Certification of Connected and Automated Vehicles for Vulnerable Road Users
The autonomous systems industry in the Pittsburgh region supports 14,900 jobs and $ 1.2 billion in total labor income. It is estimated that within five years, the industry’s total scale will reach $ 10 billion. The key powerhouse is the development of connected and autonomous vehicles (CAVs). Albeit this huge opportunity, one hurdle to this transformative change is the concern of safety. Between 2013 and 2020, 31 states and the District of Columbia enacted legislation related to autonomous vehicles. The impact of state action is starting to manifest through the attraction of efforts that test autonomous systems to regions across the country as companies continue to advance their platforms. Numerous advancements have been developed to mitigate safety risks. For example, simulation tools, closed test grounds, and open corridors have been deployed by companies and universities. A critical research topic in safety is the evaluation of safety for vulnerable road users (VRUs), such as wheelchair users, people with strollers, vision-impaired people, service-dog users, and e-scooter users. Failure to ensure those people’s safety may result in criticism and backlash from the public and also objection and pushback from regulators. The primary goal of this project is to address this gap by designing and implementing a systematic CAV evaluation certificate program, along with simulation and physical tools, for VRUs. This objective presents two challenges: (1) the limited data availability; (2) the lack of mature hardware for testing. The research team plans to address these by leveraging two strengths. The first strength is their expertise in multi-fidelity Generative Artificial Intelligence (AI). To provide stringent assessment, the team will leverage their previous work on adversarial, knowledge-based, and data-driven scenario generation to create extensive critical scenarios that pose significant risks to VRUs. PI Zhao has experience in utilizing large language models (LLMs) in autonomous vehicle (AV) legal behavior monitoring. To ensure the coverage of scenarios required by regulations and policies, the team will use similar approaches to assist the scenario design. The team will also utilize their previous work in accelerated evaluation to boost efficiency. These approaches are intended to mitigate the first challenge. The second strength is the expertise in both the automotive and robots. The team possesses the expertise to design systems with both autonomous vehicles and VRUs operated by robots. The team will develop a platform that can carry balloon pedestrians/wheelchair users in different terrains and mimic e-scooter users with their wheeled and legged robots. This will offer the advantage of agility and efficiency for self-reconstruction in the event of collisions. Testing robots developed in this project could serve as initial products for a spin-off start-up. In the next five years, Pittsburgh will encounter increasing competition from regions with signature state and regional initiatives that support autonomy applications. To maintain its position, Pittsburgh must establish programs to reinforce its current innovation ecosystem and root emerging companies and talent in the region. The team believes this project will establish a unique strength in the CAV safety evaluation area and secure Pittsburgh’s leading role in the field of autonomy.
- Record URL:
Language
- English
Project
- Status: Active
- Funding: $100000
-
Contract Numbers:
69A3552344811
-
Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
Carnegie Mellon University
Pittsburgh, PA United StatesSafety21 University Transportation Center
Carnegie Mellon University
Pittsburgh, PA United States 15213 -
Project Managers:
Stearns, Amy
-
Performing Organizations:
Carnegie Mellon University
Pittsburgh, PA United StatesSafety21 University Transportation Center
Carnegie Mellon University
Pittsburgh, PA United States 15213 -
Principal Investigators:
Zhao, Ding
- Start Date: 20240701
- Expected Completion Date: 20250630
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers
Subject/Index Terms
- TRT Terms: Artificial intelligence; Autonomous vehicles; Certification; Connected vehicles; Risk assessment; Robots; Traffic safety; Vehicle safety; Vulnerable road users
- Subject Areas: Highways; Pedestrians and Bicyclists; Planning and Forecasting; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01933400
- Record Type: Research project
- Source Agency: Safety21 University Transportation Center
- Contract Numbers: 69A3552344811
- Files: UTC, RIP
- Created Date: Oct 13 2024 8:48AM