基于駕駛行為的VMS交通誘導(dǎo)信息的優(yōu)化研究
[Abstract]:In recent years, with the rapid development of social economy and rising living standard in China, the number of cars has been increasing year by year. The rapid growth of vehicle ownership not only brings convenience to people's travel, but also leads to the emergence of urban traffic congestion. In this paper, Revealed Preference,RP survey and Stated Preference,SP survey are used to analyze the influencing factors of the driver's attention to variable information tagging (Variable Massage Signs,VMS), and to excavate the factors that affect the driver's path choice behavior. Based on the mechanism of the influence of VMS information on the path selection behavior of travelers, the design of VMS information on the variable information board is optimized to induce the driver route selection more effectively, and finally to alleviate the increasingly serious traffic congestion. In this study, the VMS information of urban roads is optimized with the second ring of Xi'an city. First of all, eight independent variables are selected from four aspects of driver's personal attributes, travel characteristics, VMS information release form and content to construct the orderly Logit model and partial advantage ratio model of the driver's attention to VMS information. The factors that significantly affect the attention of drivers to VMS information are analyzed. The advantages and disadvantages of the ordered Logit model and the partial dominance ratio model are analyzed by comparing the test indexes. Elastic analysis was used to quantitatively analyze the influence of significant influencing factors on driver's attention to VMS information. Taking the attention of the drivers on Xi'an city road to the VMS information on the second ring variable information board as an example, the empirical analysis is carried out. Secondly, 11 variables are selected from the driver's personal attributes, travel characteristics and road information attributes to construct the binomial Logit model of driver's path selection, and the Jackknife and Bootstrap techniques are introduced to further improve the accuracy of the Logit model. The classification discusses whether to make a detour in the publication of VMS information, the congestion time and the reason of congestion, and the influence of the distribution form and update frequency of VMS information on the driver's path choice. Taking the driver's choice of route choice on the second Ring Road of Xi'an as an example, the empirical analysis is carried out. Finally, 16 independent variables are selected from five aspects: personal attributes of driver, travel characteristics, travel weather, road condition information attributes and information publishing color to construct multi-item Logit model and nested Logit model for optimizing VMS information. The advantages and disadvantages of multi-item Logit model and nested Logit model are analyzed by comparing the test indexes. By means of elastic analysis, the degree of drivers' preference for VMS information was analyzed quantitatively. Taking the preference of drivers on Xi'an city road to the VMS information on the variable information board of the second ring of Xi'an city as an example, the empirical analysis is carried out.
【學(xué)位授予單位】:長(zhǎng)安大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類(lèi)號(hào)】:U495
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