Search Results

This research focused on developing a methodology for a vehicle dynamics model of a passenger vehicle outfitted with an aftermarket Automated Driving System software package using only literature and track based results. This package consisted of Autoware.AI (Autoware ®) operating on Robot Operating System 1 (ROS™) with C++ and Python ®. Initial focus was understanding the basics of ROS and how to implement test scenarios in Python to characterize the control systems and dynamics of the vehicle. As understanding of the system continued to develop, test scenarios were adapted to better fit system characterization goals with identification of system configuration limits. Trends from on-track testing were identified and paired with first-order linear systems to simulate physical vehicle responses to given command inputs. Sub-models were developed and simulated in MATLAB ® with command inputs from on-track testing.

In order to validate the operation of advanced driver assistance systems (ADAS), tests must be performed that assess the performance of the system in response to different scenarios. Some of these systems are designed for crash-imminent situations, and safely testing them requires large stretches of controlled pavement, expensive surrogate targets, and a fully functional vehicle. As a possible more-manageable alternative to testing the full vehicle in these situations, this study sought to explore whether these systems could be isolated, and tests could be performed on a bench via a hardware-in-the-loop methodology. For camera systems, these benches are called Camera-in-the-Loop (CiL) systems and involve presenting visual stimuli to the device via an external input.

This paper examines variability of two static rollover metrics, Static Stability Factor (SSF) and Tilt Table Ratio (TTR), due to vehicle loading and vehicle-to-vehicle variation. Variability due to loading was determined by measuring SSF and TTR for 14 vehicles/configurations at multiple loadings. Up to five loadings were used per vehicle/configuration tested. Vehicle-to-vehicle variability was studied by measuring SSF and TTR for ten unmodified vehicles of each of four make/models. Five baseline vehicles, as similar as was feasible, were tested. The other five test vehicles spanned the range of submodels and options available. In general, both SSF and TTR decreased as occupants were added to a vehicle. The change in SSF and TTR per occupant was fairly consistent, with changes in TTR being more consistent. Placing ballast on the floor of the cargo compartment had a mixed effect on SSF, raising it for some vehicles and lowering it for others.

This paper discusses the importance of having an adequate model for the dynamic response characteristics of tire lateral force to steering inputs. Computer simulation and comparison with experimental results are used to show the importance of including appropriate tire dynamics in simulation tire models to produce accurate predictions of vehicle dynamics. Improvements made to the tire dynamics model of an existing vehicle stability and control simulation, the Vehicle Dynamics Analysis, Non-Linear (VDANL) simulation, are presented. Specifically, the improvements include changing the simulation's tire dynamics from first-order system tire side force lag dynamics to second-order system tire slip angle dynamics. A second-order system representation is necessary to model underdamped characteristics of tires at high speeds. Lagging slip angle (an input to the tire model) causes all slip angle dependent tire force and moment outputs to be lagged.

As Intelligent Transportation Systems (ITS) become more prevalent, the need to archive data from field tests becomes more critical. These data can guide the design of future systems, provide an information conduit among the many developers of ITS, enable comparisons across locations and time, and support development of theoretical models of driver behavior. The National Highway Traffic Safety Administration (NHTSA) is interested in such an archive. While a design for an ITS data archive has not yet been developed, NHTSA has supported the enhancement of the Test Planning, Analysis, and Evaluation System (Test PAES), originally developed by Calspan SRL Corporation for the U. S. Air Force Armstrong Laboratory, for possible use in such an archive. On a single screen, Test PAES enables engineering unit data, audio, and video, as well as a vehicle animation, to be time synchronized, displayed simultaneously, and operated with a single control.

In crashes between heavy trucks and light vehicles, most of the fatalities are the occupants of the light vehicle. A reduction in heavy truck stopping distance should lead to a reduction in the number of crashes, the severity of crashes, and consequently the numbers of fatalities and injuries. This study made use of the National Advanced Driving Simulator (NADS). NADS is a full immersion driving simulator used to study driver behavior as well as driver-vehicle reactions and responses. The vehicle dynamics model of the existing heavy truck on NADS had been modified with the creation of two additional brake models. The first was a modified S-cam (larger drums and shoes) and the second was an air-actuated disc brake system. A sample of 108 CDL-licensed drivers was split evenly among the simulations using each of the three braking systems. The drivers were presented with four different emergency stopping situations.

This study was performed to showcase the possible applications of the Hardware-in-the-loop (HIL) simulation environment developed by the National Highway Traffic Safety Administration (NHTSA), to test heavy truck crash avoidance safety systems. In this study, the HIL simulation environment was used to recreate a simulation of an actual accident scenario involving a single tractor semi-trailer combination. The scenario was then simulated with and without an antilock brake system (ABS) and electronic stability control (ESC) system to investigate the crash avoidance potential afforded by the tractor equipped with the safety systems. The crash scenario was interpreted as a path-following problem, and three possible driver intended paths were developed from the accident scene data.

