PI: H. Scott Matthews
Co-PI(s): Paul S. Fischbeck
University: Carnegie Mellon University
Around the world, vehicles of many types are subject to manually conduct periodic inspections to assess the current status of their safety systems. These programs check status of vehicle safety components like brakes, tires, lights, etc. In past work, the CMU research team created a data analytics infrastructure to collect data on and assess the effectiveness of state safety inspection programs for passenger vehicles.
In this project, researchers define a vision of a technology-information-policy system that can better serve all stakeholders in ensuring the safety of the commercial trucking fleet. Currently, highway trucks (aka tractors) and trailers are subject to a patchwork of state and federal safety inspections which check individual safety components like tires, brakes, and lights. These inspections are manual, and duplicative, and in a freight environment, lead to disruptions in fleet efficiency as well as substantial annual costs from vehicle and driver downtime.
Our vision is comprised of three parts: a data analytics infrastructure for assessment of safety component failures of commercial trucks and trailers; the adaptation of an existing connected truck telematics system to be a real-time diagnostic for truck fleet safety assessment; and bridging to acceptance of public agencies to accept telematics approaches in place of some truck inspections.
The researchers will partner with two Pennsylvania firms to achieve this vision. CompuSpections, a passenger vehicle safety inspection information technology firm, and Truck-Lite Co., LLC, whose Pittsburgh-based global R&D center is developing sensing and hardware systems to continuously assess the status of safety technologies in trucks and trailers.