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SAE J3078 provides test methods and criteria for the evaluation of the operator enclosure environment in earth-moving machinery as defined in ISO 6165. SAE J3078/1 gives the terms and definitions which are used in other parts of SAE J3078. It is applicable to Off-Road Self-Propelled Work Machines as defined in SAE J1116 and tractors and machinery for agriculture and forestry as defined in ANSI/ASAE S390.

Heavy Vehicle Event Data Recorders (HVEDRs) have the ability to capture important data surrounding an event such as a crash or near crash. Efforts by many researchers to analyze the capabilities and performance of these complex systems can be problematic, in part, due to the challenges of obtaining a heavy truck, the necessary space to safely test systems, the inherent unpredictability in testing, and the costs associated with this research. In this paper, a method for simulating vehicle speed sensor (VSS) inputs to HVEDRs to trigger events is introduced and validated. Full-scale instrumented testing is conducted to capture raw VSS signals during steady state and braking conditions. The recorded steady state VSS signals are injected into the HVEDR along with synthesized signals to evaluate the response of the HVEDR. Brake testing VSS signals are similarly captured and injected into the HVEDR to trigger an event record.

The current focus in the ongoing development of autonomous driving systems (ADS) for heavy duty vehicles is that of vehicle operational safety. To this end, developers and researchers alike are working towards a complete understanding of the operating environments and conditions that autonomous vehicles are subject to during their mission. This understanding is critical to the testing and validation phases of the development of autonomous vehicles and allows for the identification of both the nominal and edge case scenarios encountered by these systems. Previous work by the authors saw the development of a comprehensive scenario generation framework to identify an operating domain specification (ODS), or external and internal conditions an autonomous driving system can expect to encounter on its mission to form critical scenario groups for autonomous vehicle testing and validating using statistical patterns, clustering, and correlation.

Highway safety remains a significant concern, especially in mixed traffic scenarios involving heavy-duty vehicles (HDV) and smaller passenger cars. The vulnerability of HDVs following closely behind smaller cars is evident in incidents involving the lead vehicle, potentially leading to catastrophic rear-end collisions. This paper explores how automatic speed enforcement systems, using speed cameras, can mitigate risks for HDVs in such critical situations. While historical crash data consistently demonstrates the reduction of accidents near speed cameras, this paper goes beyond the conventional notion of crash occurrence reduction. Instead, it investigates the profound impact of driver behavior changes within desired travel speed distribution, especially around speed cameras, and their contribution to the safety of trailing vehicles, with a specific focus on heavy-duty trucks in accident-prone scenarios.

Automatic emergency braking and forward collision warning (FCW) reduce the incidence of police-reported rear-end crashes by 27% to 50%, but these systems may not be effective for preventing rear-end crashes with nonpassenger vehicles. IIHS and Transport Canada evaluated FCW performance with 12 nonpassenger and 7 passenger vehicle or surrogate vehicle targets in five 2021-2022 model year vehicles. The presence and timing of an FCW was measured as a test vehicle traveling 50, 60, or 70 km/h approached a stationary target ahead in the lane center. Equivalence testing was used to evaluate whether the proportion of trials with an FCW (within ± 0.20) and the average time-to-collision of the warning (within ± 0.23 sec) for each target was meaningfully different from a global vehicle car target (GVT).

Lane changing is an essential action in commercial vehicles to prevent collisions. However, steering system malfunctions significantly escalate the risk of head-on collisions. With the advancement of intelligent chassis control technologies, some autonomous commercial vehicles are now equipped with a four-wheel independent braking system. This article develops a lane-changing control strategy during steering failures using torque vectoring through brake allocation. The boundaries of lane-changing capabilities under different speeds via brake allocation are also investigated, offering valuable insights for driving safety during emergency evasions when the steering system fails. Firstly, a dual-track vehicle dynamics model is established, considering the non-linearity of the tires. A quintic polynomial approach is employed for lane-changing trajectory planning. Secondly, a hierarchical controller is designed.

Considering the current trend towards the electrification of commercial vehicles, the development of Beam eAxle solutions has become necessary. The utilization of an electric drive unit in heavy-duty solid axle-based commercial vehicles presents unique and demanding challenges. These include the necessity for elevated peak and continuous torque while meeting packaging constraints, structural integrity requirements, and extended service life. One such solution was developed by BorgWarner to address these challenges. This paper offers a comprehensive overview of the design and development process undertaken for this Dual Motor Beam eAxle system. This includes the initial comparison of various eAxle solutions, the specifications of components selected for this design, and the initial results from dyno and vehicle development.

Bicycle computers record and store global position data that can be useful for forensic investigations. The goal of this study was to estimate the absolute error of the latitude and longitude positions recorded by a common bicycle computer over a wide range of riding conditions. We installed three Garmin Edge 530 computers on the handlebars of a bicycle and acquired 9 hours of static data and 96 hours (2214 km) of dynamic data using three different navigation modes (GPS, GPS+GLONASS, and GPS+Galileo satellite systems) and two geographic locations (Vancouver, BC, Canada and Orange County, CA, USA). We used the principle of error propagation to calculate the absolute error of this device from the relative errors between the three pairs of computers. During the static tests, we found 16 m to 108 m of drift during the first 4 min and 1.4 m to 5.0 m of drift during a subsequent 8 min period. During the dynamic tests, we found a 95th percentile absolute error for this device of ±8.04 m.

