Researchers Develop New Strategy to Reduce Traffic Congestion after Accidents

Strategic Insights -

Researchers at Henan University of Technology have developed a new strategy to reduce traffic congestion after accidents in urban road networks. The strategy involves using SUMO software to analyze the characteristics of network accidents and then developing a road network recovery model that includes traffic signal optimization and guiding vehicles to avoid the accident area. The model was tested in a road network in Zhengzhou city, with results showing that the proposed strategy effectively reduces vehicle delay after an accident.

Key Takeaways:

  • The researchers employed SUMO software to analyze the characteristics of network accidents, including traffic speed, density, occupancy rate, and acceleration.
  • The developed road network recovery strategy consists of two parts: congestion propagation model and traffic signal optimization.
  • The congestion propagation model divides the road network into an 'accident core area' and an 'accident surrounding area'.
  • Traffic signal optimization is applied in the accident core area to improve traffic capacity.
  • Vehicles in the accident surrounding area are guided to avoid the accident core area to reduce traffic pressure.
  • The proposed recovery strategy was tested in a road network in Zhengzhou city with traffic accident points set in the network's center and edge areas.
  • The results show that the proposed recovery strategy effectively reduces vehicle delay after an accident.
  • The average vehicle delay was reduced by 6.73%, 16.15%, and 16.84% under low, medium, and high traffic demand, respectively, when a traffic accident occurs in the edge area of the network.
  • The average vehicle delay was reduced by 9.91%, 15.56%, and 18.80% under low, medium, and high traffic demand, respectively, when a traffic accident occurs in the central area of the network.
  • A sensitivity analysis of the strategy with respect to the traffic accident duration was conducted, demonstrating its good performance.
  • The research provides a new approach to improving the efficiency of urban road networks by exploring the congestion propagation from traffic accidents.
  • The proposed recovery strategy can be applied to various types of road networks, including those with high traffic demand.

Statistics:

  • Average vehicle delay reduction: 6.73% (edge area), 16.15% (edge area - medium traffic demand), 16.84% (edge area - high traffic demand)
  • Average vehicle delay reduction: 9.91% (central area - low traffic demand), 15.56% (central area - medium traffic demand), 18.80% (central area - high traffic demand)
  • Traffic accident duration sensitivity analysis: demonstrated good performance of the proposed recovery strategy

Sources:

  • VerticalNews, "Researchers Detail New Data in Engineering and Applied Science" (2025)
  • Journal of Engineering and Applied Science, "Analysis of traffic accident characteristics and recovery strategy of urban road network" (2025, 72(1):1-16)
  • SpringerOpen, publisher of Journal of Engineering and Applied Science
  • NewsRx, "Reports from Henan University of Technology Highlight Recent Research in Engineering and Applied Science" (2025)