01506672

Component

https://doi.org/10.3141/2443-02

http://scholar.google.com...suji&publication_year=2014

Vehicle detectors are essential devices for advanced traffic management and information systems. Hence, the accuracy of traffic data from detectors is fundamentally important. When evaluating detectors, one uses a baseline data source that generates reference data. However, reference data also contain errors and uncertainties, albeit small ones. Nevertheless, little research has been performed to address the errors and uncertainties of reference data. This study proposed a new detector evaluation scheme to resolve that problem. The scheme takes errors and uncertainties of reference data into account for reliable detector evaluation. Moreover, the scheme applies the interval estimation technique, instead of the traditional point estimation, to present detector evaluation results. The suggested scheme was thoroughly verified by using the South Korea detector test bed, a verification that the scheme produced reliable detector evaluation results.

01548337

14-0189

English

pp 12–20

2014

Transportation Research Record: Journal of the Transportation Research Board

9780309295314

Print

Figures (4) ; References (21) ; Tables (5)

Acceptance tests; Accuracy; Confidence intervals; Data quality; Traffic data; Traffic surveillance; Vehicle detectors

Data and Information Technology; Highways; Operations and Traffic Management; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Jan 27 2014 2:10PM

• Algorithm for Detector-Error Screening on Basis of Temporal and Spatial Information
• Application of Seasonal Adjustment Factors to Subsequent Year Data
• Automated Analysis of Pedestrians’ Nonconforming Behavior and Data Collection at an Urban Crossing
• Effect of Traffic Load Input Level on Mechanistic–Empirical Pavement Design
• Estimating Spatially and Temporally Continuous Bicycle Volumes by Using Sparse Data
• Estimation of Annual Average Daily Bicycle Traffic with Adjustment Factors
• Exploring Bias in Traffic Data Aggregation Resulting from Transition of Traffic States
• Hybrid Prediction Approach Based on Weekly Similarities of Traffic Flow for Different Temporal Scales
• Identification of Network Sensor Locations for Estimation of Traffic Flow
• Institutionalizing Bicycle and Pedestrian Monitoring Programs in Three States
• Process to Determine Locations for Motorcycle Counts
• Reidentification of Trucks on Basis of Axle-Spacing Measurements to Facilitate Analysis of Weigh-in-Motion Accuracy
• Semiautomated Tool for Extraction of Microlevel Traffic Data from Videographic Survey
• Software-Based Vehicle Reidentification with Existing Loop Infrastructure
• Vehicle Length Measurement and Length-Based Vehicle Classification in Congested Freeway Traffic