ENERGY CONSERVATION THROUGH VIDEO IMAGING AND ON-LINE TRAFFIC MONITORING. FINAL REPORT
This report presents and proposes the use of the Autoscope and its accompanying Autoscope vehicle detection and measures of effectiveness (MOE) data collection programs as a viable option for real time traffic monitoring and analysis of intersections and highway segments. The MOE algorithms presented in this report were tested at three test sites. The MOE data obtained from the test sites were validated using manual methods. The results are encouraging, showing an average error of about 10% in MOE estimates obtained during congested traffic flow conditions. Section 1 of this report provides an introduction. In section 2, basic traffic flow definitions and notational conventions are provided. In section 3, a background to the MOE collection problem and current MOE collection techniques are presented. The current vehicle detection instrumentation available to traffic engineers is briefly described in section 4. In section 5, the components of the vehicle detection and MOE collection instrumentation presented in this report are discussed. The proposed MOE collection algorithms and methodology are presented in section 6. Section 7 contains the testing and validation results. Finally, in section 8, conclusions from the test results are presented.
University of Minnesota, MinneapolisDepartment of Civil and Mineral Engineering, 122 Civil and Mineral Engineering Building
Minneapolis, MN United States 55455-0220
- Pettersson, A
- Michalopoulos, P
- Publication Date: 1993-6
- Features: Appendices; Figures; References; Tables;
- Pagination: 124 p.
- TRT Terms: Algorithms; Energy conservation; Measures of effectiveness; Traffic surveillance; Validation; Vehicle detectors; Video imaging detectors
- Old TRIS Terms: Test results
- Subject Areas: Energy; Environment; Highways; Operations and Traffic Management; I73: Traffic Control;
- Accession Number: 00667770
- Record Type: Publication
- Files: TRIS
- Created Date: Oct 28 1994 12:00AM