Search Results

When commercial vehicles have less than ideal lateral dynamics traveling at high speeds, those dynamics can sometimes be a significant factor in serious and fatal accidents that occur. The primary goal of this study was to create a validated vehicle dynamics model to aid in handling evaluations and a validated model that can play an important role in accurately predicting the movement of the vehicle in limit conditions. The model is used to simulate the effect on roll gradient by altering spring stiffnesses and adding a rear stabilizer for a class 6 or class 7 commercial vehicle (CV). Outputs from 4-post Kinematics & Compliance (K&C) tests of a prototype vehicle were used to model the suspension system. The tire model was developed in collaboration with Calspan [1] using physical tire testing. The vehicle masses, inertias and stiffnesses were modelled using IPG TruckMaker for Simulink (TM4SL) [2].

In the last few years, the number of Advanced Driver Assistance Systems (ADAS) on road vehicles has been increased with the aim of dramatically reducing road accidents. Therefore, the OEMs need to integrate and test these systems, to comply with the safety regulations. To lower the development cost, instead of experimental testing, many virtual simulation scenarios need to be tested for ADAS validation. The classic multibody vehicle approach, normally used to design and optimize vehicle dynamics performance, is not always suitable to cope with these new tasks; therefore, real-time lumped-parameter vehicle models implementation becomes more and more necessary. This paper aims at providing a methodology to convert experimentally validated light commercial vehicles (LCV) multibody models (MBM) into real-time lumped-parameter models (RTM).

This paper provides a simulation analysis of a novel interconnected roll stability control (RSC) system for improving the roll stability of semitrucks with double trailers. Different from conventional RSC systems where each trailer’s RSC module operates independently, the studied interconnected RSC system allows the two trailers’ RSC systems to communicate with each other. As such, if one trailer’s RSC activates, the other one is also activated to assist in further scrubbing speed or intervening sooner. Simulations are performed using a multi-body vehicle dynamics model that is developed in TruckSim® and coupled with the RSC model established in Simulink®. The dynamic model is validated using track test data. The simulation results for a ramp steer maneuver (RSM) and sine-with-dwell (SWD) maneuver indicate that the proposed RSC system reduces lateral acceleration and rollover index for both trailers, decreasing the likelihood of wheel tip-up and vehicle rollover.

The tractor usage is growing in the world due to derivative of rural economy and farming process. It needed wide range of implements based on the applications of the customer. The tractor plays a major role in Agricultural and Construction applications. In a tractor, hydraulic system is act as a heart of the vehicle which controls the draft and position of the implement. Hydraulic system consists of Powertrain assembly, 3-point linkage and DC sensing assembly. The design of hydraulic powertrain assembly is challenging because the loads acting on the system varies based on the type of implement, type of crop, stage of farming and soil conditions etc., Hydraulic powertrain assembly is designed based on standards like IS 12207-2019 which regulates the test methods for the system based on the lift capacity of the tractor. In this paper, virtual simulation has been established to optimize the design and perform the test correlation.

In an off-road vehicle, Vehicle Structure plays a major role in passenger safety, Aesthetics, Durability, through a validated construction of canopy structure. This structure is to maintain the shape of the vehicle and to support various loads acting on the vehicle. In present market a safe, Durable, Robust, Waterproof, Noise less, Light weight and cost-effective off-road vehicle will always be a delight for any customer. However, the current conventional way of Soft top vehicle structure use metal brackets and formed sheet parts to create a structure to retain the canopy shape in place. These conventional structures are often heavier and would have many demerits such as heavy weight, Corrosion, Risk of canopy tear due to metallic structure edges and inappropriate draining, water management. Considering this we replaced the heavy metal brackets in to blow molded plastic parts.

In recent years, the removal of lead (Pb), which is an environmentally hazardous material often used in bearings for automotive engines, has been continuously promoted. Bismuth (Bi) is attracting attention as a substitute for lead, and it is currently being used mainly for passenger cars and trucks as a lead replacement. However, lead has not been replaced for motorcycles where the bearings are exposed to high temperatures at high rotation speeds, and trucks and generators where high loading capacity, long lifetime and good corrosion resistance are required. It has been difficult to achieve both high load and corrosion resistant for a bearing overlay material. The purpose of this development is to improve the corrosion resistance and fatigue resistance of bismuth overlay by developing a bismuth- antimony alloy overlay in which antimony (Sb) is added to the bismuth matrix.

