Traffic congestion is more and more serious. Efficient route guidance has been the main way to relieve congestion. The existing research results mainly concentrate on optimizing single vehicle routing or multi-vehicles route guidance with small traffic network scale. There is no real-time and dynamic route guidance for large-scale multi-vehicles and multi-intersections. The current studies mainly have the following limitations: (1) the need for an appropriate metric or factor for the evaluation a route guidance project; (2) access to real-time route guidance for multiple vehicles in large scale multiple intersection urban networks. In view of the above problems

this paper proposes a route guidance quantum searching (RGQS) method for real-time dynamic multi-intersections in urban traffic network

which takes full account of various factors and provides real-time route guidance to avoid local congestion. The extensive experiments show that the RGQS method can reduce the traveling time by 20% compared with the comparison algorithms in the artificial road network and the real road network

respectively.