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Pedestrian Automatic Emergency Braking (P-AEB) is a technology designed to avoid or reduce the severity of vehicle to pedestrian collisions. This technology is currently assessed and evaluated via EuroNCAP and similar procedures in which a pedestrian test target is crossing the road, walking alongside the road, or stationary in the forward vehicle travel path. While these assessment methods serve the purpose of providing cross-comparison of technology performance in a standardized set of scenarios, there are many scenarios which could occur which are not considered or studied. By identifying and performing non-EuroNCAP, non-standardized scenarios using similar methodology, the robustness of P-AEB systems can be analyzed. These scenarios help identify areas of further development and consideration for future testing programs. Three scenarios were considered as a part of this work: straight line approach, curved path approach, and parking lot testing.

An Electronic Stability Control algorithm has been developed for All-Terrain Vehicles. The algorithm is implemented on SEA’s Robotic Test Driver which has been customized to drive ATVs unmanned. The ESC algorithm is incorporated in the real-time controller. When activated, ESC monitors vehicle states and when they exceed pre-determined thresholds, ESC intervenes by dropping throttle and applying the vehicle’s brakes. The intention of this algorithm is to prevent yaw instability and ultimately limit the vehicle’s roll angle. ESC is implemented on two vehicles, which exhibit varying degrees of understeer. Test data is provided to illustrate the determination in setting threshold limits. The efficacy of the ESC is demonstrated by showing the system being enabled and disabled.

The use of platforms to carry vulnerable road user (VRU) targets has become increasingly necessary with the rise of automated driver assistance systems (ADAS) on vehicles. These ADAS features must be tested in a wide variety of collision-imminent scenarios which necessitates the use of strikable targets carried by an overrun-able platform. To enable the testing of ADAS sensors such as lidar, radar, and vision systems, S-E-A, a longtime supplier of vehicle testing equipment, has created the STRIDE robotic platform (Small Test Robot for Individuals in Dangerous Environments). This platform contains many of the key ingredients of other platforms on the market, such as a hot-swappable battery, E-stop, and mounting points for targets. However, the STRIDE platform additionally provides features which can enable non-routine testing such as: turning in place, driving with an app on a mobile phone, user-scripting, and steep grade climbing capability.

A machine has been developed to measure the center-of-gravity (CG) location of a seat. This machine uses a system of pivots, a yaw bearing and two sensors to get the X, Y and Z CG of the seat. Test object mass is measured separately on a scale. A stable pendulum arrangement is used to get the CG location. Governing equations for the machine are shown in the paper and a typical test procedure is discussed. An error analysis is discussed and shows the requisite accuracy of platform angle, geometric dimensions, seat weight and applied weight in order to achieve the desired 3 mm accuracy target. A full system statistical analysis demonstrates that all X and Y CG locations, when compared with theoretical values, are off by less than 1 mm and well within the 3 mm accuracy target. For Z CG, the errors were shown to be 3.3 mm or lower with 95 percent confidence.

A machine has been developed to measure the complete inertia matrix; mass, center of gravity (CG) location, and all moments and products of inertia. Among other things these quantities are useful in studying engine vibrations, calculation of the torque roll axis, and in the placement of engine mounts. While the machine was developed primarily for engines it can be used for other objects of similar size and weight, and even smaller objects such as tires and wheels/rims. A key feature of the device is that the object, once placed on the test table, is never reoriented during the test cycle. This reduces the testing time to an hour or less, with the setup time being a few minutes to a few hours depending on the complexity of the shape of the object. Other inertia test methods can require up to five reorientations, separate CG measurement, and up to several days for a complete test.

This research was to model a 6×4 tractor-trailer rig using TruckSim and simulate severe braking maneuvers with hardware in the loop and software in the loop simulations. For the hardware in the loop simulation (HIL), the tractor model was integrated with a 4s4m anti-lock braking system (ABS) and straight line braking tests were conducted. In developing the model, over 100 vehicle parameters were acquired from a real production tractor and entered into TruckSim. For the HIL simulation, the hardware consisted of a 4s4m ABS braking system with six brake chambers, four modulators, a treadle and an electronic control unit (ECU). A dSPACE simulator was used as the “interface” between the TruckSim computer model and the hardware.