Tire rolling resistance and temperature are the main parameters for the design and driving of the heavy-duty tires due to their effects on fuel economy and safety. In this paper, the influence of many factors on the tire rollingresistance and temperature is studied, including speed, inflation pressure and normal load; the relationship between rolling resistance properties and temperature of heavy tires is studied based on several experiments to explore the physical mechanism and characteristics of tire rolling resistance for heavy-duty vehicles. The effects of the driving time and temperature of the tire on the rolling resistance are performed on tire’s experimental platform, in which the empirical models involved in the driving time and temperature of the tire for the rolling resistance are established using the least square method for fitting the experimental data.

This paper presents a comprehensive investigation aimed to assess the effect of tire inflation pressure on the fuel consumption of a typical 4×4 off-road vehicle over unprepared soft terrains. For this purpose, a fourteen-degrees-of-freedom (14-DOF) full parametrized vehicle model is employed and numerically simulated in MATLAB/Simulink™ environment. This model is intended to consider all the rotational dynamics and compliances of all-wheel-drivetrain aggregates using SimDriveline™ toolbox including engine, transmission, differentials, shafts and wheels. Numerous simulations are carried out to examine both the tractive efficiency and fuel consumption considering all power losses in transmission, terrains and tire slippage over different operating conditions such as terrain’s mechanical properties, tire weight distribution and drivetrain configurations (open or locked center differential).

Autonomous farming has gained a vast interest due to the need for increased farming efficiency and productivity as well as reducing operating cost. Technological advancement enabled the development of Autonomous Driving (AD) features in unstructured environments such as farms. This paper discusses an approach of utilizing satellite images to estimate the drivable areas of agriculture fields with the aid of LiDAR sensor data to provide the necessary information for the vehicle to navigate autonomously. The images are used to detect the field boundaries while the LiDAR sensor detects the obstacles that the vehicle encounters during the autonomous driving as well as its type. These detections are fused with the information from the satellite images to help the path planning and control algorithms in making safe maneuvers. The image and point cloud processing algorithms were developed in MATLAB®/C++ software and implemented within the Robot Operating System (ROS) middleware.

For car-following models, the car-following characteristics differ depending on the vehicle type, such as passenger cars, motorcycles, and trucks. Therefore, constructing a model for each category is essential. To that end, various modeling methods have been proposed; however, herein, we particularly focused on the long short-term memory (LSTM), which is the best method for forecasting long-term time-series data.[1, 2] The objective of this study was to construct a car-following model for each vehicle category using the LSTM and to evaluate the model accuracy for each vehicle category. In this study, US-101 and I-80 data provided by the next-generation simulation (NGSIM), which is based on natural traffic flow data, were used. In the NGSIM, only car-following situations were selected as car-following data, and these were classified into the vehicle type: motorcycles, passenger cars, and trucks.

Technology is ever advancing in the world around us, and it is no different when it comes to data acquisition systems used in accident reconstruction. In 2016, the SAE publication “Data Acquisition Using Smart Phone Applications,” Neale et al. evaluated the accuracy of basic fitness applications in tracking position within the smart phone itself [1]. In 2018, a follow up publication “Mid-Range Data Acquisition Units Using GPS and Accelerometers” tested the Harry’s Lap TimerTM application for use in smart phones and compared the data to the Race Logic VBOX [2]. In this paper, another data acquisition system, the MoTeC C185, was tested. The MoTeC C185 data logger contains an internal 3-axis accelerometer and was also equipped with an external Syvecs 50Hz GPS Module with 6-axis accelerometer. A test vehicle was instrumented with the MoTeC C185, Race Logic VBOX, and Harry’s Lap TimerTM.

This article presents an autonomous steering control scheme for articulated heavy vehicles (AHVs). Despite economic and environmental benefits in freight transportation, lateral stability is always a concern for AHVs in high-speed highway operations due to their multi-unit vehicle structures, and high centers of gravity (CGs). In addition, North American harsh winter weather makes the lateral stability even more challenging. AHVs often experience amplified lateral motions of trailing vehicle units in high-speed evasive maneuvers. AHVs represent a 7.5 times higher risk than passenger cars in highway operation. Human driver errors cause about 94% of traffic collisions. However, little attention has been paid to autonomous steering control of AHVs.

Autonomous truck with modular chassis has the characteristics of high driving flexibility and strong load capacity. It can be equipped with different numbers of modular chassis according to the task requirements. The application of autonomous truck can solve the problems of traffic accidents and shortage of drivers effectively, which is the development trend of trucks in the future. For the collision-free trajectory planning problem of dual-modular chassis autonomous truck, this paper designs a hierarchical local trajectory planner that combines the artificial potential field method with polynomial curve fitting method. This planner plans the center of mass trajectory firstly, and then generates the modular chassis trajectories according to the position relationship between the center of mass and the chassis.

