Vision-Based Passenger Activity Analysis System in Public Transport and Bus Stop Areas

Abstract

This study presents the development of a vision system for passenger activity analysis in public transport and bus stop areas. The vision system used people detection and counting algorithm to track the flow of boarding and alighting passengers in a bus stop area. A fuzzy logic controller used inputs from the vision system to determine boarding frequency and alighting frequency for analysis of bus route and dwell time to avoid long queueing that usually cause traffic congestion. People detection and counting result using DS6 dataset (indoor) have 96.81% accuracy with 97.93% precision. People detection and counting result using DS4–1 dataset (outdoor, bus stop area) have 80.39% accuracy with 87.13% precision. Fuzzy simulation results show a boarding frequency of 22 passengers /minute and alighting frequency of 12 passengers /minute. The vision system also analyzed the boarding and alighting of passengers in no loading and unloading areas. This event usually caused traffic bottleneck due to road blockage and long bus queues. In the analysis of DS4–1 (24-hr length) videos, a total of 212 no loading/unloading violations were recorded.