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CMVRTC: System Validations and Duty Cycle Data Collections


Project Goal:

The goal is to understand how often ADS-equipped CMVs will be engaged in automated operations.  Further, it will identify and characterize key areas of failure for a commercial Class 8 tractor-trailer vehicle and quantify their severity, probability of occurrence, and how controllable the resulting situation is by an autonomous vehicle system.


Currently, many of the autonomous vehicle systems in development for commercial vehicles are focusing on improving safety through accurate sensing of the environment and control of the vehicle to reduce the probability of a collision.  The safety of an autonomous vehicle is much more complex than simply avoiding primary collisions with other vehicles.  According to the 2019 Large Truck and Bus Crash Facts, approximately 1% of fatal crashes are the result of an event other than a collision with another vehicle, fixed object, or rollover.  Additionally, nearly 12% of fatal crashes involving a large truck, the vehicle was not on roadway.  With the occurrence of non-collision fatalities and presence of non-moving vehicle fatalities, there is a potential gap in the identification and mitigation of the causes of these events by an autonomous vehicle system.


In order to understand the feasibility of carriers investing in ADS-equipped CMVs, it is important to identify the characteristics of the average duty cycle—specifically, in what percentage of the cycle the CMV will be operating under automation.  Further, we must understand the failure modes of these vehicles in real world operations.  Data will be collected on ADS-equipped CMVs and, for comparison, on CMVs engaged in standard operations. These data will be compared to understand how ADS-equipped vehicles operate relative to standard vehicles.