The response efficiency of urban emergency rescue systems is critical to public safety, and path planning algorithms are key technologies for ensuring the rapid passage of rescue vehicles. Conventional navigation algorithms cannot meet the extreme time-sensitivity requirements and highly disturbed road network characteristics inherent in rescue missions. This paper focuses on optimising priority routes for emergency rescue vehicles. By analysing the dynamic attributes of rescue vehicles under abnormal driving conditions, it dissects the nonlinear coupling mechanism between rescue vehicles and dynamic traffic flow parameters, revealing the formation mechanism of secondary congestion in road networks under forced-priority strategies. Traditional static algorithms exhibit significant response delays to sudden traffic conditions and rely on single-dimensional decision-making. This paper proposes an optimisation method that integrates global path search with localised signal control, introducing a dynamic evasion coordination mechanism for non-emergency vehicles. This provides a theoretical foundation and implementation pathway for building adaptive, innovative emergency transportation systems.
Wei et al. (Wed,) studied this question.