Abstract
A significant majority of the state of the art autonomous sensing and navigation technologies rely on good lane markings or detailed 3D maps of the environment and are more suited for urban communities. On the other hand, a large number of rural roads in the U.S. do not have lane markings and have irregular boundaries. These challenges are common to many small and rural communities (SRCs), defined as an incorporated city, town, or village with a population of less than 50,000. As of 2019, there are 18,723 SRCs in the US [1,2]; these communities are sparsely connected and cover huge areas. The objective of this project is to develop an efficient sensing and navigation system for SRCs that use crowdsourced topological maps such as the Open Street Map (OSM) [3] that provides high-level road network information in concert with onboard sensing systems that include LIDAR and cameras to localize and navigate an autonomous vehicle. The system will be tested and validated on a large number of rural roads in the SRCs around College Station, TX.
Project Highlights
Coming Soon!
Final Report
Coming Soon!
EWD & T2 Products
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Presentations/Publications
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Research Investigators (PI*)
Sivakumar Rathinam (TAMU/TTI)*
Stephen Ninan (TAMU/TTI-Student)
Project Information
Start Date: 2021-09-01
End Date: 2023-08-31
Status: Active
Grant Number: 69A3551747115
Total Funding: $240,371
Source Organization: Safe-D National UTC
Project Number: 06-004
Safe-D Theme Areas
Big Data Analytics
Automated Vehicles
Safe-D Application Areas
Vulnerable Users
Operations and Design
Vehicle Technology
More Information
RiP URL
UTC Project Information Form
Sponsor Organization
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC 20590 United States
Performing Organization
Texas A&M University
Texas A&M Transportation Institute
3135 TAMU
College Station, Texas 77843-3135
USA