This paper summarizes the results of test maneuvers devised to measure on-road, untripped, rollover propensity. Complete findings from this research are contained in [1]. Twelve test vehicles, representing a wide range of vehicle types and classes were used. Three vehicles from each of four categories: passenger cars, light trucks, vans, and sport utility vehicles, were tested. The vehicles were tested with vehicle characterization and untripped rollover propensity maneuvers. The vehicle characterization maneuvers were designed to determine fundamental vehicle handling properties while the untripped rollover propensity maneuvers were designed to produce two-wheel lift for vehicles with relatively higher rollover propensity potential. The vehicle characterization maneuvers were Pulse Steer, Sinusoidal Sweep, Slowly Increasing Steer, and Slowly Increasing Speed. The rollover propensity maneuvers were J-Turn, J-Turn with Pulse Braking, Fishhook #1 and #2, and Resonant Steer.

Testing vision-based advanced driver assistance systems (ADAS) in a Camera-in-the-Loop (CiL) bench setup, where external visual inputs are used to stimulate the system, provides an opportunity to experiment with a wide variety of test scenarios, different types of vehicle actors, vulnerable road users, and weather conditions that may be difficult to replicate in the real world. In addition, once the CiL bench is setup and operating, experiments can be performed in less time when compared to track testing alternatives. In order to better quantify normal operating zones, track testing results were used to identify behavior corridors via a statistical methodology. After determining normal operational variability via track testing of baseline stationary surrogate vehicle and pedestrian scenarios, these operating zones were applied to screen-based testing in a CiL test setup to determine particularly challenging scenarios which might benefit from replication in a track testing environment.

This paper presents National Highway Traffic Safety Administration’s 2017 and 2018 test track research results with heavy vehicles equipped with forward collision warning and automatic emergency braking systems. Newly developed objective test procedures were used to perform and collect performance data with three single-unit trucks equipped with the crash avoidance systems. The results of this research show that the test procedures are applicable to many heavy vehicles and indicate that performance improvements in heavy vehicles equipped with these safety systems can be objectively measured.

Driver distraction has been identified as a high-priority topic by the National Highway Traffic Safety Administration, reflecting concerns about the compatibility of certain in-vehicle technologies with the driving task, whether drivers are making potentially dangerous decisions about when to interact with in-vehicle technologies while driving, and that these trends may accelerate as new technologies continue to become available. Since 1991, NHTSA has conducted research to understand the factors that contribute to driver distraction and to develop methods to assess the extent to which in-vehicle technologies may contribute to crashes. This paper summarizes significant findings from past NHTSA research in the area of driver distraction and workload, provides an overview of current ongoing research, and describes upcoming research that will be conducted, including research using the National Advanced Driving Simulator and work to be conducted at NHTSA’s Vehicle Research and Test Center.

According to NHTSA's 2011 Traffic Safety Facts [1], passenger vehicle occupant fatalities continued the strong decline that has been occurring recently. In 2011, there were 21,253 passenger vehicles fatalities compared to 22,273 in 2010, and that was a 4.6% decrease. However; large-truck occupant fatalities increased from 530 in 2010 to 635 in 2011, which is a 20% increase. This was a second consecutive year in which large truck fatalities have increased (9% increase from 2009 to 2010). There was also a 15% increase in large truck occupant injuries from 2010. Moreover, the fatal crashes involving large trucks increased by 1.9%, in contrast to other-vehicle-occupant fatalities that declined by 3.6% from 2010. The 2010 accident statistics NHTSA's report reveals that large trucks have a fatal accident involvement rate of 1.22 vehicles per 100 million vehicle miles traveled compared to 1.53 for light trucks and 1.18 for passenger cars.

Side object detection systems (SODS) are collision warning systems which alert drivers to the presence of traffic alongside their vehicle within defined detection zones. The intent of SODS is to reduce collisions during lane changes and merging maneuvers. This study examined the effect of right SODS on the performance of commercial vehicle drivers as a means of assessing the impact of these systems on safety. In this study, eight professional truck drivers drove a tractor-semitrailer equipped with four different sets of SODS hardware or side view mirror configurations. These subjects had no previous experience with SODS. Subjects were tested with two right SODS (a radar-based system and an ultrasonic-based system), a fender-mounted convex mirror, and, for comparison, standard side view mirrors only. For each case, subjects drove the test vehicle through a set route for one day.

