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

2017 ◽  
Vol 2017 ◽  
pp. 1-10
Author(s):  
Liang Shen ◽  
Hu Shao ◽  
Long Zhang ◽  
Jian Zhao
Keyword(s):  
Travel Time ◽  
Risk Taking ◽  
Optimal Algorithm ◽  
Optimal Path ◽  
Global Optimum ◽  
Path Finding ◽  
Shortest Path Algorithm ◽  
Global Optimal ◽  
Risk Taking Behaviors ◽  
Reliable Path

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 K-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.

scholarly journals Optimal Path Finding Method Study Based on Stochastic Travel Time

2013 ◽  
Vol 03 (04) ◽  
pp. 260-265 ◽  
Author(s):  
Zhanquan Sun ◽  
Weidong Gu ◽  
Yanling Zhao ◽  
Chunmei Wang
Keyword(s):  
Travel Time ◽  
Optimal Path ◽  
Path Finding ◽  
Finding Method ◽  
Stochastic Travel Time

Stochastic Multiclass Traffic Assignment with Consideration of Risk-Taking Behaviors

2008 ◽  
Vol 2085 (1) ◽  
pp. 111-123 ◽  
Author(s):  
Shan Di ◽  
Changxuan Pan ◽  
Bin Ran
Keyword(s):  
Travel Time ◽  
Risk Taking ◽  
Network Flows ◽  
Simulation Analysis ◽  
Transportation Network ◽  
Travel Times ◽  
Traffic Equilibrium ◽  
Travel Time Distribution ◽  
Log Normal ◽  
Risk Taking Behaviors

A study of the problem of predicting traffic flows under traffic equilibrium in a stochastic transportation network is presented. Travelers’ risk-taking behaviors are explicitly modeled with respect to probabilistic travel times. Traveling risks are quantified from the travel time distributions directly and are embedded in the route choice conditions. The classification of risk-neutral, risk-averse, and risk-prone travelers is based on their preferred traveling risks. The formulation of the model clarifies that travelers with different risk preferences have the same objective–to save travel time cost–though they may make different route choices. The proposed solution algorithm is applicable for networks with normal distribution link travel times theoretically. Further simulation analysis shows that it can also be applied to approximate the equilibrium network flows for other frequently used travel time distribution families: gamma, Weibull, and log-normal. The proposed model was applied to a test network and a medium-sized transportation network. The results demonstrate that the model captures travelers’ risk-taking behaviors more realistically and flexibly compared with existing stochastic traffic equilibrium models.

Risk-Taking Behaviors in Adolescents

1999 ◽  
Author(s):  
Kristin M. von Ranson ◽  
Susan L. Rosenthal
Keyword(s):  
Risk Taking ◽  
Risk Taking Behaviors

Adolescents’ Future Negative Time Perspective and Risk-Taking Behaviors: The Roles of Coping Styles and Self-Control

2020 ◽  
Author(s):  
Kai Dou ◽  
Ming-Chen Zhang ◽  
Yue Liang
Keyword(s):  
Risk Taking ◽  
Time Perspective ◽  
Longitudinal Design ◽  
Coping Styles ◽  
Future Time Perspective ◽  
Self Control ◽  
Total N ◽  
Negative Coping ◽  
Risk Taking Behaviors ◽  
Negative Time

The association between future time perspective and risk-taking behaviors has received extensive empirical attention. However, the underlying mechanism that links future negative time perspective to risk-taking behaviors are complex and not well-understood. To address this gap, we adopted a longitudinal design examined the association between FNTP and risk-taking behaviors, and the roles of coping styles and self-control in this association among Chinese adolescents (total N = 581, 46.3% females). Results showed that FNTP at wave 1 predicted risk-taking behavior at wave 3 via positive and negative coping styles at wave 2. Furthermore, adolescents with low self-control and used negative coping strategies prefer to engage in risk-taking behaviors as compared to their high self-control counterparts. Taken together, these research findings underscore the importance of considering influence of the future negative time perspective on adolescents’ risk-taking behaviors, and provided important implications for developing the preventions and interventions for reducing adolescents’ risk-taking behaviors.

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