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In 2006, there were approximately 23,500 rear-end crashes involving heavy trucks (i.e., gross vehicle weight greater than 4,536 kg). The Enhanced Rear Signaling (ERS) for Heavy Trucks project was developed by the Federal Motor Carrier Safety Administration (FMCSA) to investigate methods to reduce or mitigate those crashes where a heavy truck has been struck from behind by another vehicle. Visual warnings have been shown to be effective, assuming the following driver is looking directly at the warning display or has his/her eyes drawn to it. A visual warning can be placed where it is needed and it can be designed so that its meaning is nearly unambiguous. FMCSA contracted with the Virginia Tech Transportation Institute (VTTI) to investigate potential benefit of additional rear warning-light configurations as rear-end crash countermeasures for heavy trucks.

Safety and minimal transit time are vital during transportation of essential commodities and passengers, especially in winter conditions. Icy roads are the worst driving conditions with the least available friction, leaving valuable cargo and precious human lives at stake. The study investigates the available friction at the tire-ice interface due to changes in key operational parameters. Experimental analysis of tractive performance of tires on ice was carried out indoor, using the terramechanics rig located at the Advanced Vehicle Dynamics Laboratory (AVDL) at Virginia Tech. The friction-slip ratio curves obtained from indoor testing were inputted into TruckSIM, defining tire behavior for various ice scenarios and then simulating performance of trucks on ice. The shortcomings of simulations in considering the effects of all the operational parameters result in differences between findings of indoor testing and truck performance simulations.

Studying the kinetic and kinematics of the rim-tire combination is very important in full vehicle simulations, as well as for the tire design process. Tire maneuvers are either quasi-static, such as steady-state rolling, or dynamic, such as traction and braking. The rolling of the tire over obstacles and potholes and, more generally, over uneven roads are other examples of tire dynamic maneuvers. In the latter case, tire dynamic models are used for durability assessment of the vehicle chassis, and should be studied using high fidelity simulation models. In this study, a three-dimensional finite element model (FEM) has been developed using the commercial software package ABAQUS. The purpose of this study is to investigate the tire dynamic behavior in multiple case studies in which the transient characteristics are highly involved.

Vehicle analytical models are often favorable due to describing the physical phenomena associated with vehicle operation following from the principles of physics, with explainable mathematical trends and with extendable modeling to other types of vehicle. However, no experimentally validated analytical model has been developed as yet of diesel engine fuel consumption rate. The present paper demonstrates and validates for trucks and light commercial vehicles an analytical model of supercharged diesel engine fuel consumption rate. The study points out with 99.6% coefficient of determination that the average percentage of deviation of the steady speed-based simulated results from the corresponding field data is 3.7% for all Freeway cycles. The paper also shows with 98% coefficient of determination that the average percentage of deviation of the acceleration-based simulated results from the corresponding field data under negative acceleration is 0.12 %.

A graphical user interface (GUI) toolbox called Vehicle System Simulator (VSS) is developed in MATLAB to ease the use of this vehicle model and hopefully encourage its widespread application in the future. This toolbox uses the inherent MATLAB discrete-time solvers and is mainly based on Level-2 s-function design. This paper describes its built-in vehicle dynamics model based on multibody dynamics approach and nonlinear tire models, and traction/braking control systems including Cruise Control and Differential Braking systems. The built-in dynamics model is validated against CarSim 8 and the simulation results prove its accuracy. This paper illustrates the application of this new MATLAB toolbox called Vehicle System Simulator and discusses its development process, limitations, and future improvements.

Human expert drivers have the unique ability to combine correlated sensory inputs with repetitive learning to build complex perceptive models of the vehicle dynamics as well as certain key aspects of the tire-ground interface. This ability offers significant advantages for navigating a vehicle through the spatial and temporal uncertainties in a given environment. Conventional traction control algorithms utilize measurements of wheel slip to help insure that the wheels do not enter into an excessive slip condition such as burnout. This approach sacrifices peak performance to ensure that the slip limits are generic enough suck that burnout is avoided on a variety of surfaces: dry pavement, wet pavement, snow, gravel, etc. In this paper, a novel approach to traction control is developed using an anthropomimetic control synthesis strategy.

