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原文传递 Monitoring and Predicting Pedestrian Behavior at Traffic Intersections.

题名：	Monitoring and Predicting Pedestrian Behavior at Traffic Intersections.
作者：	Navarro-Serment, L. E.
关键词：	Pedestrian information, Pedestrian movement, Pedestrian traffic, Real time control, Sensors, Traffic signal control systems, Traffic surveillance, Vehicle detectors, Traffic monitoring systems
摘要：	Effective traffic monitoring systems must take into account all moving objects. While vehicle detection systems are common, sensor-based solutions that provide awareness of pedestrian activity have yet to become an integral part of a smart and effective infrastructure capable of protecting these most vulnerable traffic participants. Such a system could alert incoming vehicles about dangerous situations involving pedestrians, or provide adaptive traffic light control systems with information about the motion of people, so that they can operate and make decisions cognizant of all moving objects. In the previous research work the project developed a vision-based framework which is capable of detecting, tracking, and predicting the trajectories of people. These abilities constitute the core of a system capable of monitoring any developments concerning pedestrian motion. In this project, we aim at positioning our research for deployment. The project plans to enhance the algorithms to make them suitable for operation in real traffic situations, in terms of accuracy and robustness against adverse operating conditions. Additionally, the project will address the difficulties of bringing a new site into effective action, such as camera calibration and the initial identification of a context to make predictions. The expected outcome is an implementation of the enhanced framework which can be deployed in the field, and is capable of providing pedestrian information to Surtrac1—a real time traffic signal control system. The milestones envisioned, to accomplish in two years, are: (1) Development of enhanced approach for pedestrian detection; (2) Implementation of prototype suitable for operation in real time; and (3) Testing and characterization of prototype in the field. The team is composed of a Master's student, and researchers with many years of experience in computer vision for autonomous systems.
报告类型：	科技报告