Ｒeasonable path planning can shorten the travelling time to ensure that rescue forces can arrive at the scene in time and improve the efficiency of emergency rescue． Based on the urban road traffic characteristics and the dynamic evolution of traffic environments，this paper proposed an extended co-evolutionary algorithm ( ECEA) to calculate the optimal rescue path． The ECEA establishes a co-evolutionary optimization mechanism，which means that the path planning process co-evolves with the evolution of traffic environments． Meanwhile，ECEA can flexibly select the search scope to improve the number and quality of alternative solutions． Experimental results show that ECEA outperforms timing co-evolutionary algorithm ( TCEPO) and Online re-optimization ( OLRO) both in the travelling time and robustness under the condition of limited data，thereby improving emergency rescue efficiency．