Center for Advanced Automotive Research

The Center for Advanced Automotive Research (CAAR) focuses on the research, development and evaluation of next generation automotive systems. CAAR is staffed by a multidisciplinary team of dedicated individuals who are passionate about improving the safety and efficiency of our nation’s transportation system. This team strives to solve a broad set of challenges associated with integrating cutting-edge technologies into the vehicles of tomorrow. The primary research areas of CAAR include crash warning/avoidance/mitigation, connected vehicles, driver-vehicle interfaces, crash causation, and vehicle automation. CAAR comprises two research groups: the Advanced Product Test and Evaluation (APTE) group and the Connected & Advanced Vehicle Systems (CAVS) group. These groups work cooperatively with their industry and governmental partners to solve complex transportation problems through technology advancement.

Zac Doerzaph
Center Director

V2V DVI Characteristics On-Road Study

Connected-vehicle technologies enable communication between vehicles (V2V) and between vehicles and infrastructure (V2I). This communication is used by various in-vehicle applications to improve the safety, mobility, and sustainability of the transportation system as well as enrich the driving experience. The communication between vehicles and infrastructure provides a perfect opportunity to generate timely crash warning system (CWS) alerts. Read More

V2V DVI Characteristics On-Road Study

Connected-vehicle technologies enable communication between vehicles (V2V) and between vehicles and infrastructure (V2I). This communication is used by various in-vehicle applications to improve the safety, mobility, and sustainability of the transportation system as well as enrich the driving experience. The communication between vehicles and infrastructure provides a perfect opportunity to generate timely crash warning system (CWS) alerts.

CWSs alert drivers of a specific safety condition such as a forward collision warning (FCW) and require a time-sensitive response. When developing a CWS, it is necessary to consider the associated driver-vehicle interface (DVI) to encourage appropriate responses. Among the aspects of the DVI to consider are the modalities (visual, auditory, and tactile) of the displays that are used to alert the driver of an impending crash conflict. It is common for CWSs to include both a visual icon as well as an auditory component to warn a driver.  Further, tactile warnings (e.g., haptic seat vibrations) are emerging as features of some CWSs. Human factors research is needed to determine the effects of different CWS parameters on driver performance and thus maximize the benefit of these warnings to elicit correct driver responses to potential conflicts.

This study examines these characteristics of DVIs associated with an FCW alert, and intersection movement assist (IMA) warning, and left turn across path (LTAP) warning in light vehicles. The primary goal of this research is to improve the effectiveness of a CWS DVI for V2V communications in light vehicles.

This NHTSA-sponsored project began in April 2014 and will conclude in January 2016.

Countermeasures to Prevent Underage Fatalities from Alcohol-Related Traffic Crashes

Traffic fatalities are the leading cause of death for youth ages 8-20 (NHTSA, 2012). Many of these traffic crashes are the direct result of alcohol-impaired driving. Over 30% of youth drivers ages 15-20 killed in traffic crashes have a positive Blood Alcohol Concentration (BAC), and 26% are over the legal level of impairment (NHTSA, 2013). Research-driven solutions are necessary to address youth drinking and driving. Read More

Countermeasures to Prevent Underage Fatalities from Alcohol-Related Traffic Crashes

Traffic fatalities are the leading cause of death for youth ages 8-20 (NHTSA, 2012). Many of these traffic crashes are the direct result of alcohol-impaired driving. Over 30% of youth drivers ages 15-20 killed in traffic crashes have a positive Blood Alcohol Concentration (BAC), and 26% are over the legal level of impairment (NHTSA, 2013). Research-driven solutions are necessary to address youth drinking and driving.

