This study models and analyzes the dynamic interaction between route choice and prescriptive information on a degradable network. The predictively prescriptive information is first explicitly modeled based on travelers’ behavior and historical data. Its accuracy is then dynamically measured to adjust the information compliance rate based on travelers’ expectations and experiences. Finally, a logit function is adopted to describe travelers’ route choice. Based on the proposed model, the dynamic interaction between route choice and prescriptive information on a degradable network is investigated by theoretical analyses and numerical experiments, which provides insights for the design and operation of advanced traveler information systems and traffic management.
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