Institute Publications, Virginia Tech Transportation Institute (VTTI)
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- AI Dash Cam Performance Testing: Final ReportCamden, Matthew C.; Soccolich, Susan A.; Faulkner, Daniel; Ridgeway, Christie; Herbers, Eileen; Golusky, Mark (2025-03-31)The objective of this project was to assess the Nauto® driver monitoring system (DMS) technology for alert performance. The study tested the technology’s alert performance for six risky driving behaviors as performed in a heavy truck and five driver maneuvers performed during high-risk driving scenarios in a light-duty vehicle. The task types were selected by the sponsor. VTTI evaluated DMS performance by calculating rates of in-cabin audible alerts, rates of alerts recorded on the virtual platform’s dashboard, and time to alert (TTA) from the start of the tested driving behavior or from time to collision, depending on the test scenario. The study included a test-track experiment to determine the rate at which the system provided in-cab audible alerts in response to specific driving behaviors and maneuvers. The test-track experiment driving behaviors were performed between September 20, 2024, and December 12, 2024. The first six specific driving behaviors were performed in a Class 8 tractor (i.e., close following of a lead vehicle; making an outgoing phone call on a handheld smartphone; sending an outgoing text message; discreetly using a smartphone in lap; not wearing a seatbelt; and performing a rolling stop through a stop sign). The remaining driving maneuvers were performed in a light-duty commercial vehicle (i.e., approaching a stopped vehicle target to elicit an external scene-only forward collision warning [FCW]; approaching a vulnerable road user [VRU] target to elicit an external scene-only FCW; approaching a stopped vehicle target while texting to elicit a FCW based on the fusion of an external FCW paired with driver distraction; approaching a VRU target while texting to elicit an FCW based on the fusion of an external FCW paired with driver distraction; close following of a lead vehicle while sending an outgoing text message). The Nauto DMS was tested in a single installation position in each study vehicle. Testing took place on VTTI’s Smart Roads test track. The performed behaviors and maneuvers were tested under daytime and nighttime lighting conditions. The stopped vehicle was an inflatable target from a tow-behind vehicle model system. The VRU targets included an adult pedestrian target and a motorcycle target, both models meeting Euro New Car Assessment Program standards. During testing, the stationary pedestrian target’s arms and legs moved in a motion consistent with walking across the roadway; a remote control was used to operate the model. In-cab alerts, dashboard alerts, and TTA were recorded for every trial. The following results provide a summary of key findings and do not provide a comprehensive review of all analyses. Further details can be found in the Results section of the report. In the Class 8 tractor, the system provided audible alerts for all trials of tested driver-distraction-related tasks (i.e., making an outgoing phone call on a handheld smartphone, sending an outgoing text message, and discreetly using a handheld smartphone in lap) and the seat belt use task. For the rolling stop task, in-cabin alerts were provided in 95% of all trials. The audible alert rate for the close following of a lead vehicle task was 50% over all trials. In the light-duty commercial vehicle, the system provided audible alerts in at least 80% of daytime trials for external scene fusion and external scene-only FCW tasks, regardless of target. Nighttime trials of these tasks had audible alert rates of 50% or below, with no alerts provided for external scene-only FCW using a pedestrian. For FCW tasks, 75% to 93% of trials with alerts had alerts provided prior to the swerve point, depending on the task. Close following of a lead vehicle while texting had an overall alert rate of 95%. Average TTA for the driver distraction-related tasks performed in the Class 8 tractor was under 5 seconds, regardless of lighting condition. Average TTA for the rolling stop task was 3.36 seconds. Average TTA for the seat belt use task was 12.95 seconds. For the close following of a lead vehicle task, the range in TTA across trials was 16 seconds for daytime trials and over 20 seconds for nighttime trials. For FCW tasks in the light-duty commercial vehicle, TTA was calculated as time between the start of the alert and the vehicle reaching the target. For the stopped vehicle target tasks, the overall average TTA was 1.99 seconds for external scene-only FCW and 2.47 seconds with driver distraction. For the pedestrian target tasks, overall average TTA was 2.67 seconds without distraction and 2.30 seconds with driver distraction. For the motorcycle target tasks, the overall average TTA was 3.93 seconds without distraction and 4.24 seconds with driver distraction. Close following of a lead vehicle with distraction had an average TTA of 6.27 seconds in daytime trials and 9.06 seconds in nighttime trials. For all trials performed in the Class 8 tractor, the dashboard alert rate matched that of the in-cab alert rate. In the commercial light vehicle, a trial of external scene FCW using a motorcycle target that did not have an in-cabin audible alert was included on the dashboard with the appropriate alert type. For all other tasks and trials performed in the light-duty commercial vehicle, the dashboard alert rate matched that of the in-cab alert rate. The current study used a validated approach, with repeatable methods, and was performed in a controlled setting to collect data on the performance of the Nauto DMS. However, it is also important to document study limitations, which inform the accurate interpretation of the presented results and the ability of the results to be extrapolated outside of the tested conditions. VTTI does not endorse any dash cam used or not used in this study. The results obtained are based on controlled testing in specific conditions using only one driver. The current study assessed the system’s performance for three specific metrics and was not a holistic assessment of system performance, effectiveness of the DMS on changing driver behavior or crash avoidance and prevention, or carrier/driver acceptance of the device.
