Advanced driver assistance systems for teen drivers: A national survey of teen and parent perceptions

Abstract

Objective: Recently developed advanced driver assistance systems (ADAS) have the potential to compensate for teen driving errors and reduce overall crash risk. To date, very limited research has been conducted on the suitability of ADAS for teen drivers—the population most likely to benefit from such systems. The opportunity for ADAS to reduce the frequency and severity of crashes involving teen drivers is hindered when there is a lack of trust, acceptance, and use of those technologies. Therefore, there is a need to study teen and parent perceptions of ADAS to help identify and overcome any potential barriers to ADAS use.

Methods: A U.S. national survey was developed based on themes from previously conducted teen and parent ADAS focus groups. Survey topics included trust in ADAS, effect of ADAS on teen driver safety and driving behavior, effect of ADAS on skill development, data privacy, and cybersecurity. Responses included 5-point Likert scales and open-ended questions. The survey was managed through an online respondent panel by ResearchNow. Eligibility criteria included licensed teens (16–19 years) and parents of licensed teens. Teen and parent responses were compared using chi-square statistics in SAS 9.4.

Results: Two thousand and three (teens?=?1,000; parents?=?1,003) respondents qualified for and completed the survey between September 1 and September 20, 2017. Overall, teens (72%) and parents (61%) felt that ADAS would have a positive impact on transportation. However, teens were more likely to exhibit a positive outlook on ADAS, whereas parents were more likely to have a negative outlook (P?<?.01). Teens felt that ADAS would be useful during bad weather or drowsy driving but were less concerned than parents about ADAS intervention during their own risky driving (P?<?.01). The majority of teens (65%) and parents (71%) agreed that teens should learn to drive on vehicles without ADAS, with parents being more likely to agree than teens (P?<?.01). Parents (55%) were more likely than teens (47%) to be concerned about insurance companies keeping track of teen driving data (P?<?.01). Most respondents exhibited some concern of ADAS being susceptible to hacking (57%).

Conclusions: This study represents the first effort to quantify ADAS perceptions among teen drivers and their parents at the U.S. national level. These data highlight potential barriers to ADAS use among teen drivers, including a relative disinterest among teens for ADAS intervention during risky driving as well as concerns among both teens and parents that ADAS will inhibit skill development. These survey findings will help inform educational programs to accelerate fleet turnover and provide the foundation for ADAS optimization and evaluation studies among sociodemographic groups.     

Prevalence of driver physical factors leading to unintentional lane departure crashes

Objective: Some lane-keeping assist systems in development and production provide autonomous braking and steering to correct unintentional lane drift but otherwise require drivers to fully control their vehicles. The goal of this study was to quantify the proportion of drivers involved in unintentional lane drift crashes who would be unable to regain control of their vehicles to inform the design of such systems.

Methods: The NHTSA's National Motor Vehicle Crash Causation Survey collected in-depth, on-scene data for a nationally representative sample of 5,470 U.S. police-reported passenger vehicle crashes during 2005–2007 that occurred between 6 a.m. and midnight and for which emergency medical services were dispatched. The physical states of drivers involved in the 631 lane drift crashes in the sample, which represented 259,034 crashes nationally, were characterized.

Results: Thirty-four percent of drivers who crashed because they drifted from their lanes were sleeping or otherwise incapacitated. These drivers would be unlikely to regain full control of their vehicles if an active safety system prevented their initial drift. An additional 13% of these drivers had a nonincapacitating medical issue, blood alcohol concentration (BAC) ≥ 0.08%, or other physical factor that may not allow them to regain full vehicle control. When crashes involved serious or fatal injuries, 42% of drivers who drifted were sleeping or otherwise incapacitated, and an additional 14% were impacted by a nonincapacitating medical issue, BAC ≥ 0.08%, or other physical factor.

Conclusions: Designers of active safety systems that provide autonomous lateral control should consider that a substantial proportion of drivers at risk of lane drift crashes are incapacitated. Systems that provide only transient corrective action may not ultimately prevent lane departure crashes for these drivers, and drivers who do avoid lane drift crashes because of these systems may be at high risk of other types of crashes when they attempt to regain control. Active lane-keeping assist systems may need to be combined with in-vehicle driver monitoring to identify incapacitated drivers and safely remove them from the roadway if the systems are to reach their maximum potential benefit.     

Development of injury risk models to guide CT evaluation in the emergency department after motor vehicle collisions

Abstract

Objective: The clinical evaluation of motor vehicle collision (MVC) victims is challenging and commonly relies on computed tomography (CT) to detect internal injuries. CT scans are financially expensive and each scan exposes the patient to additional ionizing radiation with an associated, albeit low, risk of cancer. Injury risk prediction based on regression modeling has been to be shown to be successful in estimating Injury Severity Scores (ISSs). The objective of this study was to (1) create risk models for internal injuries of occupants involved in MVCs based on CT body regions (head, neck, chest, abdomen/pelvis, cervical spine, thoracic spine, and lumbar spine) and (2) evaluate the performance of these risk prediction models to predict internal injury.

Methods: All Abbreviated Injury Scale (AIS) 2008 injury codes were classified based on which CT body region would be necessary to scan in order to make the diagnosis. Cases were identified from the NASS-CDS. The NASS-CDS data set was queried for cases of adult occupants who sought medical care and for which key crash characteristics were all present. Forward stepwise logistic regression was performed on data from 2010–2014 to create models predicting risk of internal injury for each CT body region. Injury risk for each region was grouped into 5 levels: very low (<2%), low (2–5%), medium (5–10%), high (10–20%), and very high (20%). The models were then tested using weighted data from 2015 in order to determine whether injury rates fell within the predicted risk level.

Results: The inclusion and exclusion criteria identified 5,477 cases in the NASS-CDS database. Cases from 2010–2014 were used for risk modeling (n?=?4,826). Seven internal injury risk models were created based on the CT body regions using data from 2010–2014. These models were tested against data from 2015 (n?=?651). In all CT body regions, the majority of occupants fell in the very low or low predicted injury rate groups, except for the head. On average, 57% of patients were classified as very low risk and 15% as low risk for each body region. In most cases the actual rate of injury was within the predicted injury risk range. The 95% confidence interval overlapped with predicting injury risk range in all cases.

Conclusion: This study successfully demonstrated the ability for internal injury risk models to accurately identify occupants at low risk for internal injury in individual body regions. This represents a step towards incorporating telemetry data into a clinical tool to guide physicians in the use of CT for the evaluation of MVC victims.