01043544

Component

https://doi.org/10.3141/2024-01

http://scholar.google.com...hang&publication_year=2007

A new approach to traffic data collection, known as link monitoring systems—systems that “mine” location data from existing infrastructure (such as cellular telephone networks or fleet management systems) to estimate link speeds and travel times—is emerging. In general, these systems are being developed and operated by private firms, which then seek to sell the data to transportation agencies. To make sound purchasing decisions, agencies must evaluate the quality of the data that they are considering purchasing. The research effort described in this paper developed and field-tested a link monitoring system evaluation procedure. This procedure is based on the use of state-of-the-art information technology resources, namely, geographic information systems and Global Positioning Systems (GPS), to provide a flexible, thorough, and fair evaluation methodology. The methodology consists of four steps. Step 1 is baseline data collection, which includes study site investigation, route design, and probe vehicle runs. Step 2 is data reduction, involving GPS data postprocessing, spatial processing, and travel time and link speed derivation. Step 3 is temporal match, and Step 4 deals with comparisons, including accuracy quantification and temporal traffic condition comparisons. The paper illustrates the procedure based on an evaluation of the Airsage link monitoring system in Hampton Roads, Virginia. In this evaluation, 147,000 GPS points that supported comparisons with over 1,000 link and time data records provided by the Airsage system were collected.

01088321

English

pp 1-7

2007

Transportation Research Record: Journal of the Transportation Research Board

9780309104517

Print

Figures (5) ; References (6) ; Tables (4)

Data collection; Data mining; Data quality; Data reduction; Geographic information systems; Global Positioning System; Information technology; Monitoring; Traffic data; Traffic surveillance

Hampton Roads (Virginia)

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

TRIS, TRB, ATRI

Feb 8 2007 4:58PM

• Adaptive Seasonal Time Series Models for Forecasting Short-Term Traffic Flow
• Bayesian Approach Based on Geographic Information System to Identify Hazardous Roadway Segments for Traffic Crashes
• Data Collection Based on Global Positioning System for Travel Time and Delay for Arterial Roadway Network
• Data Collection Time Intervals for Stochastic Short-Term Traffic Flow Forecasting
• Decision Support System for Predicting Traffic Diversion Impact Across Transportation Networks Using Support Vector Regression
• Evaluating Highway Capacity Investments Using a Geographic Information Systems-Based Tool: Trip-Based Full Marginal Cost Approach
• Forecasting of Short-Term Freeway Volume with v-Support Vector Machines
• Fuzzy Optimization Approach: Comparison with the Classical Optimization Method Using the Problem of Timing a Traffic Signal
• Methodology for Selection and Development of TransXML Schemas
• Quantum-Frequency Algorithm for Automated Identification of Traffic Patterns
• Transportation Asset Management and Visualization Using Semantic Models and Google Earth
• Visualizing and Analyzing Activities in an Integrated Space-Time Environment: Temporal Geographic Information System Design and Implementation
• Wavelet-Based Pavement Distress Image Edge Detection with À Trous Algorithm