Evaluation of Traffic Data Collection Method

Abstract:

Traffic counts are one of the fundamental data sources for the Highway Performance Monitoring System (HPMS). Automatic Traffic Recorders (ATRs) are used to provide continuous traffic count coverage at selected locations to estimate annual average daily traffic (AADT). However, ATR data is often unavailable. This paper investigated the feasibility of using Video Detection System (VDS) technology when ATR data is not available. An Android Tablet-based manual traffic counting application was developed to acquire manual count based ground truth data. The performance of VDS was evaluated under various conditions including mounting styles, heights, and roadway offsets. The results indicated that VDS data presents reasonably accurate data, although the data exhibits more variability compared to ATR data.

• Periodical: Applied Mechanics and Materials (Volumes 764-765)
• Pages: 905-909
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.764-765.905
• Online since: May 2015
• Authors: Won Ho Suh*, James Anderson, Angshuman Guin, Michael Hunter
• Keywords: Automatic Traffic Recorder, Traffic Count, Traffic Data Collection, Video Detection System

References

[1] United Nations Economic Commission for Europe: Handbook on Statistics on Road Traffic, Methodology and Experience, United Nations Economic Commission for Europe (UNECE) – Transport Division (2007).

DOI: 10.18356/9789210013536c001

[2] J. Mergel: An Overview of Traffic Monitoring Programs in Large Urban Areas, Center for Transportation Information of Volpe National Transportation Systems Center (1997).

[3] G. Leduc: Road Traffic Data: Collection Methods and Applications. European Commission Joint Research Centre. Institute for Prospective Technological Studies (2008).

[4] K. Ahn, H. Rakha and D. Hill: Data Quality White Paper. Federal Highway Administration (2008).

[5] Federal Highway Administration: Traffic Data Quality Measurement (2004).

[6] Transportation Research Board: Traffic Monitoring Data Successful Strategies in Collection and Analysis, Transportation Research Circular EC120 (2007).

[7] E. Fekpe, D. Gopalakrishna and D. Middleton: Highway Performance Monitoring System Traffic Data for High-Volume Routes: Best Practices and Guidelines. Federal Highway Administration (2004).

[8] E. Minge, J. Kotzenmacher, and S. Peterson: Evaluation of Non-Intrusive Technologies for Traffic Detection. Minnesota Department of Transportation (2010).

[9] A. Rhodes, E. Smaglik, and D. Bullock: Vendor Comparison of Video Detection Systems. Purdue University, West Lafayette, IN (2006).

DOI: 10.5703/1288284313402

[10] J. Medina, R. Benekohal, and M. Chitturi: Evaluation of Video Detection Systems. Illinois Department of Transportation (2009).

[11] D. Middleton and R. Parker: Evaluation of Promising Vehicle Detection Systems, Texas Transportation Institute (2002).

[12] S. Birchfield, W. Sarasua, and N. Kanhere: Computer Vision Traffic Sensor for Fixed and Pan-Tilt-Zoom Cameras (2010).

[13] P. Hidas and F. Milthorpe: Traffic Counts for Strategic Transport Model Validation: What Counts?. Proceedings of the 32rd Australasian Transport Research Forum (ATRF) (2009).

[14] C. Toth, W. Suh, V. Elango, R. Sadana, A. Guin, M. Hunter, and R. Guensler: Tablet-Based Traffic Counting Application Designed to Minimize Human Error. Transportation Research Record: Journal of the Transportation Research Board, No. 2339 (2013).

DOI: 10.3141/2339-05