Shortest path problem considering on-time arrival probability

Nie, Yu; Wu, Xing

doi:10.1016/j.trb.2009.01.008

Cited by 279 publications

(169 citation statements)

References 33 publications

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“…Mcginty et al first put forward the concept of "path quality" and thought that path quality should be considered in the optimal path selection [9]. Nie et al presented the concept of "reliable path" which holds that the reliable path should be one that can guarantee the arrival on time [10]. Choi et al introduced the concept of "driver orientation" and chose the appropriate path as the optimal path [11].…”

Section: Related Workmentioning

confidence: 99%

Application of Angle Related Cost Function Optimization for Dynamic Path Planning Algorithm

et al. 2018

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Abstract:In recent years, Intelligent Transportation Systems (ITS) have developed a lot. More and more sensors and communication technologies (e.g., cloud computing) are being integrated into cars, which opens up a new design space for vehicular-based applications. In this paper, we present the Spatial Optimized Dynamic Path Planning algorithm. Our contributions are, firstly, to enhance the effective of loading mechanism for road maps by dividing the connected sub-net, and building a spatial index; and secondly, to enhance the effect of the dynamic path planning by optimizing the search direction. We use the real road network and real-time traffic flow data of Karamay city to simulate the effect of our algorithm. Experiments show that our Spatial Optimized Dynamic Path Planning algorithm can significantly reduce the time complexity, and is better suited for use as a real-time navigation system. The algorithm can achieve superior real-time performance and obtain the optimal solution in dynamic path planning.

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Section: Related Workmentioning

confidence: 99%

Application of Angle Related Cost Function Optimization for Dynamic Path Planning Algorithm

et al. 2018

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“…Other models include minimizing a combination of expected travel costs and the penalty for violation of the time windows (Russell and Urban, 2008;Tas et al, 2013Tas et al, , 2014. Notably, routing models that deal with uncertainty often pose significant computational challenges compared to their deterministic counterparts (see for instance, Nikolova et al, 2006;Nie and Wu, 2009;Kosuch and Lisser, 2009). …”

Section: Related Workmentioning

confidence: 99%

Routing Optimization Under Uncertainty

Jaillet

Sim

2016

Operations Research

118

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We consider a class of routing optimization problems under uncertainty in which all decisions are made before the uncertainty is realized. The objective is to obtain optimal routing solutions that would, as much as possible, adhere to a set of specified requirements after the uncertainty is realized. These problems include finding an optimal routing solution to meet the soft time window requirements at a subset of nodes when the travel time is uncertain, and sending multiple capacitated vehicles to different nodes to meet the customers' uncertain demands. We introduce a precise mathematical framework for defining and solving such routing problems. In particular, we propose a new decision criterion, called the Requirements Violation (RV) Index, which quantifies the risk associated with the violation of requirements taking into account both the frequency of violations and their magnitudes whenever they occur. The criterion can handle instances when probability distributions are known, and ambiguity, when distributions are partially characterized through descriptive statistics such as moments information. We develop practically efficient algorithms involving Benders decomposition to find the exact optimal routing solution in which the RV Index criterion is minimized, and give numerical results from several computational studies that show the attractive performance of the solutions.

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“…Ying [11] presented a reliable routing algorithm with real time and historical information. Nie and Wu [12] studied the problem of finding a prior shortest path to guarantee a given likelihood of arriving on time in a stochastic network. Chen et al [13] proposed an efficient algorithm for finding a risk-averse path for users in autonomous vehicle navigation systems.…”

Section: Literature Reviewmentioning

confidence: 99%

The Global Optimal Algorithm of Reliable Path Finding Problem Based on Backtracking Method

Shen

Shao

Zhang

et al. 2017

Mathematical Problems in Engineering

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There is a growing interest in finding a global optimal path in transportation networks particularly when the network suffers from unexpected disturbance. This paper studies the problem of finding a global optimal path to guarantee a given probability of arriving on time in a network with uncertainty, in which the travel time is stochastic instead of deterministic. Traditional path finding methods based on least expected travel time cannot capture the network user's risk-taking behaviors in path finding. To overcome such limitation, the reliable path finding algorithms have been proposed but the convergence of global optimum is seldom addressed in the literature. This paper integrates the -shortest path algorithm into Backtracking method to propose a new path finding algorithm under uncertainty. The global optimum of the proposed method can be guaranteed. Numerical examples are conducted to demonstrate the correctness and efficiency of the proposed algorithm.

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Shortest path problem considering on-time arrival probability

Cited by 279 publications

References 33 publications

Application of Angle Related Cost Function Optimization for Dynamic Path Planning Algorithm

Application of Angle Related Cost Function Optimization for Dynamic Path Planning Algorithm

Routing Optimization Under Uncertainty

The Global Optimal Algorithm of Reliable Path Finding Problem Based on Backtracking Method

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