- VTTI Annual Report, 2021 Fiscal Year(Virginia Tech, 2021)Learn more about VTTI's accomplishments during fiscal year 2021.
- Estimating Crash Consequences for Occupantless Automated VehiclesWitcher, Christina; Henry, Scott; McClafferty, Julie A.; Custer, Kenneth; Sullivan, Kaye; Sudweeks, Jeremy D.; Perez, Miguel A. (Virgina Tech Transportation Institute, 2021-02)Occupantless vehicles (OVs) are a proposed application of automated vehicle technology that would deliver goods from merchants to consumers with neither a driver nor passengers onboard. The purpose of this research was to understand and estimate how the increased presence of OVs in the United States fleet may influence crash risk and associated injuries and fatalities. The approach used to estimate potential modifications in crash risk consequences was a counterfactual simulation, where real-world observations were modified as if alternate events had occurred. This analysis leveraged several U.S. national crash databases, along with the Second Strategic Highway Research Program (SHRP 2) Naturalistic Driving Study (NDS) dataset. The analysis required the derivation of parameters that could be used to modify existing crash estimates as OVs enter the fleet in greater numbers. The team estimated benefit parameters pertaining to (1) the crashes that could be ultimately avoided altogether based on the OV’s smaller size, (2) benefits that could be obtained from the improved crashworthiness characteristics of the OV, and (3) benefits due to the lack of occupants in the OV. Results showed that of the 58,852 fatalities in the national databases examined, a full-scale market penetration of OVs was estimated to reduce fatalities by 34,284, a reduction of 58.2%. Most of this reduction (83%) would come from the lack of occupants in the OVs. Similarly, of the 6,615,117 injured persons in the national databases examined, a full-scale penetration of OVs was estimated to reduce injured persons by 4,088,935, a reduction of 61.8%. As was observed for fatalities, most of this reduction (72.1%) would come from the lack of occupants in the OVs. The results of this investigation, however, should not be taken as definitive benefit estimates. There are important assumptions inherent in the parameters that were used, and some of these assumptions may not be immediately realized. Rather, the results are meant to support critical thinking into how innovative technologies such as OVs may offer benefits that transcend the typical approaches used in vehicle safety, including passive and active safety measures.
- VTTI Annual Report, 2020 Fiscal Year(Virginia Tech, 2020)Learn more about VTTI's accomplishments during fiscal year 2020.
- VTTI Annual Report, 2019 Fiscal Year(Virginia Tech Transportation Institute (VTTI), 2019)Learn more about VTTI's accomplishments during fiscal year 2019.
- VTTI 25(Virginia Tech Transportation Institute, 2013)This booklet, published in 2013, commemorated 25 years of research at the Virginia Tech Transportation Institute (VTTI).
- National Surface Transportation Safety Center for Excellence Annual Report, January - December 2012(Virginia Tech, 2012)This annual report documents the center's research and positive impact on transportation safety in 2012.
- National Surface Transportation Safety Center for Excellence Annual Report, January-December 2011(Virginia Tech, 2011)This annual report documents the center's research and positive impact on transportation safety in 2011.
- National Surface Transportation Safety Center for Excellence Annual Report, January - December 2010(Virginia Tech, 2010)This annual report documents the center's research and positive impact on transportation safety in 2010.
