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Development and evaluation of a real-time pedestrian counting system for high-volume conditions based on 2D LiDAR
Transportation Research Part C: Emerging Technologies ( IF 5.775 ) Pub Date : 2020-02-13 , DOI: 10.1016/j.trc.2020.01.018
Asad Lesani; Ehsan Nateghinia; Luis F. Miranda-Moreno

Automated monitoring of pedestrians on non-motorized facilities with high pedestrian flows is challenging. Several automated sensor solutions are commercially available that have been evaluated in the literature including traditional point-based sensors, such as inductive loop detectors for bicycles and infrared sensors for pedestrians. More recently, image-based systems, based on video cameras or thermal video cameras, have been developed. Despite the various options, some key limitations of existing solutions exist, in particular, the lack of low-cost solutions using embedded systems capable of performing in real-time under high volume (flow) conditions. This work aims at developing and evaluating the performance of a novel, real-time counting system, developed for environments with high pedestrian flows. The proposed system is based on emerging LiDAR (Light Detection and Ranging) technology. As an input, the system uses the distance measurements from a two-dimensional LiDAR sensor with a set of distinct laser channels and a given angular resolution between each channel. The developed system processes those measurements using a clustering algorithm to detect, count, and identify the direction of travel of each pedestrian. The system’s performance is evaluated by comparing its directional counting outputs with manual counts (ground truth) using disaggregate and aggregate (15-minutes interval) counts at two different monitoring locations. The results demonstrate that the system accurately counts more than 97% of the pedestrians at the disaggregate level, with a false direction detection rate of 1.1%. The over-counting error is 0.7% and the under-counting errors are 1.3% and 2.7% for the two selected sites. At the aggregate level (15-minutes interval), the average absolute percentage deviations (AAPDs) are 1.6% and 4.3% while the weighted AAPDs are 1.5% and 3.5% for the first and second sites, respectively. The accuracy of the proposed system is higher than the traditional technologies used for the same purpose.
更新日期:2020-02-21

 

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