Development of a Cooperative Perception System

Feng, Yiheng; Tarko, Andrew

doi:10.5703/1288284317728

i

Development of a Cooperative Perception System

2023-08-01
By Feng, Yiheng ; Tarko, Andrew

File Language:

English

Details

Creators:

Feng, Yiheng ; Tarko, Andrew
Corporate Creators:

Center for Connected and Automated Transportation (CCAT) ; Purdue University
Corporate Contributors:

United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology ; United States. Department of Transportation. University Transportation Centers (UTC) Program
Subject/TRT Terms:

Connected Vehicles Cooperatives Highway Safety Instrumentation Intelligent Vehicles Intersections Intersection Safety Perception Roadside Roadside Instrumentation Vehicle To Vehicle Communications
Publication/ Report Number:

CCAT Report No. 70
DOI:

http://dx.doi.org/10.5703/1288284317728
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final report, April 2022 – August 2023
Corporate Publisher:

Center for Connected and Automated Transportation. Purdue University
Abstract:

Cooperative perception that integrates sensing capabilities from both infrastructure and vehicles can greatly benefit the transportation system in terms of safety and data acquisition. In this project, a prototype of such a system was developed and evaluated by integrating a Lidar-based infrastructure detection system (facilitated with a portable Traffic Scanner, TScan) with an SAE Level 4 connected and automated vehicle (CAV). Vehicle-to-everything (V2X) communication devices were installed on both the TScan and the CAV to enable real-time message transmission of detection results in the form of SAE J2735 Basic Safety Messages (BSMs). The prototype system was validated using a case study. This aimed at improving CAV situation awareness and protecting vulnerable road user (VRU) safety. The field-testing results demonstrated the benefit of cooperative perception from infrastructure sensors in detecting the occluded VRU and helping the CAV plan safer and smoother trajectories.
Format:

PDF
Funding:

69A3551747105
Collection(s):

University Transportation Centers
Main Document Checksum:

urn:sha-512:f3539ce330cbf1630bda37eda37e9a25ad260b94c2a6ec569c1b46cf14e5171c693534b31f69fa9c9bab3df18bfca51b8def0e71b824bd87a9cec3283a208628
Download URL:

https://rosap.ntl.bts.gov/view/dot/73642/dot_73642_DS1.pdf
File Type:

[PDF - 2.45 MB ]

File Language:

English

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