Experiment Conducted in Indiana Showed Connected and Automated Vehicles with Traffic Scanning Technology Enhanced Smooth Stopping Behavior by 62.9 Percent Upon Detecting Vulnerable Road Users.
V2X Prototype Tested at A University Campus in Indiana Found Safety Benefits for a Pedestrian-Vehicle Conflict Scenario at a T-Intersection.
Indiana, United States
Development of a Cooperative Perception System
Summary Information
Cooperative perception combining sensing capabilities from both infrastructure and vehicles has the potential to greatly improve safety and data acquisition in transportation. In this study, a prototype cooperative perception system was developed and evaluated by integrating a LiDAR-based infrastructure detection system, named TScan, with an SAE Level Four (high automation) Connected and Automated Vehicle (CAV). Vehicle-to-everything (V2X) communication devices were installed both in TScan and the CAV to enable real-time Basic Safety Message (BSM) transmission of detection results. The prototype system was evaluated using a case study conducted at Purdue University campus in Indiana in March 2023, with the goal of improving CAV situation awareness and Vulnerable Road User (VRU) safety.
METHODOLOGY
In designing the experiment for the case study, a VRU (a cardboard box of the same height as a teenager placed on a remote-controlled skateboard) traveling from west to east was considered to be in a potential conflict point at a T-intersection with a CAV traveling from south to north. Three different experiments were conducted, with the central hypothesis being “TScan could detect the VRU before they arrive at the intersection, which would lead to a safer and smoother vehicle reaction”:
- Experiment 1: The VRU and the vehicle are approaching the intersection at the same time without TScan and the vehicle is driven by a human driver.
- Experiment 2: The VRU and the vehicle are approaching the intersection at the same time without TScan and the vehicle is automated.
- Experiment 3: The VRU and the vehicle are approaching the intersection at the same time with TScan and the vehicle is automated.
FINDINGS
- In Experiment 1, the human driver was not able to detect the VRU and crashed without having time to apply the brakes.
- Based on the results from the Experiments 2 and 3, the average deceleration value of CAV reduced from 1.32 to 0.49 meters per seconds squared (m/s2) when TScan was used, which corresponded to an enhancement of 62.9 percent in smooth stopping behavior of CAV upon detecting the VRU.
- In addition, the maximum deceleration of CAV reduced from 5.12 m/s2 in Experiment 2 to 2.21 m/s2 in Experiment 3, corresponding to 56.8 percent reduction in hard braking.
