Optimal Route Based on Dynamic Programming for Road Networks

2008 ◽  
Vol 12 (6) ◽  
pp. 546-553 ◽  
Author(s):  
Manoj Kanta Mainali ◽  
◽  
Kaoru Shimada ◽  
Shingo Mabu ◽  
Kotaro Hirasawa
Keyword(s):  
Dynamic Programming ◽  
Road Networks ◽  
Q Method ◽  
Navigation Systems ◽  
Optimal Route ◽  
Dijkstra Algorithm ◽  
Q Value ◽  
The Road ◽  
Multiple Origins ◽  
Q Values

One of the main functions of the traffic navigation systems is to find the optimal route to the destination. In this paper, we propose an iterative Q value updating algorithm, Q method, based on dynamic programming to search the optimal route and its optimal traveling time for a given Origin-Destination (OD) pair of road networks. The Q method uses the traveling time information available at adjacent intersections to search for the optimal route. The Q value is defined as the minimum traveling time to the destination when a vehicle takes the next intersection. When the Q values converge, the optimal route to the destination can be determined by choosing the minimum Q value at each intersection. The Q method gives us the solutions from multiple origins to a single destination. The proposed method is not restricted to find a single solution, but, if there exist multiple optimal routes with the identical traveling time to the destination, the proposed method can find all of it. In addition to that, when the traveling time of the road sections changes, an alternative optimal route can be found easily starting with the already obtained Q values. We compared the Q method with Dijkstra algorithm and the simulation results showed that the Q method can give better performances, depending on the situations, when the traveling time of the road sections changes.

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

2010 ◽  
Vol 6 (1) ◽  
pp. 14-22 ◽  
Author(s):  
Manoj Kanta Mainali ◽  
Shingo Mabu ◽  
Shanqing Yu ◽  
Shinji Eto ◽  
Kotaro Hirasawa
Keyword(s):  
Dynamic Programming ◽  
Search Algorithm ◽  
Navigation Systems ◽  
Optimal Route ◽  
Route Search ◽  
Car Navigation

Determining optimal road class and road deactivation strategies using dynamic programming

2006 ◽  
Vol 36 (6) ◽  
pp. 1509-1518 ◽  
Author(s):  
Axel E Anderson ◽  
John D Nelson ◽  
Robert G D'Eon
Keyword(s):  
Dynamic Programming ◽  
Programming Model ◽  
Road Networks ◽  
Road Construction ◽  
Construction Costs ◽  
Deactivation Model ◽  
Spatial And Temporal Scales ◽  
The Road ◽  
Network Costs

Forest managers are faced with complicated road construction and deactivation decisions. When construction, upgrading, and deactivation strategies must be determined simultaneously over broad spatial and temporal scales, the problem becomes very complex and decision support systems are needed. In this paper, we report the development and application of an optimal road class and deactivation model using dynamic programming. We tested our model on projected road networks on Hardwicke Island, British Columbia. Sensitivity of inputs such as construction costs, upgrade costs, hauling and maintenance costs, deactivation costs, length of time horizon, discount rate, and haul volume were tested within and between two road networks. Comparison of road networks revealed that haul volume concentration, average haul distance, and total road length are the most important variables that affect road class decisions and total network costs. Within our case study, the road network with the lowest average hauling distance resulted in the lowest total cost (CAN$0.24/m3 less), because hauling costs are the largest component (46%) of total transportation costs. The dynamic programming model can be used to assess numerous road construction and maintenance assumptions under various silviculture and harvest systems.

Fast computation of Q-value-based dynamic programming on road networks

2012 ◽  
Vol 7 (4) ◽  
pp. 408-414
Author(s):  
Feng Wen ◽  
Deng Zhang ◽  
Shingo Mabu ◽  
Manoj Kanta Mainali ◽  
Kotaro Hirasawa
Keyword(s):  
Dynamic Programming ◽  
Road Networks ◽  
Fast Computation ◽  
Q Value

scholarly journals Evaluating the Safety Risk of Rural Roadsides Using a Bayesian Network Method

2019 ◽  
Vol 16 (7) ◽  
pp. 1166 ◽  
Author(s):  
Tianpei Tang ◽  
Senlai Zhu ◽  
Yuntao Guo ◽  
Xizhao Zhou ◽  
Yang Cao
Keyword(s):  
Bayesian Network ◽  
Low Cost ◽  
Road Networks ◽  
Access Point ◽  
Safety Risk ◽  
Crash Data ◽  
Risk Levels ◽  
The Road ◽  
Run Off ◽  
Point Density

Evaluating the safety risk of rural roadsides is critical for achieving reasonable allocation of a limited budget and avoiding excessive installation of safety facilities. To assess the safety risk of rural roadsides when the crash data are unavailable or missing, this study proposed a Bayesian Network (BN) method that uses the experts’ judgments on the conditional probability of different safety risk factors to evaluate the safety risk of rural roadsides. Eight factors were considered, including seven factors identified in the literature and a new factor named access point density. To validate the effectiveness of the proposed method, a case study was conducted using 19.42 km long road networks in the rural area of Nantong, China. By comparing the results of the proposed method and run-off-road (ROR) crash data from 2015–2016 in the study area, the road segments with higher safety risk levels identified by the proposed method were found to be statistically significantly correlated with higher crash severity based on the crash data. In addition, by comparing the respective results evaluated by eight factors and seven factors (a new factor removed), we also found that access point density significantly contributed to the safety risk of rural roadsides. These results show that the proposed method can be considered as a low-cost solution to evaluating the safety risk of rural roadsides with relatively high accuracy, especially for areas with large rural road networks and incomplete ROR crash data due to budget limitation, human errors, negligence, or inconsistent crash recordings.

