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Simulation assessment of incident detection by cellular phone call-in programs
Authors:Mussa  Renatus N  Upchurch  Jonathan E
Institution:(1) Department of Civil Engineering, FAMU-FSU College of Engineering, 2525 Pottsdamer Street, Tallahassee, FL, 32310, USA, (E-mail;(2) Department of Civil and Environmental Engineering, University of Massachusetts at Amherst, Amherst, MA, 01003, USA (E-mail
Abstract:This research study was designed to assess by simulation the efficacy of incident detection by cellular phone call-in programs. The assessment was conducted by varying the proportion of drivers with cellular phones on the highway so as to mirror the cellular industry statistics that show a continued growth of ownership of cellular phones in the United States. An analytical model, which combined simulation and the limited field data available in the literature, was used to determine measures of effectiveness of the cellular phone-based detection system. The results showed that a cellular phone detection system offers fast incident detection times and higher detection rates for both shoulder and lane blocking incidents. For example, in moderate traffic flow (i.e. 1,550 vehicles per hour per lane), 90 percent of incidents blocking two lanes were detected in 1.5 minutes when the proportion of drivers with cellular phones was one out of 10 drivers, even with only 20 percent of them willing to report incidents. When the current proportion of cellular ownership, i.e. 1 out of 3, was used in the simulation, the detection time improved to 0.8 minutes. The simulation analysis of incident detection by cellular phones also showed that there is a direct relationship between the probability of detection and the detection time; that is, the specification of a higher detection rate resulted in slower detection times. This is in sharp contrast with the results of field study of automatic incident detection (AID) systems which demonstrated an inverse relationship between probability of detection and detection time. This revised version was published online in June 2006 with corrections to the Cover Date.
Keywords:cellular telephones  incident detection  simulation  traffic modeling  wireless communications
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