Travel Decision Model of Heterogeneous Commuters under Uncertain Environment

In order to better describe the commuter's travel decision-making behavior under different travel environment,heterogeneous commuters and types are defined,and the commuters are divided into three types,including conservative type,neutral type and adventure type,respectively,analysis on the travel environment supply and the travel environment demand.Suppose the travel demand obeys the gamma distribution and the capacity obeys the beta distribution,and the travel time function of different commuter type is deduced,the travel decision model based on the cumulative foreground theory is established.Analyze the example results,compared with the fluctuation of travel demand,the degradation of traffic capacity has a more significant impact on travel decision-making behavior;and different types of commuters cause different disturbances to travel decision-making behavior.

Analysis of the Impact of Their Travel Decisions Based on Public Perception of Air Quality -A Case of Shanghai

Based on air quality perception, researching through field survey forms on Shanghai＇ s public travel decisions, article give a comparative analysis and a descriptive statistics on survey data. The study found, different identity, qualifications, age, background of Shanghai＇ s Public perception to air quality perform a universal character, and the rate of concerning for air pollution is relatively high, but to air pollution, they lack of understanding of its essence. Shanghai＇s public have a large usage of mobile devices, the way of concerns for air quality shows a ＂move concern＂ feature. There is a certain influence of air quality on public＇s travel decisions, on the condition that public often go out and show their concern on air quality information.

Leave the expressway or not? Impact of dynamic information

This study investigates drivers＇ diversion decision behavior under expressway variable message signs that provide travel time of both an expressway route and a local street route. Both a conventional cross-sectional logit model and a mixed logit model are developed to model drivers＇ response to travel time information. It is based on the data collected from a stated preference survey in Shanghai, China. The mixed logit model captures the heterogeneity in the value of ＂travel time＂ and ＂number of traffic lights＂ and accounts for correlations among repeated choices of the same respondent. Results show that travel time saving and driving experience serve as positive factors, while the number of traffic lights on the arterial road, expressway use frequency, being a middle-aged driver, and being a driver of an employer-provided car serve as negative factors in diversion. The mixed logit model obviously outperforms the cross-sectional model in dealing with repeated choices and capturing heterogeneity regarding the goodness-of-fit criterion. The significance of standard deviations of random coefficients for travel time and number of traffic lights evidences the existence of hetero- geneity in the driver population. The findings of this study have implications for future efforts in driver behaviormodeling and advanced traveler information system assessment.