Mechanical and thermal properties of the rubber compounds of a tire play an important role in the overall performance of the tire when it is in contact with the terrain. Although there are many studies conducted on the properties of the rubber compounds of the tire to improve some of the tire characteristics such as the wear of the tread, there is a limited number of studies that focused on the performance of the tire when it is in contact with ice. This study is a part of a more comprehensive project looking into tire-ice performance and modeling. A significant part of this study is the experimental investigation of the effect of rubber compounds on tire performance in contact with ice. For this, four tires have been selected for testing. Three of them are completely identical in all tire parameters (such as tire dimensions), except for the rubber compounds. Several tests were conducted for the chosen tires in three modes: free rolling, braking, and traction.

Restrictions on track testing, combined with advances in technology, have contributed to an increased dependence on sensors and data acquisition for diagnosing problems and improving performance in motorsports vehicles. This dependence has created a new set of challenges for race engineers to collect quality data from a vehicle at the track. Successful 7- or 8-post shaker rig testing is highly dependent on the quality of the data acquired at the track. An improperly configured data acquisition system can actually be worse than a faulty sensor. This paper highlights a few of the most common problems in motorsports data acquisition: aliasing and sample rate selection. The effects of these problems are described for typical suspension sensors such as accelerometers, shock potentiometers, load cells, and laser ride height sensors. An experimental case study is presented to explain the implications of these problems.

This paper studies the effect of different longitudinal load conditions, roundabout cross-sectional geometry, and different semi-truck pneumatic suspension systems on roll stability in roundabouts, which have become more and more popular in urban settings. Roundabouts are commonly designed in their size and form to accommodate articulated heavy vehicles (AHVs) by evaluating such affects as off-tracking. However, the effect of the roadway geometry in roundabouts on the roll dynamics of semi-tractors and trailers are equally important, along with their entry and exit configuration. , Because the effect of the roundabout on the dynamics of trucks is further removed from the immediate issues considered by roadway planner, at times they are not given as much consideration as other roadway design factors.

Tire-pavement interaction noise (TPIN) is a dominant source for passenger cars and trucks above 40 km/h and 70 km/h, respectively. TPIN is mainly generated from the interaction between the tire and the pavement. In this paper, twenty-two passenger car radial (PCR) tires of the same size (16 in. radius) but with different tread patterns were tested on a non-porous asphalt pavement. For each tire, the noise data were collected using an on-board sound intensity (OBSI) system at five speeds in the range from 45 to 65 mph (from 72 to 105 km/h). The OBSI system used an optical sensor to record a once-per-revolution signal to monitor the vehicle speed. This signal was also used to perform order tracking analysis to break down the total tire noise into two components: tread pattern-related noise and non-tread pattern-related noise.

Heavy-vehicle event data recorders (HVEDRs) provide a source of temporal vehicle data just prior to, during, and for a short period after, an event. In the 1990s, heavy-vehicle (HV) engine manufacturers expanded the capabilities of engine control units (ECU) and engine control modules (ECM) to include the ability to record and store small amounts of parametric vehicle data. This advanced capability has had a significant impact on vehicle safety by helping law enforcement, engineers, and researchers reconstruct events of a vehicle crash and understand the details surrounding that vehicle crash. Today, EDR technologies have been incorporated into a wide range of heavy vehicle (HV) safety systems (e.g., crash mitigation systems, air bag control systems, and behavioral monitoring systems). However, the adoption of EDR technologies has not been uniform across all classes of HVs or their associated vehicle systems.

Structural Health Monitoring (SHM), especially in the field of rotary machinery diagnosis, plays a crucial role in determining the defect category as well as its intensity in a machine element. This paper proposes a new framework for real-time classification of structural defects in a roller bearing test rig using time domain-based classification algorithms. Along with the bearing defects, the effect of eccentric shaft loading has also been analyzed. The entire system comprises of three modules: sensor module – using accelerometers for data collection, data processing module – using time-domain based signal processing algorithms for feature extraction, and classification module – comprising of deep learning algorithms for classifying between different structural defects occurring within the inner and outer race of the bearing.