Unmanned Ground Vehicle (UGV) has a wide range of applications in the military, agriculture, firefighting and other fields. Path planning, as a key aspect of autonomous driving technology, plays an essential role for UGV to accomplish the established driving tasks. At present, there are many global path planning algorithms in grid maps on unstructured roads, while general grid maps do not consider the specific elevation or ground type difference of each grid, and unstructured roads are generally considered as flat and open roads. On the contrary, the unmanned off-road is always a bumpy road with undulating terrain, and meanwhile, the landform is complex and the types of features are diverse. In order to ensure the safety and improve the efficiency of autonomous driving of UGV in off-road environment, this paper proposes a global off-road path planning method for UGV based on the raw image of remote sensing map. Firstly, the raw image is gridded.

Image segmentation has historically been a technique for analyzing terrain for military autonomous vehicles. One of the weaknesses of image segmentation from camera data is that it lacks depth information, and it can be affected by environment lighting. Light detection and ranging (LiDAR) is an emerging technology in image segmentation that is able to estimate distances to the objects it detects. One advantage of LiDAR is the ability to gather accurate distances regardless of day, night, shadows, or glare. This study examines LiDAR and camera image segmentation fusion to improve an advanced driver-assistance systems (ADAS) algorithm for off-road autonomous military vehicles. The volume of points generated by LiDAR provides the vehicle with distance and spatial data surrounding the vehicle.

Autonomous vehicles (AV) are sophisticated systems comprising various sensors, powerful processors, and complex data processing algorithms that navigate autonomously to their respective goals. Out of several functions performed by an AV, one of the most important is developing situational intelligence to predict collision-free future trajectories. As an AV operates in environments consisting of various entities, such as other AVs, human-driven vehicles, and static obstacles, developing situational intelligence will require a collaborative approach. The recent developments in artificial intelligence (AI) and deep learning (DL) relating to AVs have shown that DL-based models can take advantage of information sharing and collaboration to develop such intelligence.

The new generation vehicles these days are managed by networked controllers. A large portion of the networks is planned with more security which has recently roused researchers to exhibit various attacks against the system. This paper talks about the liabilities of the Controller Area Network (CAN) inside In-vehicle communication protocol and a few potentials that could take due advantage of it. Moreover, this paper presents a few security measures proposed in the present examination status to defeat the attacks. In any case, the fundamental objective of this paper is to feature a comprehensive methodology known as Intrusion Detection System (IDS), which has been a significant device in getting network data in systems over many years. To the best of our insight, there is no recorded writing on a through outline of IDS execution explicitly in the CAN transport network system.

Classic vehicle production had limitations in bringing the driving commands to the actuators for vehicle motion (engine, steering and braking). Steering columns, hydraulic tubes or steel cables needed to be placed between the driver and actuator. Change began with the introduction of e-gas systems. Mechanical cables were replaced by thin, electric signal wires. The technical solutions and legal standardizations for addressing the steering and braking systems, were not defined at this time. Today, OEMs are starting E/E-Architecture transformations for manifold reasons and now have the chance to remove the long hydraulic tubes for braking and the solid metal columns used for steering. X-by-wire is the way forward and allows for higher Autonomous Driving (AD) levels for automated driving vehicles. This offers new opportunities to design the vehicle in-cabin space. This paper will start with the introduction of x-by-wire technologies.

The purpose of this study was to construct driver models using long short-term memory (LSTM) in car-following situations, where other vehicles change lanes and cut in front of the ego vehicle (EGV). The development of autonomous vehicle systems (AVSs) using personalized driver models based on the individual driving characteristics of drivers is expected to reduce their discomfort with vehicle control systems. The driving characteristics of human drivers must be considered in such AVSs. In this study, we experimentally measured data from the EGV and other vehicles using a driving simulator consisting of a six-axis motion device and turntable. The experimental scenario simulated a traffic congestion scenario on a straight section of a highway, where a cut-in vehicle (CIV) changed lanes from an adjacent lane and entered in between the EGV and preceding vehicle (PRV).

Platoon is a system that connects vehicles through vehicle-to-vehicle (V2V) communication technology to maintain a short distance between vehicles while driving on the road. To improve fuel efficiency, many automotive original equipment manufacturers (OEMs) are interested in developing and demonstrating real-world platoon system. However, it is hard for heavy duty trucks to develop this system due to the difficulty of maintaining the targeted intervehicle distance not only for fuel efficiency but also for safety in case of emergency braking. Because of this critical safety issue in the emergency situation, the platoon system for heavy duty trucks can be hardly demonstrated or tested in real vehicle environment. The relatively complex system and the slow response characteristic of commercial vehicles makes this even more difficult.