A global routing strategy in dynamic traffic environments with a combination of Q value-based dynamic programming and boltzmann distribution

Yu, Shanqing; Ye, Fengming; Wang, Hongqiang; Mabu, Shingo; Shimada, Kaoru; Yu, Song-Nian; Hirasawa, Kotaro

doi:10.1109/sice.2008.4654732

Cited by 9 publications

(1 citation statement)

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“…As for other applications of the Q-method, it can be applied to find the global optimal route considering the traffic volume. Such applications have been studied by Yu et al [19,20].…”

Section: Background: the Q-methodsmentioning

confidence: 99%

Dynamic optimal route search algorithm for car navigation systems with preferences by dynamic programming

Mainali

Mabu

et al. 2010

IEEJ Transactions Elec Engng

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Optimal route search to the destination is one of the most important functions of car navigation devices. The development of road traffic infrastructure has made it possible to receive real-time information of the traffic situation. Route search algorithms for car navigation devices make use of this information to avoid the traffic congestions. Such algorithms should find the new optimal route efficiently when the traffic situation changes. Usually, the minimum traveling time or distance is considered to define the optimal route. However, the minimum traveling time or distance is not always what the user is looking for. The user may prefer to travel on a certain route even at the cost of traveling time or distance. Car navigation devices should consider such preferences when finding the optimal route. In this paper, we propose a dynamic programming algorithm to find the optimal route considering that it should deal with the changes of the traffic situation and multiple criteria. The proposed method uses the information from the previous computation to find the new optimal route considering user preferences when the traveling time of the road section changes. The proposed method was applied to a real road network to find the optimal route. Results show that the proposed method can find the user-preferred optimal route. Simulation results also show better calculation time of the proposed method compared to the Dijkstra algorithm. 

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“…As for other applications of the Q-method, it can be applied to find the global optimal route considering the traffic volume. Such applications have been studied by Yu et al [19,20].…”

Section: Background: the Q-methodsmentioning

confidence: 99%