The efficacy of a variety of legislative and programmatic approaches to this problem has been demonstrated in the research literature. This is particularly true for legislative approaches such as the 21 minimum legal drinking age (Fell, Fisher, Voas, Blackman, & Tippetts, 2009; Shults et al., 2001), graduated driver licensing with night driving restrictions and use/lose laws (Fell, Todd, & Voas, 2011), social host liability (Dills, 2010), prices and taxing (Wagennar, Tobler, & Komro, 2010), and bans on alcohol advertising targeting minors (Smith & Geller, 2009). Unfortunately, these solutions are often costly and fail to target a community’s precise needs. Furthermore, a systematic review of the countermeasure literature for alcohol-involved underage traffic fatalities has never been conducted to identify efficacious programs or best practices.

In order to identify and evaluate existing effective underage drinking countermeasures that reduce vehicle crashes the National Highway Traffic Safety Administration (NHTSA) is sponsoring research to conduct an extensive literature review in this domain. This includes a comprehensive literature search across a multitude of search engines and interfaces. The search spans literature from multiple academic disciplines and regions of the world. Relevant research will be identified and coded based on countermeasure components, efficacy, and methodological rigor. The final product will be the first large-scale assessment of effective countermeasures/programs that reduce underage drinking and specifically improve traffic outcomes.

Human Factors Evaluation of an In-Vehicle Active Traffic and Demand Management (ATDM) System

Active Traffic and Demand Management (ATDM) is designed to manage roadway traffic and reduce congestion while improving safety. As a traditionally infrastructure-centric application, ATDM uses dynamic signs (often on overhead gantries) to provide relevant regulatory and informational content to drivers. With Connected Vehicles, the ATDM interface may instead be located inside vehicles, allowing messages to be more ubiquitous and salient, while also decreasing infrastructure cost to road operators and road sign clutter along the roadway. However, in-vehicle devices can have negative consequences such as driver distraction, driver dependence, complacency, and annoyance. Read More

Human Factors Evaluation of an In-Vehicle Active Traffic and Demand Management (ATDM) System

Active Traffic and Demand Management (ATDM) is designed to manage roadway traffic and reduce congestion while improving safety. As a traditionally infrastructure-centric application, ATDM uses dynamic signs (often on overhead gantries) to provide relevant regulatory and informational content to drivers. With Connected Vehicles, the ATDM interface may instead be located inside vehicles, allowing messages to be more ubiquitous and salient, while also decreasing infrastructure cost to road operators and road sign clutter along the roadway. However, in-vehicle devices can have negative consequences such as driver distraction, driver dependence, complacency, and annoyance.

The following research study focuses on the development and Human Factors evaluation of an in-vehicle ATDM system deployed on the I-66 corridor in Northern Virginia. The purpose of this research is to determine if in-vehicle signage, coupled with ATDM, can successfully manage traffic while maintaining a balance between salience and annoyance of the associated message system.

In-Vehicle Device
The in-vehicle ATDM features will include 1) dynamic speed limits, 2) dynamic lane use/shoulder control, 3) High Occupancy Vehicle (HOV) restrictions, and 4) other traveler information through variable message signs (VMS). In addition, this system is equipped with various audio and visual alerts in order to notify to driver when relevant information has been updated. There will be 40 total participants in this study – 20 participants will be traveling during peak hours, and 20 participants will be traveling during non-peak hours in order to generate data on the in-vehicle system with varying traffic levels.

Participant Questionnaires
During the drive, participants will be asked to respond modified NASA Task Load Index questions regarding each of the alerts administered along the route. The NASA TLX questions will ask the participant to rate the following categories from 1 – 5 (low to high): mental demand, temporal demand, comprehension, effort, and frustration.

In addition to the modified NASA Task Load Index questions, participants will also complete pre and post-drive questionnaires aimed to capture the participant’s impressions of the in-vehicle system, including attributes such as: desirability, distractibility, driver behavior, general concerns, and areas of improvement.

