Optimal speed detector density for the network with travel time information |
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| Institution: | 1. Department of Pediatrics, Shaare-Zedek Medical Center, and Pediatric Specialist Clinics, Clalit Health services, Jerusalem, Israel;2. Department of Obstetrics and Gynecology, Hadassah-Hebrew University Medical Center, Jerusalem, Israel;3. Medical Data Unit, Clalit Health services, Jerusalem, Israel;4. School of Medicine, Technion, Haifa, Israel;5. Department of Pediatrics and Pediatric Endocrine Unit, Hadassah-Hebrew University Medical Center, Jerusalem, Israel.;1. Department of Endocrinology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow 226014, India;2. Biostatistics and Health Informatics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow 226014, India;1. International Neurologic & Psychiatric Epidemiology Program, Department of Neurology & Ophthalmology, Michigan State University, 909 West Fee Road, Room 324, East Lansing, MI 48824, USA;2. Department of Internal Medicine, University of Zambia School of Medicine, Lusaka, Zambia, Nationalist Road, P.O. Box 50110, Lusaka, Zambia;3. Department of Neurology, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY 14642, USA;4. Vanderbilt Institute for Global Health, Vanderbilt University Medical Center, 2525 Westend- Suite 725, Nashville, TN 37203, USA;5. Department of Neurology, Vanderbilt University Medical Center, A-0118 Medical Center North, Nashville, TN 37203, USA;6. Epilepsy Care Team, Chikankata Health Services, Mazabuka, Zambia |
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| Abstract: | In the expressway network, detectors are installed on the links for detecting the travel time information while the predicted travel time can be provided by the route guidance system (RGS). The speed detector density can be determined to influence flow distributions in such a way that the precision of the travel time information and the social cost of the speed detectors are optimized, provided that each driver chooses the minimum perceived travel time path in response to the predicted travel time information. In this paper, a bilevel programming model is proposed for the network with travel time information provided by the RGS. The lower-level problem is a probit-based traffic assignment model, while the upper-level problem is to determine the speed detector density that minimizes the measured travel time error variance as well as the social cost of the speed detectors. The sensitivity analysis based algorithm is proposed for the bilevel programming problem. Numerical examples are provided to illustrate the applications of the proposed model and of the solution algorithm. |
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