie Li

    (Carollo Engineers, Inc., Los Angeles, CA 90017, USA)

  • Yanyan Qin

    (School of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China)

Abstract

On highways, it is commonplace to observe car-following behavior among vehicles. Unfortunately, this behavior results in significant particulate matter (PM) emissions, which greatly contribute to environmental pollution. Additionally, adverse weather conditions such as rain can negatively affect vehicles’ car-following behavior and have further influences on their PM emissions. The technology of connected automated vehicles (CAVs) offers a promising solution for mitigating these negative influences. This paper investigates the effect of various rainy weather conditions on PM emissions during car-following behavior on highways and proposes a CAV car-following strategy to reduce these emissions. Firstly, we employed a calibrated car-following model of traditional vehicles to perform simulation experiments, examining characteristics of PM emissions under four levels of rain and two simulation scenarios. Secondly, based on the relationship between PM emissions and speed fluctuations, we proposed a CAV car-following strategy by stabilizing traffic flow to smooth speed fluctuations. The proposed CAV car-following strategy was then validated through simulation experiments, and its effectiveness in reducing PM emissions under rainy conditions was assessed. The results indicate that higher speed fluctuations during car-following behavior lead to more PM emissions in rainy weather. By utilizing the proposed car-following strategy, CAVs can significantly reduce PM emissions in rain conditions, with average reductions of 41.07%, 59.46%, 49.60%, and 71.66% under very light rain, light rain, moderate rain, and heavy rain conditions, respectively. The findings of this paper facilitate the assessment of PM emissions fluctuations in different rainy weather conditions, which in turn can contribute to the development of more effective PM emissions control strategies. The proposed CAV car-following strategy can smooth speed fluctuations, and improve traffic flow stability, thus reducing PM emissions in rainy weather. It has the potential to mitigate environmental pollution from the transportation sector.

Suggested Citation

  • Renjie Li & Yanyan Qin, 2024. "Car-Following Strategy Involving Stabilizing Traffic Flow with Connected Automated Vehicles to Reduce Particulate Matter (PM) Emissions in Rainy Weather," Sustainability, MDPI, vol. 16(5), pages 1-23, February.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:5:p:2045-:d:1349237
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    References listed on IDEAS

    as
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