Optimal route of road networks by dynamic programming

Mainali, Manoj Kanta; Shimada, Kaoru; Mabu, Shingo; Hirasawa, Kotaro

doi:10.1109/ijcnn.2008.4634284

Cited by 14 publications

(9 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this paper, we use Q value-based Dynamic Programming (DP) [4], [5] because of its efficiency in the dynamic environments. In Q value-based DP approach, Q value is defined for the pair of adjacent intersections and the optimal route is determined by solving the following simultaneous nonlinear equation iteratively,…”

Section: Procedures 1 Of the Proposed Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Algorithm for Route Planning with Multiple Intermediate Destinations

Mainali

Mabu

Hirasawa

2011

SICE Journal of Control, Measurement, and System Integration

Self Cite

View full text Add to dashboard Cite

: The optimal route recommendation in navigation systems is often considered to be the optimal route recommendation between two locations, i.e., an origin and a destination. However, in practical scenarios, traveling to several intermediate destinations before the final destination needs to be considered. Conventional route search algorithms cannot consider such restrictions in the route search. In this paper, a method to find the optimal route via several intermediate destinations is proposed. The proposed method is divided into three steps. In the first step, the conventional route search algorithm is used to find the optimal traveling time and optimal route among the origin, intermediate destinations and final destination. In the second step, the visiting order of the intermediate destination is optimized using the population based RasID-D (RasID-DP) to minimize the total traveling time. Finally, the optimal route from the origin to destination is determined based on the results of the previous steps. The proposed method is evaluated based on the efficiency of the optimization of the visiting order of intermediate destinations. Simulation results show that RasID-DP based optimization can find better solutions efficiently.

show abstract

Section: Procedures 1 Of the Proposed Methodsmentioning

confidence: 99%

“…Often, the route with minimum traveling time or minimum traveling distance is considered as the optimal route. The optimal route search problem between two locations has been extensively studied in the literature and many algorithms have been proposed [1]- [5].…”

Section: Introductionmentioning

confidence: 99%

Algorithm for Route Planning with Multiple Intermediate Destinations

Mainali

Mabu

Hirasawa

2011

SICE Journal of Control, Measurement, and System Integration

Self Cite

View full text Add to dashboard Cite

show abstract

“…The route search algorithm should also be efficient to find the new optimal route when the traveling time changes due to something like the traffic congestion. We have already proposed Q value updating algorithm (Q method) [3,4] that exploits the available information and finds the new optimal route with the minimum number of updates. The algorithm proposed in this paper is an extension of our previous work in terms of considering the multiple criteria.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimal route search for road networks by dynamic programming

Mainalil

Shimada

Mabu

et al. 2008

2008 SICE Annual Conference

View full text Add to dashboard Cite

One of the most important functions of car navigation systems is to assist drivers to travel to destinations. Minimum traveling distance or time is often considered to find the optimal route to the destination. However, when searching for the optimal route, it is essential to consider users' preference in the search. In this paper, we propose a new Dynamic Programming method to find the optimal route to the destination considering multiple criteria. The proposed method is an extension of our previous route search algorithm, Q method. In this study, we will define the Q values for the pair of road sections. A general index will be introduced, which takes multiple criteria into consideration. Q values are updated based on the local information available including other Q values at the adjacent road sections. When the traveling time changes, we use the already obtained Q values to find the new optimal route. We applied the proposed method to a very simple artificial road network. Simulation results show that we can find better routes when considering multiple criteria compared to the optimization using the traveling time only.

show abstract

“…Therefore, presenting alternative routes to drivers may show greater advantages in global perspective and some research shows that a majority of drivers are willing to accept alternative routes suggested by advanced navigation systems [5]. In our previous work, we proposed a global traf c routing strategy [6], where Q Value-based Dynamic Programming [7] and Boltzmann distribution [8] are combined. However, this strategy is only applied to static environments where the traf c volume from each origin to destination is constant.…”

Section: Introductionmentioning

confidence: 99%

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

Wang

et al. 2008

2008 SICE Annual Conference

View full text Add to dashboard Cite

A simple traf c system is proposed in this paper, in which the global optimal route considering the traf c volume is selected as the guidance for the vehicles. In the proposed system, Q Value-based Dynamic Programming is adopted to calculate the optimal traveling time to each destination from every intersection of the road network. And Boltzmann Optimal Route Method is used to generate several route candidates, the usefulness of which is evaluated in terms of the total traveling time considering traf c volume. Furthermore, dynamically changing traf c volumes of all the given Origin-Destination pairs of road networks are constantly provided in the road simulation we used and the traveling time of each section is continuously updated according to its dynamic traf c volume. In this paper, the analysis and comparison between Greedy Strategy and Bolztmann Strategy with various "temperatures" are carried out. The simulation result showed the effectiveness of the proposed Boltzmann Optimal Route Method.

show abstract

Optimal route of road networks by dynamic programming

Cited by 14 publications

References 12 publications

Algorithm for Route Planning with Multiple Intermediate Destinations

Algorithm for Route Planning with Multiple Intermediate Destinations

Multi-objective optimal route search for road networks by dynamic programming

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

Contact Info

Product

Resources

About