Anticipated Results
It is currently anticipated that drivers will respond positively to the in-vehicle ATDM system. There may be some evidence of distraction due to the in-vehicle setup, but it is expected that the level of distraction will not be significant enough to negatively affect driver safety. It will be interesting to determine whether drivers find the alerts helpful, receive feedback regarding the design of the in-vehicle system, obtain any suggestions for improvement, and ascertain if drivers would like to have this technology incorporated inside their own vehicles.

Vehicle-Based Basic Safety Message (BSM) Generator for Accelerating Deployment

The initial deployment of V2X connected-vehicles will not produce immediate benefits. Considering that the average survivability of vehicles in the United States is approximately 15 years [NHTSA 2006], the market penetration needed for the benefits associated with connected-vehicle systems won’t be fully realized for some time. Even if all new vehicles are mandated to include such systems in addition to aftermarket devices, a disproportionate amount of non-connected vehicles compared to connected vehicles will continue to exist for some time. Since very few connected vehicles will be initially deployed, the environment will be incomplete in terms of data available for connected-vehicle applications. Read More

Vehicle Based BSM Generator for Accelerating Deployment

The initial deployment of V2X connected-vehicles will not produce immediate benefits. Considering that the average survivability of vehicles in the United States is approximately 15 years [NHTSA 2006], the market penetration needed for the benefits associated with connected-vehicle systems won’t be fully realized for some time. Even if all new vehicles are mandated to include such systems in addition to aftermarket devices, a disproportionate amount of non-connected vehicles compared to connected vehicles will continue to exist for some time. Since very few connected vehicles will be initially deployed, the environment will be incomplete in terms of data available for connected-vehicle applications.

To overcome this problem, it is proposed to use ranging sensors that are now becoming increasingly common in new vehicles. By accessing this sensor, relative distances and speeds of other vehicles can be determined. This information can then be packaged into a Basic Safety Message (BSM) and transmitted over-the-air (OTA) by a Generating Host Vehicle (GHV) for use by other connected vehicles or infrastructure applications. By utilizing ranging sensors and connected vehicle systems, early deployment benefits for both drivers and infrastructure are increased.

The proposed research project focuses on development of a BSM generating algorithm implemented to expedite the benefits of connected vehicle systems. If positive performance results are gained, the proof of concept can then be leveraged to support:

  • NHTSA V2V decision
  • Connected-automation information sharing (i.e. Cooperative Active Cruise Control in the presence of non-connected traffic)
  • Enhancement to current V2X messages
  • Creation of new V2X messages
  • New application development
  • Connected vehicle misbehavior detection
  • CVI-UTC research capabilities

Connected Vehicle Virginia Testbed System Performance

If the Connected Vehicle Virginia Test Bed is to support a full-scale regional deployment, the environment must be able to effectively handle the volume of connected vehicles. In such an environment, the benefits of vehicle-to-vehicle/infrastructure (V2X) systems hinge on the ability to securely, transmit, receive, and process information. Synonymous to actual traffic jams, a similar situation may exist on the Vehicle-to-Infrastructure (V2I) 'information super-highway.' Stop-and-go traffic is a common occurrence along I-66 and its arterials. If all of the vehicles were instrumented with V2X technologies, spectral channels and network devices may become locally congested due to the amount of over-the-air (OTA) transmissions. If OTA transmissions are not properly handled, this may result in the interruption of key V2X applications. Read More

Connected Vehicle Virginia Testbed System Performance

If the Connected Vehicle Virginia Test Bed is to support a full-scale regional deployment, the environment must be able to effectively handle the volume of connected vehicles. In such an environment, the benefits of vehicle-to-vehicle/infrastructure (V2X) systems hinge on the ability to securely, transmit, receive, and process information. Synonymous to actual traffic jams, a similar situation may exist on the Vehicle-to-Infrastructure (V2I) 'information super-highway.' Stop-and-go traffic is a common occurrence along I-66 and its arterials. If all of the vehicles were instrumented with V2X technologies, spectral channels and network devices may become locally congested due to the amount of over-the-air (OTA) transmissions. If OTA transmissions are not properly handled, this may result in the interruption of key V2X applications.

