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I-Corps: Advanced traffic systems and traffic analysis using light detection and ranging (LiDAR) sensors on the roadside

Project: Research

Abstract & Details

Description

Award ID: 2135414

The broader impact/commercial potential of this I-Corps project is to provide behavior-level data with roadside LiDAR (light detection and ranging) technologies to fill today's traffic data gap and meet data requirements for advanced traffic systems. Advanced traffic engineering requires behavior-level traffic analyses to improve traffic safety, reduce traffic delay, and enhance energy efficiency in transportation. However, existing traffic sensing technologies often cannot provide sufficient data. Potential customers of the envisioned platform, with hardware for data collection and online service for data processing, will primarily be traffic data collection companies that collect and provide required data to government agencies or engineering projects. Larger traffic agencies with in-house data collection teams may also be users of the technology. This I-Corps project further develops a roadside LiDAR (light detection and ranging) traffic sensing system which integrates LiDAR sensing hardware, artificial intelligence (AI) algorithms for data processing, and trajectory analysis services for road traffic. The LiDAR sensor hardware is customizable for both permanent or portable deployment by integrating appropriate power supplies, LiDAR sensors, edge computation units, and data communication devices. The roadside LiDAR sensing platform is significantly different from on-vehicle sensing systems. The AI algorithms are specifically developed for roadside sensing by including background object filtering, object clustering, object classification, object tracking, and geo-referencing of object trajectories for roadside sensing. The geographic information system (GIS) traffic analysis services utilize geo-analysis functions to provide traffic engineering knowledge and/or real-time traffic control input. This project is based on successful demonstration of proof-of-concept applications. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Ruth Shuman
StatusClosed
Effective start/end date07/15/2112/31/22

Funding

  • I-Corps Teams: $50,000.00

Active Fiscal Year

  • FY2023
  • FY2022

Start Fiscal Year

  • FY2021

TIP Programs

  • I-Corps Teams

Key Technology Areas

  • Artificial Intelligence
  • (confidence score: 99%)
  • Advanced Communications
  • (confidence score: 99%)

Technology Foci

  • Wireless communication — terrestrial and space
  • (confidence score: 95%)
  • Artificial Intelligence (Broad)
  • (confidence score: 100%)

Congressional District at Award

  • District n. 02 of Nevada

Current Congressional District

  • District n. 02 of Nevada

United States

  • Nevada

Core Based Statistical Area (CBSA)

  • Reno, NV

County

  • County: Washoe, NV

EPSCoR Jurisdiction

  • Yes

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