NHTSA has released reports across a spectrum of topics addressing new vehicle technologies. Topics such as the implications of newer cockpit designs on drivers, approaches to address cybersecurity vulnerabilities in modern vehicles, the performance of crash avoidance technologies, and safety applications for communications technology installed on heavy vehicles. NHTSA continues to prioritize vehicle safety research that will help reduce fatalities and injuries.
Driver vehicle interface (DVI) design guidance has been developed as part of a larger research effort intended to perform an initial human factors assessment of driver performance and behavior under Level 2 and Level 3 automated driving. Safe and efficient operation of any motor vehicle requires that the DVI be designed in a manner consistent with driver limitations, capabilities, and expectations. This document is intended to assist DVI developers achieve these outcomes.
This document provides human factors design guidance for driver-vehicle interfaces (DVIs). The guidance provided is based on the findings of current high-quality research (including both the best-available scientific literature and current research being conducted by agencies of the United States Department of Transportation), as well as basic human factors concepts. The design guidance is provided as a complementary resource to other documents and resources, as well as an augment to industry research and existing guidance from the National Highway Traffic Safety Administration.
Cybersecurity Best Practices for Modern Vehicles (PDF, 2.69M)
The document describes NHTSA’s non-binding guidance to the automotive industry for improving motor vehicle cybersecurity. NHTSA believes the voluntary best practices described in the document provide a solid foundation for developing a risk-based approach and important processes that can be maintained, refreshed and updated effectively over time to serve the needs of the automotive industry.
This report describes a framework for establishing sample preliminary tests for automated driving systems, focusing on light-duty vehicles with higher levels of automation, where the system is required to perform the full dynamic driving task, including lateral and longitudinal control, as well as object and event detection and response. It took the first steps of partitioning the ADS performance space as a test framework of independent factors, and mapped forward refining the testing framework through methods of modeling, simulation, track testing, and open road testing. Outcomes included identifying tactical maneuver/competency behaviors from various sources; identifying the ADS operational design domains; and developing evaluation.
This report describes research assessing functional safety of a generic automated lane centering (ALC) system, a key technology supporting vehicle automation by providing continuous lateral control to keep the vehicle in its travel lane. This study follows the concept phase process in the ISO 26262 standard and applies hazard and operability study, functional failure modes and effects analysis, and systems-theoretic process analysis (STPA) methods. This study identifies 5 vehicle-level safety goals, 47 functional safety requirements (an output of the STPA process) for the ALC system, and 26 additional safety requirements (also an output of the STPA process) for the ALC system based on the results of the safety analysis. This study also uses the results of the analysis to develop potential test scenarios and identify possible areas for diagnostic trouble code coverage. The document appendices are in a separate document.
This report covers a field study of vehicle crash warning technologies using an innovative large-scale data collection technique for gathering information about the crash avoidance systems and how drivers respond to them. Although the specific system studied was the General Motors camera-based forward collision alert and lane departure warning system, this technique could be applied to other emerging active safety crash avoidance systems. The study team found that this data collection technique has several strengths including cost, sample size, and naturalistic testing by having drivers using their own vehicles where they can adjust system settings or even turn systems off. The technique allowed researchers to study possible long-term changes in how drivers adapt to such systems, and to acquire “rapid-turnaround” large-scale results in an efficient manner.
This study will help support the development of V2P based collision avoidance technologies and examined the GES and FARS crash databases in order to classify 21 pedestrian pre-crash scenarios based on different vehicle and pedestrian maneuvers. These scenarios were ranked based on associated costs, and five priority scenarios were selected that represent 88 percent of pedestrian crash costs. For the priority scenarios crash contributing factors were examined and quantified to identify common occurrences in crashes, including physical settings, environmental conditions, and driver and pedestrian characteristics. Kinematic equations describing the crash scenarios were also derived and exercised to obtain estimates of the minimum stopping distances for various vehicle velocities and braking levels. The goal of this study was to develop an updated understanding of the pedestrian crash problem and the potential of V2P technology to address pedestrian crashes.
This study developed and exercised a methodology to estimate the potential safety benefits of pedestrian crash avoidance/mitigation (PCAM) systems. PCAM systems can avoid a pedestrian crash by warning the driver of an impending crash and/or applying Automatic External Braking (AEB). This report examines the GES and FARS crash databases to develop a target population of pedestrian crashes that are addressable by PCAM systems. These crashes fit into two general scenarios: 1) vehicle going straight and the pedestrian crossing the roadway, and 2) vehicle going straight and pedestrian in or adjacent to the roadway, stationary or moving with or against traffic.
This report describes an independent evaluation and analysis of methods and results of data gauging heavy-truck driver acceptance of collision warning based on V2V communication technology during driver acceptance clinics. V2V technology transmits vehicle information—location, size, and speed— to predict impending collisions and warn the driver. Results suggest V2V safety warnings have a high acceptance rate among heavy truck drivers. Results from the clinics will help shape future research into improved V2V safety applications for heavy vehicles.
Test procedures to evaluate the blind spot warning/lane change warning (BSW/LCW) safety application of commercial vehicles with vehicle-to-vehicle (V2V) equipment. The prototype V2V equipment was observed to be capable of tracking potential BSW/LCW threats, but occasionally the equipment would not recognize that a vehicle was in the V2V equipment determined blind spot warning zone due to the equipment’s error in estimating the lateral range between the vehicles. The V2V equipment determined blind zone was different for each side of the vehicle evaluated in this study (shorter on right side). When the turn signals were activated, the blind zone was extended by a time based on the closing speed of the approaching vehicle. The BSW/LCW test procedures are generally well developed but the blind zone definition for commercial vehicles/tractor-trailers combinations needs to be further refined.
This report documents NHTSA’s test track research performed to support development of objective test procedures to evaluate the forward collision warning (FCW) safety application of commercial vehicles with vehicle-to-vehicle (V2V) equipment. The prototype V2V equipment was observed to be capable of tracking potential FCW threats, but had some issues when vehicles were in a curve or when switching lanes. For the curve tests, the V2V equipment had trouble determining the lateral distance between the host vehicle (HV – test subject) and the remote vehicle (RV – collision threat) for certain scenarios. Future testing with commercial vehicles equipped with V2V technology will be required to fully develop some of the FCW objective test track procedures and performance metrics.
In the General Crash Avoidance and Electronic Systems Safety Docket (NHTSA-2018-0027):
- Traffic Jam Assist System Confirmation Test (Working Draft)
- Blind Spot Intervention System Confirmation Test (Working Draft)
- Active Park Assist System Confirmation Test (Working Draft)
NHTSA will soon release a series of reports regarding advanced driver assistance systems, Automated Driving Systems, vehicle connectivity, and technical translations of federal standards. The working drafts of test procedures will cover pedestrian automatic emergency braking, rear automatic braking, and pedestrian crash avoidance systems. NHTSA will also make public reports on target populations for concept Automated Driving Systems, assessments of technologies such as automated lane centering, naturalistic data regarding use of current advanced driver assistance systems, cybersecurity on heavy vehicles, and heavy vehicle V2V messaging. NHTSA continues to prioritize vehicle safety research that can be leveraged to help reduce fatalities and injuries.