Evaluation of Traffic Data Collection Method

Suh, Won Ho; Anderson, J. M.; Guin, Angshuman; Hunter, Michael

doi:10.4028/www.scientific.net/amm.764-765.905

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…Manual counting is considered the most accurate method of traffic counting [15] [16]. Trained individuals conduct the count with or without the help of technology, which may become prone to error [17] [18] [19]. A few research has been conducted to evaluate the error of manual counts.…”

Section: Literature Reviewmentioning

confidence: 99%

Accuracy Assessment and Guidelines for Manual Traffic Counts from Pre-Recorded Video Data

Majumder,

Wilmot

2023

JTTs

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Traffic count is the fundamental data source for transportation planning, management, design, and effectiveness evaluation. Recording traffic flow and counting from the recorded videos are increasingly used due to convenience, high accuracy, and cost-effectiveness. Manual counting from pre-recorded video footage can be prone to inconsistencies and errors, leading to inaccurate counts. Besides, there are no standard guidelines for collecting video data and conducting manual counts from the recorded videos. This paper aims to comprehensively assess the accuracy of manual counts from pre-recorded videos and introduces guidelines for efficiently collecting video data and conducting manual counts by trained individuals. The accuracy assessment of the manual counts was conducted based on repeated counts, and the guidelines were provided from the experience of conducting a traffic survey on forty strip mall access points in Baton Rouge, Louisiana, USA. The percentage of total error, classification error, and interval error were found to be 1.05 percent, 1.08 percent, and 1.29 percent, respectively. Besides, the percent root mean square errors (RMSE) were found to be 1.13 percent, 1.21 percent, and 1.48 percent, respectively. Guidelines were provided for selecting survey sites, instruments and timeframe, fieldwork, and manual counts for an efficient traffic data collection survey.

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Section: Literature Reviewmentioning

confidence: 99%

Accuracy Assessment and Guidelines for Manual Traffic Counts from Pre-Recorded Video Data

Majumder,

Wilmot

2023

JTTs

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“…As more sensor data becomes available, it opens new opportunities for various transportation analysis techniques including traffic data acquisition using image recognition technology, (23)(24)(25) real-time travel time data collection, (26)(27)(28)(29)(30) and monitoring infrastructure or workers in construction areas. (31,32) In this paper, we present the application of real-time sensor data to the evaluation of the performance of ad hoc distributed traffic simulation.…”

Section: Conclusion and Limitationsmentioning

confidence: 99%

Application of Real-time Sensor Data to Evaluation of Performance of Ad Hoc Distributed Traffic Simulation

Suh¹

2019

Sensors and Materials

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Recent advancements in sensor and wireless communication technologies are creating new opportunities to effectively exploit real-time traffic data. Onboard sensors on vehicles collect real-time traffic data and simulate traffic states in a distributed fashion. A local transportation management center coordinates the overall simulation with an optimistic execution technique. In this paper, we presents a study of the application of real-time sensor data to the evaluation of the performance of ad hoc distributed traffic simulation. In this study, the real-time field data would be replaced with the streaming sensor data in a field implementation. Two scenarios were investigated to evaluate the performance. The first scenario examined how the system adequately captures changes in traffic conditions when the sensor reports a sudden increase in traffic volume and decreases under uncongested traffic conditions. The second scenario investigated how well the ad hoc distributed traffic simulation operates when a traffic incident occurs. The proposed ad hoc distributed traffic simulation with real-time sensor data was found to be capable of capturing dynamically changing traffic conditions in both the peak traffic and incident scenarios. In both scenarios, the prediction accuracy drops when the traffic state changes. However, the ad hoc approach appears generally capable of capturing dynamically changing traffic conditions when the real-time field sensor data are available.

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Evaluation of Traffic Data Collection Method

Cited by 2 publications

References 5 publications

Accuracy Assessment and Guidelines for Manual Traffic Counts from Pre-Recorded Video Data

Accuracy Assessment and Guidelines for Manual Traffic Counts from Pre-Recorded Video Data

Application of Real-time Sensor Data to Evaluation of Performance of Ad Hoc Distributed Traffic Simulation

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