Network congestion may occur from a multitude of different sources, chiefly connected vehicle transmission density. Considering the physical traffic distribution along I-66 and arterials, a common occurrence is traffic jams. If all of the vehicles were instrumented with V2X technologies, localized spectrum congestion may occur. This is due to the number of vehicles transmitting messages OTA. In addition to spectral congestion, networked devices may also be put under extreme processing load and backhaul networks may reach bandwidth limitations, as each interconnected device that processes network data may become a bottleneck.

Based on hourly traffic distribution provided in a FHWA I-66 West Bound Traffic Density Research Project [FHWA 132-133], a projection of data transmitted by vehicles and processed by the infrastructure can hit peaks in upwards of 1TB of data per hour. The projection assumes that all vehicles are transmitting 378 byte messages OTA at a rate of 10 Hz per Crash Avoidance Metrics Partnership (CAMP) research parameters [NHTSA 65]. In addition, the total projected data throughput is calculated by accounting for all other RSEs in the network.

Research in V2V communications scalability has already been performed by entities such as CAMP. On the other hand, V2I based research results are not readily available or incomplete due to the lack of equivalent connected vehicle test bed environments. Much can be gained in implementing a similar research methodology performed by CAMP and adapting it for V2I. Such results can better serve the research community, but more importantly verify the functionality of the Connected Vehicle Virginia Test Bed.

In an effort to identify system limitations, the project will run experimental studies focusing on stressing the wireless and backhaul networks on the Connected Vehicle Virginia Test Bed. By understanding what links break between equipped vehicles, roadside equipment, and network infrastructure, limitations can be characterized and improvements can be made when feasible.

Execution of the project plans to facilitate:

  • Identification of Network Bottlenecks
  • Identification of Load Shedding Strategies (i.e. data suppressing, message sequencing, or formatting)
  • Understand Impact of RSSI, Packet Error Rate, Inter Packet Gap as a function of Range, Speed, Elevation, Heading under various scalability test scenarios
  • Support USDOT NHTSA Affiliated Test Bed Research and Deployment Requirements

Advanced Product Test and Evaluation

Eddy Llaneras
Group Leader

The Advanced Product Test and Evaluation group (APTE) is dedicated to assessing and evaluating a range of in-vehicle driver convenience, safety, and technology applications on light passenger vehicles using test-track, controlled on-road studies, and naturalistic research methods. The applied nature of the work is intended to support Original Equipment Manufacturers and Automotive Suppliers in designing and improving the effectiveness of systems that quantify performance benefits, unintended consequences, and potential misuse while also characterizing driver acceptance, use, reliance, and comprehension of advanced vehicle systems.

Tyler Bray

Senior Research Specialist

Brad Cannon

Research Associate

John Delong

Senior Research Specialist

Jason Meyer

Research Associate

Connected & Advanced Vehicle Systems

The Connected & Advanced Vehicle Systems (CAVS) group is focused on leveraging connected vehicle technologies to reduce the societal costs associated with vehicle collisions. CAVS focuses on the design, development, and evaluation of connected-vehicle systems with a focus on overall system performance. This includes activities leading to improved driver-vehicle interfaces as well as enhanced communications, positioning, and integration capabilities. The group works closely with both industry and government partners to promote the state of knowledge of connected-vehicle systems and to understand the potential benefits of full-scale system deployment.

Luke Neurauter
Group Leader

Nick Britten

Lead Research Specialist

Andy Earthman

Project Assistant

Eric Glenn

Senior Research Specialist

Tom Gorman

Research Associate

Hyungil Kim

Senior Research Associate

Christine Link-Owens

Recruitment Group Manager

Amy Maxey

Project Assistant

Marty Miller

Research Associate

Miao Song

Research Associate

Reginald Viray

Research Associate

Jacob Walters

Senior Research Specialist