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.

One of the principal goals of modern vehicle control systems is to ensure passenger safety during dangerous maneuvers. Their effectiveness relies on providing appropriate parameter inputs. Tire-road contact forces are among the most important because they provide helpful information that could be used to mitigate vehicle instabilities. Unfortunately, measuring these forces requires expensive instrumentation and is not suitable for commercial vehicles. Thus, accurately estimating them is a crucial task. In this work, two estimation approaches are compared, an observer method and a neural network learning technique. Both predict the lateral and longitudinal tire-road contact forces. The observer approach takes into account system nonlinearities and estimates the stochastic states by using an extended Kalman filter technique to perform data fusion based on the popular bicycle model.

Animal-vehicle collision (AVC) is a significant safety issue on American roads. Each year approximately 1.5 million AVCs occur in the U.S., the majority of them involving deer. The increasing use of cameras and radar on vehicles provides opportunities for prevention or mitigation of AVCs, particularly those involving deer or other large animals. Developers of such AVC avoidance/mitigation systems require information on the behavior of encountered animals, setting characteristics, and driver response in order to design effective countermeasures. As part of a larger study, naturalistic driving data were collected in high AVC incidence areas using 48 participant-owned vehicles equipped with data acquisition systems (DAS). Continuous driving data including forward video, location information, and vehicle kinematics were recorded. The respective 11TB dataset contains 35k trips covering 360K driving miles.

Indoor laboratory tire testing on flat belt machines and tire testing on the actual road yield different results. Testing on the machine offers the advantage of repeatability of test conditions, control of the environmental condition, and performance evaluation at extreme conditions. However, certain aspects of the road cannot be reproduced in the laboratory. It is thus essential to understand the connection between the machine and the road, as tires spend all their life on the road. This research, investigates the reasons for differences in tire performance on the test machine and the road. The first part of the paper presents a review on the differences between tire testing in the lab and on the road, and existing methods to account for differences in test surfaces.

A vehicle's response is predominately defined by the tire characteristics as they constitute the only contact between the vehicle and the road; and the surface friction condition is the primary attribute that determines these characteristics. The friction coefficient is not directly measurable through any sensor attachments in production-line vehicles. Therefore, current chassis control systems make use of various estimation methods to approximate a value. However a significant challenge is that these schemes require a certain level of perturbation (i.e. excitation by means of braking or traction) from the initial conditions to converge to the expected values; which might not be the case all the time during a regular drive.

This paper presents the results of a study on the effect of truck configurations on the roll stability of commercial trucks in roundabouts that are commonly used in urban settings with increasing frequency. The special geometric layout of roundabouts can increase the risk of rollover in high-CG vehicles, even at low speeds. Relatively few in-depth studies have been conducted on rollover stability of commercial trucks in roundabouts. This study uses a commercially available software, TruckSim®, to perform simulations on four truck configurations, including a single-unit truck, a WB-67 semi-truck, the combination of a tractor with double 28-ft trailers, and the combination of a tractor with double 40-ft trailers. A single-lane and multilane roundabout are modeled, both with a truck apron. Three travel movements through the roundabouts are considered, including right turn, through-movement, and left turn.

Outdoor objective evaluations form an important part of both tire and vehicle design process since they validate the design parameters through actual tests and can provide insight into the functional performances associated with the vehicle. Even with the industry focused towards developing simulation models, their need cannot be completely eliminated as they form the basis for approving the performance predictions of any newly developed model. An objective test was conducted to measure the ABS performance as part of validation of a tire simulation design tool. A sample vehicle and a set of tires were used to perform the tests- on a road with known profile. These specific vehicle and tire sets were selected due to the availability of the vehicle parameters, tire parameters and the ABS control logic. A test matrix was generated based on the validation requirements.