Influence of Experience on Users’ Behaviour: A Day-to-Day Model for Route Choice Updating

Maio, M. L. De; Vitetta, Antonino; Watling, David

doi:10.1016/j.sbspro.2013.10.594

Cited by 8 publications

(2 citation statements)

References 32 publications

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“…Hence, this study can account for the effect of commuters' characteristics on departure time equilibrium. By altering the perception module, we can restore the individual differences in commuters' subjective perception (e.g., the subjective perception of travel time is considered one of the main elements that influence route choice [12]). We can also modify the cost valuation module by adding new factors or changing the process of calculating cost.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…To examine the effect of incentives on commuters' morning commute decision, Zhang et al [11] conducted an empirical study on the Beijing subway system and recommended two policies to reduce congestion during peak periods. With regard to morning commute modeling, Maio et al [12] presented a day-today route choice model to study the influence of experience on commuters' behavior. Further studies on day-to-day models in route choice behavior in response to previous travel experience can be found in Watling's work [13].…”

Section: Introductionmentioning

confidence: 99%

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Agent-Based Modeling and Simulation for the Bus-Corridor Problem in a Many-to-One Mass Transit System

Xie

Jia

et al. 2014

Discrete Dynamics in Nature and Society

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With the growing problem of urban traffic congestion, departure time choice is becoming a more important factor to commuters. By using multiagent modeling and the Bush-Mosteller reinforcement learning model, we simulated the day-to-day evolution of commuters' departure time choice on a many-to-one mass transit system during the morning peak period. To start with, we verified the model by comparison with traditional analytical methods. Then the formation process of departure time equilibrium is investigated additionally. Seeing the validity of the model, some initial assumptions were relaxed and two groups of experiments were carried out considering commuters' heterogeneity and memory limitations. The results showed that heterogeneous commuters' departure time distribution is broader and has a lower peak at equilibrium and different people behave in different pattern. When each commuter has a limited memory, some fluctuations exist in the evolutionary dynamics of the system, and hence an ideal equilibrium can hardly be reached. This research is helpful in acquiring a better understanding of commuter's departure time choice and commuting equilibrium of the peak period; the approach also provides an effective way to explore the formation and evolution of complicated traffic phenomena. Hindawi Publishing Corporation

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Section: Conclusion and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%