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Movement Retraining using Real-time Feedback of Performance
Published on: January 17, 2013
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Transferability of real-time safety performance functions for signalized intersections
Mohamed Essa1, Tarek Sayed1, Passant Reyad1
1Department of Civil Engineering, University of British Columbia, 6250 Applied Science Lane, Vancouver, BC, V6T 1Z4, Canada.
Accident; Analysis and Prevention
|June 10, 2019
Summary
Real-time safety models for connected vehicles are transferable to new traffic signal jurisdictions. These models effectively predict rear-end traffic conflicts, enhancing intersection safety evaluations.
Area of Science:
- Traffic Engineering
- Intelligent Transportation Systems
- Road Safety
Background:
- Optimizing traffic signal control for safety is feasible with Connected Vehicle (CV) technology and real-time data.
- Existing real-time safety models link dynamic traffic parameters to rear-end conflicts at signalized intersections.
Purpose of the Study:
- To investigate the transferability of real-time safety models for signalized intersections to new jurisdictions.
- To evaluate model performance with and without local calibration in destination areas.
Main Methods:
- Utilized Next Generation Simulation (NGSIM) data for detailed vehicle trajectories in California and Atlanta.
- Applied various transferability analysis approaches and goodness-of-fit measures.
- Assessed model prediction accuracy for traffic conflicts.
Main Results:
- Real-time safety models demonstrated transferability across different jurisdictions.
- Models showed validity in predicting traffic conflicts in new environments.
- Performance was evaluated with and without local calibration.
Conclusions:
- The transferability of real-time safety models is confirmed.
- These models are valid for real-time safety evaluation of signalized intersections.
- Findings support wider application of these models in diverse traffic environments.
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