- Transportation Research Today, Vol. 1, No. 2, 2014(Virginia Tech, 2014)NSTSCE’s second quarterly newsletter puts the spotlight on commercial drivers and gives an inside look at a health and wellness program.
- Transportation Research Today, Vol. 1, No. 4, 2014(Virginia Tech, 2014)NSTSCE’s fourth quarterly newsletter puts the spotlight on medication use in commercial vehicle drivers.
- Transportation Research Today, Vol. 1, No. 1, 2014(Virginia Tech, 2014)NSTSCE’s first quarterly newsletter puts the spotlight on older drivers and the transportation challenges and mobility issues they face maintaining an active lifestyle.
- Transportation Research Today, Vol. 1, No. 3., 2014(Virginia Tech, 2014)NSTSCE’s third quarterly newsletter puts the spotlight on motorcycle safety.
- National Surface Transportation Safety Center for Excellence Annual Report, January - December 2013(Virginia Tech, 2013-12)This annual report documents the center's research and positive impact on transportation safety in 2013.
- VTTI Annual Report 2018(Virginia Tech, 2018)The Virginia Tech Transportation Institute (VTTI) conducts research to save lives, save time, save money, and protect the environment. Researchers and students from multiple fields are continuously developing the techniques and technologies to solve transportation challenges from vehicular, driver, infrastructure, and environmental perspectives. As one of seven premier research institutes created by Virginia Tech to answer national challenges, VTTI has effected significant change in public policies for driver, passenger, and pedestrian safety and is advancing the design of vehicles and infrastructure to increase safety and reduce environmental impacts.
- VTTI 2013 Annual Report(Virginia Tech, 2013)The Virginia Tech Transportation Institute (VTTI) conducts research to save lives, save time, save money, and protect the environment. Researchers and students from multiple fields are continuously developing the techniques and technologies to solve transportation challenges from vehicular, driver, infrastructure, and environmental perspectives. As one of seven premier research institutes created by Virginia Tech to answer national challenges, VTTI has effected significant change in public policies for driver, passenger, and pedestrian safety and is advancing the design of vehicles and infrastructure to increase safety and reduce environmental impacts.
- VTTI 2017 Annual Report(Virginia Tech, 2017)The Virginia Tech Transportation Institute (VTTI) conducts research to save lives, save time, save money, and protect the environment. Researchers and students from multiple fields are continuously developing the techniques and technologies to solve transportation challenges from vehicular, driver, infrastructure, and environmental perspectives. As one of seven premier research institutes created by Virginia Tech to answer national challenges, VTTI has effected significant change in public policies for driver, passenger, and pedestrian safety and is advancing the design of vehicles and infrastructure to increase safety and reduce environmental impacts.
- VTTI 2015 Annual Report(Virginia Tech, 2015)The Virginia Tech Transportation Institute (VTTI) conducts research to save lives, save time, save money, and protect the environment. Researchers and students from multiple fields are continuously developing the techniques and technologies to solve transportation challenges from vehicular, driver, infrastructure, and environmental perspectives. As one of seven premier research institutes created by Virginia Tech to answer national challenges, VTTI has effected significant change in public policies for driver, passenger, and pedestrian safety and is advancing the design of vehicles and infrastructure to increase safety and reduce environmental impacts.
- VTTI 2016 Annual Report(Virginia Tech, 2016)The Virginia Tech Transportation Institute (VTTI) conducts research to save lives, save time, save money, and protect the environment. Researchers and students from multiple fields are continuously developing the techniques and technologies to solve transportation challenges from vehicular, driver, infrastructure, and environmental perspectives. As one of seven premier research institutes created by Virginia Tech to answer national challenges, VTTI has effected significant change in public policies for driver, passenger, and pedestrian safety and is advancing the design of vehicles and infrastructure to increase safety and reduce environmental impacts.
- VTTI 2014 Annual Report(Virginia Tech, 2014)The Virginia Tech Transportation Institute (VTTI) conducts research to save lives, save time, save money, and protect the environment. Researchers and students from multiple fields are continuously developing the techniques and technologies to solve transportation challenges from vehicular, driver, infrastructure, and environmental perspectives. As one of seven premier research institutes created by Virginia Tech to answer national challenges, VTTI has effected significant change in public policies for driver, passenger, and pedestrian safety and is advancing the design of vehicles and infrastructure to increase safety and reduce environmental impacts.