National Surface Transportation Safety Center for Excellence Reports (NSTSCE, VTTI)

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https://hdl.handle.net/10919/5529
http://www.vtti.vt.edu/national/nstsce/

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Browsing National Surface Transportation Safety Center for Excellence Reports (NSTSCE, VTTI) by Subject "ADS"

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    Investigation of ADAS/ADS Sensor and System Response to Rainfall Rate
    Cowan, Jonathan B.; Stowe, Loren (National Surface Transportation Safety Center for Excellence, 2024-08-23)
    Advanced driver assistance systems (ADAS) and automated driving systems (ADS) rely on a variety of sensors to detect objects in the driving environment. It is well known that rain has a negative effect on sensors, whether by distorting the inputs via water film on the sensor or attenuating the signals during transmission. However, there is little research under controlled and dynamic test conditions exploring how rainfall rate affects sensor performance. Understanding how precipitation may affect the sensor’s performance, in particular the detection and state estimation performance, is necessary for safe operation of the ADAS/ADS. This research strove to characterize how rainfall rate affects sensor performance and to provide insight into the effect it may have on overall system performance. The team selected a forward collision warning/automatic emergency braking scenario with a vehicle and surrogate vulnerable road user (VRU) targets. The research was conducted on the Virginia Smart Roads’s weather simulation test area, which can generate various simulated weather conditions, including rain, across a test range of 200 m. The selected sensors included camera, lidar, and radar, which are the primary sensing modalities used in ADAS and ADS. The rain rates during testing averaged 21 mm/h and 40 mm/h. Overall, the data backed up the expected trend that increasing rainfall rate worsens detection performance. The reduced detection probability was most prominent at longer ranges, thus reducing the effective range of the sensor. The lidars showed a general linear trend of 1% reduction in range per 1 mm/h of rainfall with some target type dependence. The long-range and short-range cameras show at least a 60% reduction in detection range at 40 mm/h. The object camera, which only detected the vehicle target, showed better performance with only a 20% reduction in range at 40 mm/h, which may be due to the underlying ADAS specific detection model. For vehicles, the radars typically showed a linear drop in detection range performance with an approximately 20% reduction in range at 40 mm/h rainfall rate. The VRU target showed a larger decrease in detection range compared to the vehicle target due likely to the smaller overall signal the VRU target returns.
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    Preparing First Responder Stakeholders for ADAS and ADS Deployments
    Trimble, Tammy E.; Faulkner, Daniel (National Surface Transportation Safety Center for Excellence, 2024-12-16)
    Previous research has found that public safety providers are unclear about the capabilities associated with advanced driver assistance systems (ADAS)- and Automated Driving System (ADS)-related technologies. Providing outreach to this population will reduce uncertainty regarding these technologies, which in turn will lead to improved safety and interactions, including crash documentation, while in the field. A training curriculum was developed that consisted of two parts: (1) a classroom portion which can be delivered in-person or online and (2) a hands-on experiential portion. Two training options were presented to local agencies: (1) an approximately 1-hour online session, to be held at the agency’s convenience, which covers the prepared training materials; and (2) an in-person, half-day session which covers the prepared training materials and provides exposure to ADAS- and ADS-equipped vehicles. Recruitment efforts resulted in five in-person and six online attendees. In-person attendees represented three separate organizations, with one organization being represented by officers from three locations. The online attendees represented six separate organizations. Only one organization had an attendee in both the in-person and online options. To better understand the time to be allotted for the online training, the in-person training was held first. As a result, the online training was ultimately extended to 1.5 to 2 hours, which allowed time for discussion throughout the training. Feedback received directly from the participants at the conclusion of the training and via the online questionnaires was overwhelmingly positive. Moving forward, the training materials will need to be updated on a continual basis to ensure the ongoing timeliness of information shared. To share the materials with a wider range of individuals, the training could be developed and shared in a manner like the Virginia Tech Transportation Institute’s (VTTI’s) Sharing the Road program, where VTTI representatives visit schools to provide information and hands-on encounters to promote safely sharing the road with large trucks. A key to success will be employing individuals with first responder experience to provide the training. Feedback suggested that those with hands-on experience combined with their ties to VTTI resulted in perceived credibility. Also, providing hands-on opportunities to see variations in technologies across vehicle models and applications was considered beneficial. Working with VTTI partners, it may be possible to obtain demonstration vehicles for this purpose. Through this development process, the team can work towards accreditation and providing the training as part of academy, in-service, or regional training days.