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Title:Field Evaluation of Smart Sensor Vehicle Detectors at Railroad Grade Crossings���Volume 4: Performance in Adverse Weather Conditions
Author(s):Medina, Juan C.; Benekohal, Rahim F.
Subject(s):microwave radar vehicle detection
Wavetronix Matrix
railroad grade crossing
inductive loop
false call
missed call
stuck-on call
dropped call
Abstract:The performance of a microwave radar system for vehicle detection at a railroad grade crossing with quadrant gates was evaluated in adverse weather conditions: rain (light and torrential), snow (light and heavy), dense fog, and wind. The first part of this report compares the results of the modified system setup in adverse weather conditions with those from good weather conditions (as presented in Volume 3 of this study). Then, the results of a re-modified system setup were compared to the results for the modified system setup in good and adverse weather conditions. The re-modification was in response to increased detection errors in adverse weather conditions. With the modified setup, system performance was sensitive to the adverse weather conditions. In torrential rain, false calls increased to 24.82%–27.08% (e.g., May 28 and June 1) when there was some traffic on the crossing. However, when there was torrential rain but only one vehicle (e.g., May 31) or no traffic flow (e.g., June 10), the radar units generated 15 false calls on each of those 2 days. For all heavy snow datasets combined, missed calls by a single radar unit and by the two radar units working as a combined unit (i.e., systemwide) represented 13.51% and 11.66% of the loop calls, respectively. The most severe snow effects were found during freezing rain/ice. In dense fog, false calls increased to 11.58%, and all false calls were generated when the gates were moving or in the down position. Wind did not affect system performance, and the errors were similar to those in good weather conditions. With the re-modified setup, the frequency of errors in heavy rain and heavy snow conditions was reduced and system performance was similar to the good weather, light rain, and light snow conditions. In heavy rain, false calls in the re-modified setup were reduced to 2.6% compared with 30.5% in the modified setup. This reduction was the result of a significant decrease in the false calls generated without objects in the crossing. The re-modified setup eliminated the systemwide missed calls in heavy snow. The re-modified setup also reduced the false calls to less than 1% in good weather, light rain, and light snow conditions and practically had no missed, stuck-on, or dropped calls. Results indicate that re-modifications improved the performance of detection system.
Issue Date:2015-01
Publisher:Illinois Center for Transportation/Illinois Department of Transportation
Citation Info:Medina, Juan C., and Rahim F. Benekohal. 2015. Field Evaluation of Smart Sensor Vehicle Detectors at Railroad Grade Crossings—Volume 4: Performance in Adverse Weather Conditions. A report of the findings of ICT-R27-095. Illinois Center for Transportation Series No. 15-002. Research Report No. FHWA-ICT-15-002. Illinois Center for Transportation, Rantoul, IL
Series/Report:Illinois Center for Transportation Series No. 15-002
Genre:Technical Report
Type:Text
Language:English
URI:http://hdl.handle.net/2142/74922
ISSN:0197-9191
Sponsor:Illinois Department of Transportation, R27-095
Rights Information:No restrictions. This document is available to the public through the National Technical Information Service, Springfield, Virginia 22161.
Date Available in IDEALS:2015-04-21


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