期刊
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
卷 108, 期 -, 页码 49-73出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trc.2019.09.004
关键词
Traffic count locations; OD demand estimation; OD demand covariance; Bi-objective optimization
资金
- National Natural Science Foundation of China [71671184]
- Research Grants Council of the Hong Kong Special Administrative Region, China [PolyU 152628/16E, R5029-18]
Vehicular traffic between different Origin-Destination (OD) pairs for a typical hourly period may statistically correlate with each other. The covariance mainly generated from the daily variation of travel patterns, network topology, and trip chaining activities of household members can be particularly high during the morning peak hour. With the increasing attention on the OD demand variance and covariance in stochastic road networks, a new criterion is proposed in this paper for measuring the estimation accuracy of OD demand covariance. The mathematical properties of this proposed criterion are analyzed to better understand the relationship between the estimation errors of mean and covariance of OD demands. This paper aims to investigate how to optimize the traffic count locations for minimizing the weighted maximum deviation of estimated mean and covariance of OD demands from the true values. To consider the effects of stochastic OD demands on the traffic count location problem in the proposed model, link choice proportions are regarded as stochastic variables and updated by an adapted traffic flow simulator in this study. Both the weighted-sum approach and bi-objective approach are examined with the adaption of the firefly algorithm (FA) to solve the single-objective and bi-objective problems. Numerical examples are presented to demonstrate the effects, with and without considering the covariance of the OD demands for the optimization of traffic count locations.
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