A micro-simulation model system of departure time using a perception updating model under travel time uncertainty. Ettema, D., Tamminga, G., Timmermans, H., & Arentze, T. Transportation Research Part A: Policy and Practice, 39(4):325--344, May, 2005.
A micro-simulation model system of departure time using a perception updating model under travel time uncertainty [pdf]Paper  doi  abstract   bibtex   
Existing microscopic traffic models have often neglected departure time change as a possible response to congestion. In addition, they lack a formal model of how travellers base their daily travel decisions on the accumulated experience gathered from repetitively travelling through the transport network. This paper proposes an approach to account for these shortcomings. A micro-simulation approach is applied, in which individuals base their consecutive departure time decisions on a mental model. The mental model is the outcome of a continuous process of perception updating according to principles of reinforcement learning. Individuals' daily travel decisions are linked to the traffic simulator SIAS-PARAMICS to create a simulation system in which both individual decision-making and system performance (and interactions between these two levels) are adequately represented. The model is applied in a case study that supports the feasibility of this approach.
@article{ettema_micro-simulation_2005,
	title = {A micro-simulation model system of departure time using a perception updating model under travel time uncertainty},
	volume = {39},
	issn = {0965-8564},
	url = {Ettema.2005.TR-A.39.pdf},
	doi = {10.1016/j.tra.2004.12.002},
	abstract = {

Existing microscopic traffic models have often neglected departure time change as a possible response to congestion. In addition, they lack a formal model of how travellers base their daily travel decisions on the accumulated experience gathered from repetitively travelling through the transport network. This paper proposes an approach to account for these shortcomings. A micro-simulation approach is applied, in which individuals base their consecutive departure time decisions on a mental model. The mental model is the outcome of a continuous process of perception updating according to principles of reinforcement learning. Individuals' daily travel decisions are linked to the traffic simulator {SIAS-PARAMICS} to create a simulation system in which both individual decision-making and system performance (and interactions between these two levels) are adequately represented. The model is applied in a case study that supports the feasibility of this approach.},
	number = {4},
	journal = {Transportation Research Part A: Policy and Practice},
	author = {Dick Ettema and Guus Tamminga and Harry Timmermans and Theo Arentze},
	month = may,
	year = {2005},
	keywords = {Departure time choice,micro-simulation},
	pages = {325--344}
}
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