Using modeling and simulation methods, the driver\u27s route choice behavior under guidance information is explored based on the combination of the decision field theory (DFT) and Bayesian theory. First, based on the Bayesian theory, a road condition dynamic updating model is presented in light of the guidance information and the driver\u27s previous travel experiences. Then, the route choice behavior model under guidance information is formed by the fusion of the process-oriented vehicle dynamic route choice model and the road condition dynamic updating model. The developed model describes a driver\u27s propensity to comply with received guidance information in terms of the interaction between perceived unreliability of the information, hi...
Abstract: Generally speaking, drivers ’ route choice is a fuzzy problem. However, if drivers’ habitu...
In recent years, a broad array of disciplines (psychology, economics, marketing, public policy and t...
Driver behaviour models that can be used to dynamically estimate or predict the degree of drivers' c...
Intelligent Transportation Systems (ITS) applications require a thorough understanding of drivers' r...
AbstractTraveller route choice behaviour is influenced by many uncertain factors, which include both...
This paper presents an agent-based approach to modelling individual driver behaviour under the in-fl...
Accurate route choice modeling is one of the most important aspects when predicting the effects of t...
AbstractIn previous research, a route choice behavior model was constructed using trial and error ty...
A model of driver's route choice behavior under advanced traveler information system (ATIS) is devel...
The commonly proposed dynamic traffic assignment models for the real-time operational control of lar...
Modeling route choice behavior is problematic, but essential to appraise travelers' perceptions of r...
AbstractModeling route choice behavior is problematic, but essential to appraise travelers' percepti...
Existing common route choice models are based on random utility theory, which follows the maximum ut...
Abstract: This paper discusses how to consider the en-route choices in utility-based route choice mo...
AbstractIn this research, route choice behavior is treated as a two-stage process consisting of a ch...
Abstract: Generally speaking, drivers ’ route choice is a fuzzy problem. However, if drivers’ habitu...
In recent years, a broad array of disciplines (psychology, economics, marketing, public policy and t...
Driver behaviour models that can be used to dynamically estimate or predict the degree of drivers' c...
Intelligent Transportation Systems (ITS) applications require a thorough understanding of drivers' r...
AbstractTraveller route choice behaviour is influenced by many uncertain factors, which include both...
This paper presents an agent-based approach to modelling individual driver behaviour under the in-fl...
Accurate route choice modeling is one of the most important aspects when predicting the effects of t...
AbstractIn previous research, a route choice behavior model was constructed using trial and error ty...
A model of driver's route choice behavior under advanced traveler information system (ATIS) is devel...
The commonly proposed dynamic traffic assignment models for the real-time operational control of lar...
Modeling route choice behavior is problematic, but essential to appraise travelers' perceptions of r...
AbstractModeling route choice behavior is problematic, but essential to appraise travelers' percepti...
Existing common route choice models are based on random utility theory, which follows the maximum ut...
Abstract: This paper discusses how to consider the en-route choices in utility-based route choice mo...
AbstractIn this research, route choice behavior is treated as a two-stage process consisting of a ch...
Abstract: Generally speaking, drivers ’ route choice is a fuzzy problem. However, if drivers’ habitu...
In recent years, a broad array of disciplines (psychology, economics, marketing, public policy and t...
Driver behaviour models that can be used to dynamically estimate or predict the degree of drivers' c...