Research On Route Choice Behaviors Under Random Disturbance Information Based On Information Feedback Mechanism

For predicting traffic conditions,formulating effective traffic travel strategies and laying out urban roads,the research on features of travelers routing behavior is required.In recent years,route-choice-behavior modeling has been one important aspect of transportation model.A reliable route choice model can help travelers choice route in real transporting,aiming at reducing their travel costs and mitigating traffic congestion.In the study of route choice behavior,randomness is an important characteristic.Random accidents being encountered by travelers during travelling are one of main reasons of changing travel costs.In addition,traveler’s route choice behavior is based on information feedback mechanisms,such as his own experience,real-time path information broadcast and so on.Based on experimental data of route choice behavior,this thesis studies the route choice behavior of travelers from the randomness during travel and the information feedback mechanism.The specific research contents are as follows:1.This thesis has completed the experiment of "route choice behavior under random perturbation information".Once experiment is divided into five groups,and each group contains 30 rounds.Random terms are added when travel time are calculated.The random terms of the five groups of experiments all obey the normal distribution with mean 0.The variances of the five groups of experiments were 0,1,10,100,and 1000.The characteristics of traveler’s route choice behavior are depicted by collecting and analyzing experimental data.2.This thesis studies the information feedback strategy in route choice behavior and draw a conclusion that the path information feedback will bring a positive effect to the traveler’s route choice.The cluster coefficient feedback strategy and weighted congestion coefficient feedback strategy are introduce here.Furthermore,we presents the cluster coefficient feedback strategy algorithm and proposes a weighted cluster coefficient feedback strategy.It is verified that the weighted cluster coefficient feedback strategy is superior to the other two feedback strategies.3.This thesis studies the route choice behavior of travelers under random perturbation information.We introduce the concept of random perturbed travel information.First,we study the characteristics of traveler’s route choice behavior under random perturbation information.Then we proposed a traffic transfer model.This model can distinguish out accurate budget flow transfer amount.The amount of traffic transfer combined with the data of the last trip can be used to estimate the path traffic of this trip.We verified the accuracy of the model by comparing with the experimental results.In summary,this thesis proposes a weighted cluster coefficient feedback strategy.This strategy can help travelers to be evenly distributed in the road network,which is conducive to improving traffic flow.Based on the experimental data,a traffic transfer model is proposed,which takes into account the random factors on the way and information feedback strategy,and can more effectively simulate real-life travel scenarios.Therefore,the path flow predicted by our model is more accurate.Travelers can review the road network in advance and make the optimal route choice behavior.This study can provide an important basis for the traveler’s route choice behavior,thereby reducing travel time and effectively evacuating traffic congestion.