scholarly journals A behavioral analysis on relationship between individuals' travel behavior and residential choice behavior

2007 ◽  
Vol 24 ◽  
pp. 481-487 ◽  
Author(s):  
Satoshi FUJII ◽  
Yusuke SOMEYA
Keyword(s):  
Travel Behavior ◽  
Choice Behavior ◽  
Behavioral Analysis ◽  
Residential Choice

Impaction of Travel Behavior and Degree of Business District Prosperity on Shopping

2014 ◽  
Vol 488-489 ◽  
pp. 1426-1429
Author(s):  
Ming Wei Liu ◽  
Shou Qi Cao ◽  
Li Zhen Zhang ◽  
Cheng Ming Chen
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
Choice Behavior ◽  
Store Choice ◽  
Media Markets ◽  
Business District

Three Media-Markets located in Shanghai have been studied the research in this area to quantitatively analysis how transportation factors such as travel time, transportation method, distance, cost and the degree of business districts prosperity affect store choice behavior.

scholarly journals Evolution dynamic of the expressway toll-free policy impact on the mode choice in a bimodal transportation network during holidays

2017 ◽  
Vol 9 (7) ◽  
pp. 168781401771108 ◽  
Author(s):  
Xiao-Mei Lin ◽  
Chun-Fu Shao ◽  
Jian-Pei Qian ◽  
Ying-Da Zhang
Keyword(s):  
Travel Behavior ◽  
Choice Behavior ◽  
Evolutionary Dynamics ◽  
Transportation Network ◽  
Mode Choice ◽  
Evolutionary Model ◽  
Travel Distance ◽  
Limited Attention ◽  
Mode Split ◽  
Implementation Effect

The implementation of expressway toll-free policy during holidays in China has caused serious congestion and frequent accidents on expressways. Many studies have explored the policy’s macroscopic outcome and its countermeasures for policy managers, while limited attention has been paid to the influence mechanism of the policy on the individuals’ travel behavior, especially the mode choice behavior. More insight into the dynamic effects of individuals reacting to policy measure is needed. This study aims at analyzing the adaption progress of the individual’s mode choice behavior and estimating the time-varying influence of the traffic policy on the mode split. With assumptions travelers’ adapting behavior conform to the inertia and myopia principles, a Logit dynamic evolutionary model for mode choice is proposed. A unique globally stable equilibrium state for the model is derived with the strict mathematical analysis. As an application, the influence of the expressway toll-free policy on mode split is evaluated. The travel cost structure, the sensitivity of the travel distance and traffic supply, and the evolutionary dynamics of the mode split are analyzed in scenarios with and without the expressway toll-free policy. The result indicates that travel distance and network’s total supply amount remarkably affect the implementation effect of the policy.

scholarly journals ANALYSIS OF RESIDENTIAL CHOICE BEHAVIOR BASED ON CLASSIFICATION OF RESIDENTIAL PREFERENCE

2011 ◽  
Vol 67 (6) ◽  
pp. II_1-II_10 ◽  
Author(s):  
Yusuke NISHIYAMA ◽  
Jun NAKATANI ◽  
Kiyo KURISU ◽  
Toshiya ARAMAKI ◽  
Keisuke HANAKI
Keyword(s):  
Choice Behavior ◽  
Residential Choice ◽  
Residential Preference ◽  
Behavior Based

Survey and Model Development of Household Residential Choice Behavior with Group Decision-Making Mechanisms

2006 ◽  
Vol 41 (0) ◽  
pp. 134-134
Author(s):  
Junyi Zhang ◽  
Akimasa Fujiwara ◽  
Masashi Kuwano ◽  
Yoriyasu Sugie ◽  
Backjin Lee
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Choice Behavior ◽  
Group Decision ◽  
Model Development ◽  
Residential Choice

Drivers’ Route Choice Behavior: Analysis by Data Mining Algorithms

2002 ◽  
Vol 1807 (1) ◽  
pp. 59-66 ◽  
Author(s):  
Toshiyuki Yamamoto ◽  
Ryuichi Kitamura ◽  
Junichiro Fujii
Keyword(s):  
Data Mining ◽  
Travel Behavior ◽  
Choice Behavior ◽  
Route Choice ◽  
Discrete Choice Models ◽  
Travel Times ◽  
Production Rules ◽  
Route Choice Behavior ◽  
Data Mining Algorithms ◽  
C4.5 Algorithm

Decision trees and production rules, which are among the methods used in knowledge discovery and data mining, are applied to investigate drivers’ route choice behavior. These methods have an advantage over artificial neural networks, another data mining method often used in analysis of travel behavior: they facilitate determination of the relationships between the explanatory variables and the choice. Specifically, the C4.5 algorithm, which produces a decision tree and a set of production rules from the tree, is applied here. Two surveys were carried out to collect data on drivers’ route choice behavior between two alternative routes on expressway networks. The two data sets include the expected minimum, maximum, and average travel times along each alternative route, as indicated by the respondent as well as his or her sociodemographic attributes. The results of the analyses suggest that different expected travel times influence route choice in different cases and that a maximum or average travel time determines route choice in some cases regardless of other attributes. The results of a comparison analysis between the C4.5 algorithm and discrete choice models indicate the superior ability offered by the former in representing drivers’ route choice.

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