01517582

Component

https://doi.org/10.3141/2443-05

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

Although average effective vehicle length (AEVL) has been recognized as one of the most popular methods for detecting data errors, how to set proper thresholds so as to prevent false alarms and missed detections remains a challenging ongoing issue. This study proposed a sequential screening algorithm that employed multiple comparisons with the best statistics to compare concurrently the estimated AEVLs between lanes and stations for assessment of the data quality of a target detector. With both the temporal and spatial information, the proposed method can reliably generate a confidence interval and determine whether the target detector is malfunctioning or in need of calibration. The proposed algorithm was tested with 2 weeks of detector data from Ocean City, Maryland. The analysis results demonstrate the effectiveness of the proposed sequential screening algorithm and its potential for field applications.

01548337

14-2214

English

pp 40–48

2014

Transportation Research Record: Journal of the Transportation Research Board

9780309295314

Print

Figures (10) ; References (22) ; Tables (4)

Algorithms; Automatic vehicle detection and identification systems; Classification; Data quality; Errors

Ocean City (Maryland)

Data and Information Technology; Highways; Operations and Traffic Management; I71: Traffic Theory; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Jan 27 2014 2:47PM

• 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 Detector Evaluation Based on Concepts of Traceability and Confidence Interval
• Vehicle Length Measurement and Length-Based Vehicle Classification in Congested Freeway Traffic