These safety research projects focus on testing, studying and ideally connecting vehicle systems designed to help prevent or mitigate crashes.
With the ultimate goal of understanding driver capabilities and limitations, this research is focused on the interaction between drivers, vehicles, and the environment.
Transportation safety goes beyond vehicle features. By focusing on gathering and analyzing data, these projects give our researchers insight into broader safety issues.
To understand how to better protect in the event of a crash, these projects focus on reducing the effects of a collision on vehicle occupants and pedestrians.
This project is a collaboration with Virginia Tech Transportation Institute (VTTI) and Michigan Tech Research Institute (MTRI)
A study to develop testing protocols for automotive PCS designed to prevent and mitigate animal-related vehicle crashes by examining crash data, collecting and analyzing naturalistic driving data, and radar scanning deer in order to better establish test parameters.
This project is a collaboration with The Ohio State University, University Of Michigan Transportation Research Institute and Virginia Tech
A project to develop a detailed test procedure for Lane Departure Warning (LDW) and Lane Departure Prevention (LDP) systems. This procedure will be used to evaluate the performance of two test vehicles, a Toyota and another make, equipped with the LDW and LDP systems.
A study to estimate the safety benefits of Lane Departure Warning (LDW) Systems.
CSRC and VT will combine crash data from multiple databases from NHTSA, including NASS – CDS (which contains details of severe crashes) and NMVCCS (which contains crash causation details) along with vehicle EDR data from individual vehicles to analyze and identify the most frequently occurring crash scenarios.
These scenarios, along with a model representing drivers, will be used to estimate the safety benefits of installing LDW systems on vehicles, including associated crash and injury reduction rates.
This project is a collaboration with TASI – Indiana University, Purdue University at Indianapolis and Ohio State University
A study to develop testing protocols for automotive Pedestrian PCS designed to prevent and mitigate pedestrian vehicle crashes using NHTSA crash databases and other data sources for pedestrian PCS testing, to develop more sophisticated and realistic test scenarios.
Toyota’s CSRC and TASI have teamed up to help define and develop these test procedures along with specifications for a surrogate pedestrian target that can be used in vehicle tests.
The study will examine crash data from NHTSA databases including FARS, CDS, NASS-GES and NMVCCS, and use the collected information to identify the most frequent pedestrian crash scenarios.
Since there is very little pedestrian pre-crash data in existing crash databases, researchers will utilize a vehicle equipped with video data recorder to capture near-miss data from actual driving experiences.
This project is a collaboration with University Of Michigan Transportation Research Institute and Michigan Tech Research Institute
A multidisciplinary project to develop test procedures for vehicle pre-collision systems in order to help consumers and the government compare technologies across the automotive industry.
Researchers will also use radar scanning technology, such as Michigan Tech Research Institute's (MTRI) Radar Scanner, to develop a surrogate target that can be used to accurately represent real vehicles on the road in crash tests.
Researchers will use the collected data to recommend test procedures, validating the surrogate target against multiple vehicles to ensure that test procedures are applicable across many manufacturers.
An analysis of the average Time to Collision (TTC) following the application of the brake, based on naturalistic driving data in forward-collision scenarios, in order to help establish the necessary distances and warning timings for Forward Collision Warning systems.
An analysis of existing crash and naturalistic driving data to investigate the factors associated with crashes and non-crashes at intersections, as well as to estimate the benefits of a system that could detect and warn in such scenarios.
A three-year project that examines and tests the belief that with brain appropriate training, older drivers can increase their driving safety with improved speed of processing and useful field of view – two physical factors which shrink with aging.
To help limit the risk to senior drivers and others, researchers are studying how brain training exercises can help senior drivers restore their field of vision.
The project’s goal is to evaluate whether brain fitness testing improves useful field of vision and to examine whether it can reduce the risk of crash events for senior drivers.
A survey of 5,600 teens and adults to examine their distracting behaviors while driving, identify social norms for both teens and parents and develop effective recommendations to help change dangerous behaviors.
A two-year study to learn how the use of an in-vehicle voice command system affects driver behavior, in order to provide the NHTSA with findings to help inform future research and the development of voluntary guidelines.
Toyota’s CSRC and the MIT AgeLab have partnered to study these workload demands and work toward developing tools to assess the development of production voice interface systems.
The study will also utilize both a fixed based driving simulator to collect physiological effects as well as an on-road driving experience to collect driving performance data.
A program to extend previous research on the relationship between the use of in-vehicle voice command systems and driver behavior to additional production vehicles and provide understanding of the ability of standardization of Phase 1 findings.
A three-year study to determine what types of feedback are most effective in helping inhibit risky behaviors, as well as when feedback can become a potential distraction, what types of individuals are more susceptible to feedback, how drivers adapt to feedback over time and whether the safety benefits of feedback persist even when it is no longer available.
Combining research in the fields of driver behavior, cognitive psychology, and cognitive neuroscience, this three-year study will advance the auto industry’s understanding of the cognitive aspect of driver distraction and how to measure cognitive load related to various secondary tasks.
The project will investigate the relationship between driver characteristics and the demands associated with in-vehicle driver tasks.