A Software-in-the-Loop (SIL) simulation is presented here wherein control algorithms for the Anti-lock Braking System (ABS) and Roll Stability Control (RSC) system were developed in Simulink. Vehicle dynamics models of a 6×4 cab-over tractor and two trailer combinations were developed in TruckSim and were used for control system design. Model validation was performed by doing various dynamic maneuvers like J-Turn, double lane change, decreasing radius curve, high dynamic steer input and constant radius test with increasing speed and comparing the vehicle responses obtained from TruckSim against field test data. A commercial ESC ECU contains two modules: Roll Stability Control (RSC) and Yaw Stability Control (YSC). In this research, only the RSC has been modeled. The ABS system was developed based on the results obtained from a HIL setup that was developed as a part of this research.

This paper presents a feedback linearization control technique as applied to a Roll Simulator. The purpose of the Roll Simulator is to reproduce in-field rollovers of ROVs and study occupant kinematics in a laboratory setting. For a system with known parameters, non-linear dynamics and trajectories, the feedback linearization algorithm cancels out the non-linearities such that the closed-loop dynamics behave in a linear fashion. The control inputs are computed values that are needed to attain certain desired motions. The computed values are a form of inverse dynamics or feed-forward calculation. With increasing system eigenvalue, the controller exhibits greater response time. This, however, puts a greater demand on the translational actuator. The controller also demonstrates that it is able to compensate for and reject a disturbance in force level.

The tractor trailer models discussed in this paper were for a real-time hardware-in-the-loop (HIL) simulation to test heavy truck electronic stability control (ESC) systems [1]. The accuracy of the simulation results relies on the fidelity and accuracy of the vehicle parameters used. However in this case where hardware components are part of the simulation, their accuracy also affects the proper working of the simulation and ESC unit. Hence both the software and hardware components have to be validated. The validation process discussed in this paper is divided into two sections. The first section deals with the validation of the TruckSim vehicle model, where experimental data is compared with simulation results from TruckSim. Once the vehicle models are validated, they are incorporated in the HIL simulation and the second section discusses the validation of the whole HIL system with ESC.

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.

This paper documents the vehicle response of a tractor-semitrailer following a sudden air loss (Blowout) in a steer axle tire while traveling at highway speeds. The study seeks to compare full-scale test data to predicted response from detailed heavy truck computer vehicle dynamics simulation models. Full-scale testing of a tractor-semitrailer experiencing a sudden failure of a steer axle tire was conducted. Vehicle handling parameters were recorded by on-board computers leading up to and immediately following the sudden air loss. Inertial parameters (roll, yaw, pitch, and accelerations) were measured and recorded for the tractor and semitrailer, along with lateral and longitudinal speeds. Steering wheel angle was also recorded. These data are presented and also compared to the results of computer simulation models. The first simulation model, SImulation MOdel Non-linear (SIMON), is a vehicle dynamic simulation model within the Human Vehicle Environment (HVE) software environment.

This paper presents the results of an in-depth study of the measurement of occupant kinematic response on the S-E-A Roll Simulator. This roll simulator was built to provide an accurate and repeatable test procedure for the evaluation of occupant protection and restraint systems during roll events within a variety of occupant compartments. In the present work this roll simulator was utilized for minimum-energy, or threshold type, rollover events of recreational off-highway vehicles (ROVs). Input profiles for these tests were obtained through a separate study involving autonomous full vehicle tests [1]. During simulated roll events anthropomorphic test device (ATD) responses were measured using on-board high speed video, an optical three-dimensional motion capture system (OCMS) and an array of string potentiometers.

A two-degree-of-freedom Roll Simulator has been developed to study the occupant kinematics of Recreational Off-Highway Vehicles (ROVs). To validate the roll simulator, test data was collected on a population of ROVs on the market today. J-turn maneuvers were performed to find the minimum energy limits required to tip up the vehicles. Two sets of tests were performed: for the first set, 10 vehicles were tested, where the motion was limited by safety outriggers to 10-15 degrees of roll; and for the second set, three of these vehicles were re-tested with outriggers removed and the vehicle motion allowed to reach 90 degrees of roll. These quarter-turn rollover tests were performed autonomously using an Automatic Steering Controller (ASC) and a Brake and Throttle Robot (BTR). Lateral and longitudinal accelerations as well as roll rate and roll angle were recorded for all tests.

