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Portable and Integrated Multi-Sensor System for Data Driven Performance Evaluation of Urban Transportation Networks

In urban areas, obstructions of traffic such as double parking, commercial vehicle deliveries, pedestrian jaywalking, taxi pick-ups and drop-offs, are potential impediments to road capacity and vehicular speed, and causes traffic delay as well as safety risks. In 2014, double parking violation had 502,082 ticketed cases in New York City according to NYCDOF records. New York City and many urban areas need to keep track of the impacts of these violations on their transportation system as well as on the residents of the city. Hence there is a strong need to develop robust methodologies to monitor these activities and analyze their potential impacts that can be in the form of longer travel times, crashes, emissions, or noise pollution. Due to the advances in sensors and computing, obtaining information related to the parking, individual vehicle or pedestrian trajectories has become remarkably feasible. Video cameras coupled with computer vision algorithms can provide very accurately, detect, track and classify vehicles. Similarly relatively inexpensive mobile sensors for measuring noise and emission levels have also become commercially available. However, integrated inexpensive multi-sensor solutions that combine these sensing solutions are not yet commercially available.

Project Details

Project Type: 
UTRC Research Initiative
Project Dates: 
September 1, 2016 to January 31, 2018
Principal Investigators: 
Dr. Kaan Ozbay
Hong Yang
Institution: 
New York University
Affiliated Faculty at Non-Member Institutions
Sponsor(s): 
University Transportation Research Center (UTRC)
Publications: 
Final Report
Project Brief
Project Status: 
Complete
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