Building on past research specific tasks used in The Crash Avoidance Metrics Partnership (CAMP) Driver Workload Metrics (DWM) project will be used to assess the impact of cognitive distraction on driver behavior.
Once the model has been created, laboratory simulator tools will be developed to validate the expected results from lab tests of driver distraction.
A study aimed at developing driver response models for crash avoidance behavior in PCS (Pre-Collision Safety), pedestrian PCS and Lane Departure scenarios, with a goal of designing testing scenarios for Advanced Driver Assistance Systems; simulator modules for testing PCS, Ped-PCS and LD scenarios; and crash avoidance driver response models that can be validated with Naturalistic Driving data.
A three-year project to develop a set of psychological principles that will guide the design of a driver vehicle interface that provides effective, real-time support for drivers of a partially intelligent vehicle (PIV).
A three-year study to determine how some older drivers may have declining abilities relative to driving, potentially increasing driving risk, and how they may use in-vehicle technologies.
This project is intended to develop a system of feedback and coaching to help teenage drivers reduce unsafe driving acts and lower their rate of auto-related injuries and death.
Throughout the study, a data acquisition system will record video and vehicle data for all driving events. The teens will get immediate feedback for risky behaviors or maneuvers in the form of a warning light or an audible alert. Delayed feedback will be a weekly report card, sent to parents.
Teenage drivers have a higher risk of being in a motor vehicle crash and sustaining injury than any other driving populations.
A comprehensive three-year study of pre-drive behavior, such as where the feet are placed prior to beginning the drive, to determine its influence on driver-vehicle interactions.
This project is a collaboration with Children's Hospital Of Philadelphia, Center for Child Injury Prevention Studies (CChIPS), NHTSA and SAFER
A season-long study of a youth ice hockey team to better understand the mechanisms of mild traumatic brain injury (mTBI) in adolescents, the most common injury to children in vehicular accidents.
This project is developing vehicle computer systems that not only notify first responders in the event of a crash, but also predicts for them the likelihood and severity of occupant and driver injuries.
To validate the algorithms, researchers will input crash event details from actual cases. Comparing the algorithms’ predictions to the actual outcomes of these crash events will help inform further refinements.
This project is working to develop a detailed crash data archive to help better understand crash mechanisms and improve in-vehicle safety countermeasures.
The project will begin by establishing what data is needed for more effective crash analysis and then finalize the data collection process.
Researchers will then prioritize crash locations for study based on crash frequency, collecting site characteristics through the use of on-board cameras, such as site conditions and environmental barriers, which may be difficult to capture in written reports by police.
The collected data will be analyzed to identify the potential causes of crashes, as well as to support the development of countermeasures.
This study is focused on developing systematic and automated tools for monitoring and analyzing driver behavior in full context, including the vehicle and environment, to better understand dangerous situations and to inform the design of effective counter-measures.
A three-year study aimed at using the SHRP2 Naturalistic Driving Study to develop a de-identified database of distracted and baseline driving events that can be used to support in-depth studies of driver distraction.
This project studies the effective ways to establish a new National Child Occupant Special Study database in order to improve how we keep children safe in vehicles.
Collecting this critical data, such as the specific type and usage characteristics of the safety restraints could help researchers look for new ways to enhance the safety of child occupants in motor vehicles.
The results of this study will help identify the key methodologies features that lead to collection of the best breadth and depth of child specific crash injury data.
This project is a collaboration with Universidad Anahuac Mexico Norte and Universidad Nacional Autonoma de Mexico
A project to develop a prototype information system which contributes to the monitoring of goals set by Mexico under the “Decade of Action for Road Safety 2011-2020.”
A study that examines the relationship between age and abdominal injuries from automobile crashes to find new ways to better protect vulnerable populations of drivers and passengers.
A four-and-a-half-year study to develop human body finite element (FE) models for children and older people (two vulnerable populations) so that engineers can account for differences in their body characteristics when designing vehicle safety systems and ultimately reduce injuries to all occupants regardless of age.
A study designed to establish an accurate simulation of rollover crash events that can establish realistic vehicle and occupant positions and kinematics at the time of first impact.
A study of the capabilities of Toyota’s pedestrian THUMS modeling system in accurately modeling the injuries suffered by pedestrians in various vehicle/pedestrian collision scenarios.
A study to go beyond traditional Finite Element Models to create parametric Human Body Modeling techniques for auto safety research that will allow engineers to simulate injuries to a wide range of vehicle occupants, including specific individuals, by semi-automating changes to the models’ body shape and posture.
A five-year project to combine collision reconstruction data with Finite Element Modeling to better understand how to reduce injuries caused by vehicle collisions, allowing researchers to pinpoint which changes to vehicle design could have prevented the actual injuries suffered by vehicle occupants.
A project that is meant to learn more about how Toyota’s Total Human Model for Safety (THUMS) models perform in crash tests at a “whole body” level.
The project will run for two-and-a-half years. In the first year, researchers will prepare to run the simulation, develop sled models, and analyze the test data to determine response corridors.
A Finite Element (FE) model will be created of the test environment based on controlled front- and side-sled impact tests the University of Virginia has previously performed on PMHS.
This project is a study of the relationship between age and how the occupant sits in, and interacts with, the vehicle due to posture and body shape changes in order to find new ways to protect older drivers and passengers.