This paper describes the assessment of driver interfaces of a type of electronics-based collision avoidance systems that has been recently developed to assist drivers of vehicles in avoiding certain types of collisions. The electronics-based crash avoidance systems studied were those which detect the presence of objects located on the left and/or right sides of the vehicle, called Side Collision Avoidance Systems, or SCAS. As many SCAS as could be obtained, including several pre-production prototypes, were acquired and tested. The testing focused on measuring sensor performance and assessing the qualities of the driver interfaces. This paper presents only the results of the driver interface assessments. The sensor performance data are presented in the NHTSA report “Development of Performance Specifications for Collision Avoidance Systems for Lane Changing, Merging, and Backing - Task 3 - Test of Existing Hardware Systems” [1].

This paper presents the test track scenario design and analysis used to estimate the performances of heavy vehicles equipped with forward collision warning and automatic emergency braking systems in rear-end crash scenarios. The first part of this design and analysis study was to develop parameters for brake inputs in test track scenarios simulating a driver that has insufficiently applied the brakes to avoid a rear-end collision. In the second part of this study, the deceleration limits imposed by heavy vehicles mechanics and brake systems are used to estimate automatic emergency braking performance benefits with respect to minimum stopping distance requirements set by Federal Motor Vehicle Safety Standards. The results of this study were used to complete the test track procedures and show that all heavy vehicles meeting regulatory stopping distance requirements have the braking capacity to demonstrate rear-end crash avoidance improvements in the developed tests.

This paper focuses on two types of electronics-based object detection systems for heavy truck applications: those sensing the presence of objects to the rear of the vehicle, and those sensing the presence of objects on the right side of the vehicle. The rearward sensing systems are intended to aid drivers when backing their vehicles, typically at very low “crawl” speeds. Six rear object detection systems that were commercially available at the time that this study was initiated were evaluated. The right side looking systems are intended primarily as supplements to side view mirror systems and as an aid for detecting the presence of adjacent vehicles when making lane changes or merging maneuvers. Four side systems, two commercially available systems and two prototypes, were evaluated.

Two computer models of drivers using preview predictor strategies have been successfully implemented in conjunction with a recently developed, all digital vehicle simulation. The driver models determine control inputs to the vehicle simulation by first predicting future vehicle position and velocity and then determining the steering and braking commands necessary to move the vehicle from the predicted to the desired path. Full technical details of the method of implementation for each of the models are given. The results of sample simulations of the driver-vehicle system using each driver model are shown. Problems of each model are discussed.

Two computer models of drivers using describing function strategies have been successfully implemented in conjunction with a recently developed, all digital vehicle simulation. The driver models determine control inputs to the vehicle simulation by means of feedback loops. Two feedback loops, an outer one on lateral position and an inner one on heading angle are used to determine the steering commands needed to move the vehicle to the desired path. One feedback loop on forward velocity is used to determine braking and acceleration commands. Full technical details of the method of implementation for each of the models are given. The results of sample simulations of the driver-vehicle system are shown and the results discussed.

The goal of this research was to find vehicle characteristics which may contribute to steering maneuver induced rollover accidents. This work involved studying vehicle handling dynamics using the Vehicle Dynamics Analysis, Non-Linear (VDANL) computer simulation. The simulation was used to predict vehicle responses while performing 28 different steering induced maneuvers for each of 51 vehicles. Various measures of vehicle response (metrics), such as response times, percent overshoots, etc., were computed for each vehicle from simulation predictions. These vehicle directional response metrics were analyzed in an attempt to identify vehicle characteristics that might be good predictor/explanatory variables for vehicle rollover propensity. The metrics were correlated, using the Statistical Analysis System (SAS) software and logistic regression, with single vehicle accident data from the state of Michigan for the years 1986 through 1988.

Phase IV of the National Highway Traffic Safety Administration's (NHTSA) rollover research program was performed in 2001, starting in the spring and continuing through the fall. The objective of this phase was to obtain the data needed to select a limited set of maneuvers capable of assessing light vehicle rollover resistance. Five Characterization maneuvers and eight Rollover Resistance maneuvers were evaluated [1]. This paper is “Volume 1” of a two-paper account of the research used to develop dynamic maneuver tests for rollover resistance ratings. Test procedures and results from one Characterization maneuver (the Slowly Increasing Steer maneuver) and four Rollover Resistance maneuvers are discussed (the NHTSA J-Turn, Fishhook 1a, Fishhook 1b, and Nissan Fishhook). Details regarding NHTSA's assessment of the Consumers Union Short Course (CUSC), ISO 3888 Part 2, Ford Path Corrected Limit Lane Change (PCL LC), and Open-Loop Pseudo Double Lane Changes are available in “Volume 2” [2].