scholarly journals Modeling of Emergency Supply Scheduling Problem Based on Reliability and Its Solution Algorithm under Variable Road Network after Sudden-Onset Disasters

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Tinggui Chen ◽  
Shiwen Wu ◽  
Jianjun Yang ◽  
Guodong Cong ◽  
Gongfa Li
Keyword(s):  
Road Network ◽  
Road Networks ◽  
Sudden Onset ◽  
The Road ◽  
Bee Colony ◽  
Proposed Model ◽  
Effectiveness And Efficiency ◽  
In Transit ◽  
Emergency Supply

It is common that many roads in disaster areas are damaged and obstructed after sudden-onset disasters. The phenomenon often comes with escalated traffic deterioration that raises the time and cost of emergency supply scheduling. Fortunately, repairing road network will shorten the time of in-transit distribution. In this paper, according to the characteristics of emergency supplies distribution, an emergency supply scheduling model based on multiple warehouses and stricken locations is constructed to deal with the failure of part of road networks in the early postdisaster phase. The detailed process is as follows. When part of the road networks fail, we firstly determine whether to repair the damaged road networks, and then a model of reliable emergency supply scheduling based on bi-level programming is proposed. Subsequently, an improved artificial bee colony algorithm is presented to solve the problem mentioned above. Finally, through a case study, the effectiveness and efficiency of the proposed model and algorithm are verified.

scholarly journals Capacity in municipalities: Infrastructures, maintenance debts and ways of overcoming a run-to-failure mentality

2021 ◽  
pp. 026909422110304
Author(s):  
Jens Alm ◽  
Alexander Paulsson ◽  
Robert Jonsson
Keyword(s):  
Economies Of Scale ◽  
Heavy Traffic ◽  
Road Networks ◽  
Large Degree ◽  
Welfare States ◽  
The Road ◽  
Technical Capacity ◽  
Multidimensional Concept ◽  
Sewage Systems ◽  
Road Segments

There is a growing maintenance debt of ageing and critical infrastructures in many municipalities in European welfare states. In this article, we use the multidimensional concept of local capacity as a point of departure to analyse how and in what ways Swedish municipalities work with the routine maintenance of infrastructures, including municipal road networks as well as water and sewage systems. For the road networks, maintenance is generally outsourced to contractors and there is also a large degree of tolerance for various standards on different road segments within and between the municipalities. Less used road segments are not as prioritised as those with heavy traffic. For the water and sewage systems, in-house technical capacity is needed as differences in water quality are not tolerated. Economies of scale mean that in-house capacity is translated into the creation of inter-municipal bodies. As different forms of capacities tend to reinforce each other, municipal capacity builds up over time in circular movements. These results add knowledge to current research by pointing to the ways municipalities are overcoming a run-to-failure mentality by building capacity to pay off the infrastructural maintenance debt.

scholarly journals Design of Optimal Rainfall Monitoring Network Using Radar and Road Networks

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 378
Author(s):  
Taeyong Kwon ◽  
Seongsim Yoon ◽  
Sanghoo Yoon
Keyword(s):  
Road Networks ◽  
Monitoring Network ◽  
Conditional Entropy ◽  
Radar Data ◽  
Disaster Risk ◽  
Water Levels ◽  
The Road ◽  
Dam Operation ◽  
A Site ◽  
High Degree

Uncertainty in the rainfall network can lead to mistakes in dam operation. Sudden increases in dam water levels due to rainfall uncertainty are a high disaster risk. In order to prevent these losses, it is necessary to configure an appropriate rainfall network that can effectively reflect the characteristics of the watershed. In this study, conditional entropy was used to calculate the uncertainty of the watershed using rainfall and radar data observed from 2018 to 2019 in the Goesan Dam and Hwacheon Dam watersheds. The results identified radar data suitable for the characteristics of the watershed and proposed a site for an additional rainfall gauge. It is also necessary to select the location of the additional rainfall gauged by limiting the points where smooth movement and installation, for example crossing national borders, are difficult. The proposed site emphasized accessibility and usability by leveraging road information and selecting a radar grid near the road. As a practice result, the uncertainty of precipitation in the Goesan and Hwacheon Dam watersheds could be decreased by 70.0% and 67.9%, respectively, when four and three additional gauge sites were installed without any restriction. When these were installed near to the road, with five and four additional gauge sites, the uncertainty in the Goesan Dam and Hwacheon Dam watersheds were reduced by up to 71.1%. Therefore, due to the high degree of uncertainty, it is necessary to measure precipitation. The operation of the rainfall gauge can provide a smooth site and configure an appropriate monitoring network.

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