METRANS UTC

Smart Sensing System for Real-time Automatic Traffic Analysis of Highway Rest Areas

Project Number

17-11

Project Summary

This research proposal targets the design of smart sensing system for real-time automatic traffic analysis of highway rest areas. We will develop low-power sensing platforms, optimized power-saving algorithms, communications protocols, and machine-learning models to yield a novel and modular multi-nodal sensing systems that will help traffic analysis of highway rest areas efficiently. This will be a part of nationwide efforts of Intelligent Transportation Systems (ITS) for smart connected roads.  To the best of our knowledge, Caltrans (or similar entity at nationwide) doesn’t have any installed ITS that can perform “automatic” and “real time” vehicle identification and classification for highway rest areas. Our proposed system will reveal high grained traffic data such that user will be able to know for “each” vehicle the time of entry and exit in the rest area and, it’s classification (based on axles). The proposed smart sensing and data interpretation system will maintain small foot-print, significantly cost-effective (compare to existing available systems), and will be capable of automatic identifying and classifying each vehicle in high way rest area in real-time. This research will focus on all levels of system design from architecture to computation to communication design.

Project Status

Complete

Year

2017

Topic Area

Urban Mobility

P.I. Name & Address

Assistant Professor, Department of Electrical Engineering; College of Engineering
California State University, Long Beach
1250 Bellflower Blvd.
ECS-521
Long Beach, CA 90840-8306
United States
mohammad.mozumdar@csulb.edu

Funding Source

US DOT

Total Project Cost

$69,197

Start and End Dates

9/1/2017 – 8/31/2018