Vehicle dynamics models employed in heavy truck simulation often treat the semitrailer as a torsionally rigid member, assuming zero deflection along its longitudinal axis as a moment is applied to its frame. Experimental testing, however, reveals that semitrailers do twist, sometimes enough to precipitate rollover when a rigid trailer may have remained upright. Improving the model by incorporating realistic trailer roll stiffness values can improve assessment of heavy truck dynamics, as well as an increased understanding of the effectiveness of stability control systems in limit handling maneuvers. Torsional stiffness measurements were conducted by the National Highway Traffic Safety Administration (NHTSA) for eight semitrailers of different types, including different length box vans, traditional and spread axle flat beds, and a tanker.

This research focuses on the development and performance of analytical models to simulate a tractor-semitrailer in straight-ahead braking. The simulations were modified and tuned to simulate full-treadle braking with all brakes functioning correctly, as well as the behavior of the tractor-semitrailer rig under full braking with selected brakes disabled. The models were constructed in TruckSim and based on a tractor-semitrailer used in dry braking performance testing. The full-scale vehicle braking research was designed to define limits for engineering estimates on stopping distance when Class 8 air-braked vehicles experience partial degradation of the foundation brake system. In the full scale testing, stops were conducted from 30 mph and 60 mph, with the combination loaded to 80,000 lbs (gross combined weight or GCW), half payload, and with the tractor-semitrailer unladen (lightly loaded vehicle weight, or LLVW).

In 2007, a software model of a Roll Stability Control (RSC) system was developed based on test data for a Volvo tractor at NHTSA's Vehicle Research and Test Center (VRTC). This model was designed to simulate the RSC performance of a commercially available Electronic Stability Control (ESC) system. The RSC model was developed in Simulink and integrated with the available braking model (TruckSim) for the truck. The Simulink models were run in parallel with the vehicle dynamics model of a truck in TruckSim. The complete vehicle model including the RSC system model is used to simulate the behavior of the actual truck and determine the capability of the RSC system in preventing rollovers under different conditions. Several simulations were performed to study the behavior of the model developed and to compare its performance with that of an actual test vehicle equipped with RSC.

Validation was performed on an existing heavy truck vehicle dynamics computer model with roll stability control (RSC). The first stage in this validation was to compare the response of the simulated tractor to that of the experimental tractor. By looking at the steady-state gains of the tractor, adjustments were made to the model to more closely match the experimental results. These adjustments included suspension and steering compliances, as well as auxiliary roll moment modifications. Once the validation of the truck tractor was completed for the current configuration, the existing 53-foot box trailer model was added to the vehicle model. The next stage in experimental validation for the current tractor-trailer model was to incorporate suspension compliances and modify the auxiliary roll stiffness to more closely model the experimental response of the vehicle. The final validation stage was to implement some minor modifications to the existing RSC model.

This paper describes a method to evaluate vehicle stability and controllability when the vehicle operates in the nonlinear range of lateral dynamics. The method is applied to open-loop steering maneuvers as well as closed-loop path-following maneuvers. Although path-following maneuvers are more representative of real world driving intent, they are usually considered inappropriate for objective assessment because of repeatability and accuracy issues. The automated test driver (ATD) can perform path-following maneuvers accurately and with good repeatability. This paper discusses the usefulness of application of the automated test drivers and path-following maneuvers. The dynamic mode of instability is not directly obtained from measurable outputs such as yawrate and lateral acceleration as in open-loop maneuvers. A few metrics are defined to quantify deviation from desired or ideal behavior in terms of observed “unexpected” lateral force and moment.

Heavy trucks are involved in many accidents every year and Electronic Stability Control (ESC) is viewed as a means to help mitigate this problem. ESC systems are designed to reduce the incidence of single vehicle loss of control, which might lead to rollover or jackknife. As the working details and control strategies of commercially available ESC systems are proprietary, a generic model of an ESC system that mimics the basic logical functionality of commercial systems was developed. This paper deals with the study of the working of a commercial ESC system equipped on an actual tractor trailer vehicle. The particular ESC system found on the test vehicle contained both roll stability control (RSC) and yaw stability control (YSC) features. This work focused on the development of a reliable RSC software model, and the integration of it into a full vehicle simulation (TruckSim) of a heavy truck.

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.