For the design optimization of the electric bus body frame orienting frontal crash, considering the uncertainties that may affect the crashworthiness performance, a robust optimization scheme considering tolerance design is proposed, which maps the acceptable variations in objectives and feasibility into the parameter space, allowing for the analysis of robustness. Two contribution analysis methods, namely the entropy weight and TOPSIS method, along with the grey correlation calculations method, are adopted to screen all the design variables. Fifteen shape design variables with a relatively high impact are chosen for design optimization.

This paper investigates the tire-road interaction for tires equipped with two different solid rubber material definitions within a Finite Element Analysis virtual environment, ESI PAMCRASH. A Mixed Service Drive truck tire sized 315/80R22.5 is designed with two different solid rubber material definitions: a legacy hyperelastic solid Mooney-Rivlin material definition and an Ogden hyperelastic solid material definition. The popular Mooney-Rivlin is a material definition for solid rubber simulation that is not built with element elimination and is not easily applicable to thermal applications. The Ogden hyperelastic material definition for rubber simulations allows for element destruction. Therefore, it is of interest and more suited for designing a tire model with wear and thermal capabilities.

The accuracy of collision severity data recorded by event data recorders (EDRs) has been previously measured primarily using barrier impact data from compliance tests and experimental low-speed impacts. There has been less study of the accuracy of EDR-based collision severity data in real-world, vehicle-to-vehicle collisions. Here we used 189 real-world front-into-rear collisions from the Crash Investigating Sampling System (CISS) database where the EDR from both vehicles recorded a severity to examine the accuracy of the EDR-reported speed changes. We calculated relative error between the EDR-reported speed change of each vehicle and a speed change predicted for that same vehicle using the EDR-reported speed change of the other vehicle and conservation of momentum. We also examined the effect of vehicle-type, mass ratio, and pre-impact braking on the relative error in the speed changes.

Building upon prior research, this paper compares computer simulations to a previously conducted rollover crash test of a tractor-semitrailer. The effects of torsional stiffness were elucidated during the correlation of simulations to the rollover test. A commercially available vehicle dynamics and reconstruction software was used for the simulation. Unique aspects of the rollover crash test were modeled in the simulation. A tractor-semitrailer quarter-turn rollover crash test conducted by IMMI was reconstructed using impact and vehicle dynamics models within the simulation software HVE (Human, Vehicle & Environment). The SIMON (SImulation MOdel Non-linear) module and the DyMESH (Dynamic MEchanical SHell) module within HVE were used. During the IMMI test, onboard instrumentation recorded acceleration and roll rate data in six degrees of freedom to characterize both tractor and semitrailer dynamics before and during the rollover event.

Dust testing of vehicles on unpaved roads is crucial in the development process for automotive manufacturers. These tests aim to ensure the functionality of locking systems in dusty conditions, minimize dust concentration inside the vehicle, and enhance customer comfort by preventing dust accumulation on the car body. Additionally, deposition on safety-critical parts, such as windshields and sensors, can pose threats to driver vision and autonomous driving capabilities. Currently, dust tests are primarily conducted experimentally at proving grounds. In order to gain early insights and reduce the need for costly physical tests, numerical simulations are becoming a promising alternative. Although simulations of vehicle contamination by dry dust have been studied in the past, they have often lacked detailed models for tire dust resuspension. In addition, few publications address the specifics of dust deposition on vehicles, especially in areas such as door gaps and locks.

The design and analysis of the roll cage for the ATV car are the subjects of this report. The roll cage is one of the key elements of an ATV car. It is the primary component of an ATV, on which the engine, steering, and gearbox are mounted. The vehicle's sprung mass is beneath the roll cage. The initiation of cracks and the deformation of the vehicle are caused by forces acting on it from various directions. Stresses are consequently produced. FEA of the roll cage is used in this paper in an effort to identify these areas. We have performed torsional analysis as well as front, rear, side impact, and rollover crash analyses. These analyses were all completed using ANSYS Workbench 2020 R1. The design process complies with all guidelines outlined in the SAE rule book of E-Baja.

SAE J115 specifies the relevant ISO standards for application to safety labels for use on off-road work machines as defined in SAE J1116.

The commercial vehicle sector (especially trucks) has major role in economic growth of a nation. With improving infrastructure, increasing number of commercial vehicles and growing amount of Vulnerable Road Users (VRUs) on roads, accidents are also increasing. As per RASSI (Road Accident Sampling System India) FY2016-21 database, commercial vehicles are involved in 43% of total accidents on Indian roads. One of the major causes of these accidents is Driver Drowsiness and Inattention (DDI) (approx. 10% contribution in total accidents). This paper describes novel driver-in-loop performance assessment methodology for comprehensive verification of Driver Monitoring System (DMS) for commercial vehicle application. Novelty lies in specification of test subjects, driving styles and variety of road traffic scenarios for verification of DMS system. Test setup is made modular to cater to different platform environments (Heavy, Intermediate, Light) with minor modifications.

In the modern and fast growing automotive sector, reliability & durability are two terms of utmost importance along with weight & cost optimization. Therefore it is important to explore new technology which has less weight, low manufacturing cost and better strength. The new technology developed always seek for a quick, cost effective and reliable methodology for its design validation so that any modification can be made by identifying the failures. This paper presents the rig level test methodology to validate and to correlate the CAE derived strain levels, life cycle & failure mode of newly developed light weight stabilizer link for EV Bus suspension