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Vehicle and Pedestrian Traffic Signal Performance Measures Using LiDAR-Derived Trajectory Data
Enrique D Saldivar-Carranza1, Jairaj Desai1, Andrew Thompson1
1Joint Transportation Research Program, Lyles School of Civil and Construction Engineering, Purdue University, West Lafayette, IN 47907, USA.
Sensors (Basel, Switzerland)
|October 16, 2024
Summary
LiDAR sensors precisely track vehicles and pedestrians at intersections, enabling real-time traffic signal performance analysis. This technology offers new insights into pedestrian movement, potentially improving traffic signal timing.
Area of Science:
- Transportation Engineering
- Traffic Flow Analysis
- Sensor Technology
Background:
- Signalized intersections are critical nodes in transportation networks.
- Traditional traffic data collection methods have limitations in accuracy and scope.
- Light Detection and Ranging (LiDAR) offers high-resolution object tracking capabilities.
Purpose of the Study:
- To develop and validate methodologies for estimating traffic signal performance measures using LiDAR data.
- To analyze vehicle and pedestrian movement patterns at signalized intersections.
- To assess the potential of LiDAR for real-time traffic monitoring and pedestrian behavior analysis.
Main Methods:
- Utilized LiDAR trajectory data from an intersection over a 24-hour period, capturing millions of vehicle and pedestrian waypoints.
- Generated Purdue Probe Diagrams (PPDs) from linear-referenced trajectories for both vehicles and pedestrians.
- Applied vehicle-based PPDs to estimate performance measures like queue lengths, arrivals on green, and level of service; pedestrian-based PPDs for wait times and multi-crosswalk traversal.
Main Results:
- Successfully estimated key traffic signal performance measures (e.g., 85th percentile queue lengths, Highway Capacity Manual Level of Service) from LiDAR data.
- Quantified pedestrian movement, including wait times and the proportion of individuals crossing multiple paths.
- Determined pedestrian walking speeds (e.g., 15th percentile at 3.9 ft/s), enabling data-driven adjustments to signal timing.
Conclusions:
- LiDAR technology provides a robust method for detailed, real-time assessment of traffic signal performance for both vehicles and pedestrians.
- The ability to measure pedestrian speeds directly allows for more informed and potentially safer traffic signal timing strategies compared to standard guidelines.
- LiDAR data enhances traffic management capabilities by offering granular insights into intersection dynamics.
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