Search Results

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.

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 %.

With advances in virtual prototyping, accurate digital modeling of driving posture is regarded as a fundamental step in the design of ergonomic driver-seat-cabin systems. Extensive work on driving postures has been carried out focusing on the measurement and prediction of driving postures and the determination of comfortable joint angle ranges. However, studies on postural sensitivity are scarce. The current study investigated whether a driver-selected posture actually represents the most preferred one, by comparing the former with ratings of postures selected at 20 predefined places around the original hip joint center (HJC). An experiment was undertaken in a lab setting, using two distinctive driving package geometries: one for a sedan and the other for an SUV. The 20 postural ratings were compared with that of the initial user-selected position.

3D digital human modeling (DHM) tools for vehicle packaging facilitate ergonomic design and evaluation based on anthropometry, comfort, and force analysis. It is now possible to quickly predict postures and positions for drivers with selected anthropometry based on ergonomics principles. Despite their powerful visual representation technology for human movements and postures, these tools are still questioned with regard to the validity of the output they provide, especially when predictions are made for different populations. Driving postures and positions of two populations (i.e. North Americans and Koreans) were measured in actual and mock-up SUVs to investigate postural differences and evaluate the results provided by a DHM tool. No difference in driving postures was found between different stature groups within the same population. Between the two populations, however, preferred angles differed for three joints (i.e., ankle, thigh, and hip).

Pre-Crash Systems (PCS) integrate the features of active and passive safety systems to reduce both crash and injury severity. Upon detection of an impending collision, PCS can provide an early warning to the driver and activate automatic braking to reduce the crash severity for the subject vehicle. PCS can also activate the seatbelt pretensioners prior to impact. This paper identifies the opportunities for injury prevention in crash types for which PCS can be potentially activated. These PCS applicable crash types include rear-end crashes, single vehicle crashes into objects (trees, poles, structures, parked vehicles), and head-on crashes. PCS can benefit the occupants of both the striking and struck vehicle. In this paper, the opportunity for injury reduction in the struck vehicle is also tabulated. The study is based upon the analysis of approximately 20,000 frontal crash cases extracted from NASS / CDS 1997-2008.

Rear-end crashes involving heavy trucks occur with sufficient frequency that they are a cause of concern within regulatory agencies. In 2006, there were approximately 23,500 rear-end crashes involving heavy trucks which resulted in 135 fatalities. As part of the Federal Motor Carrier Safety Administration's (FMCSA) goal of reducing the overall number of truck crashes, the Enhanced Rear Signaling (ERS) for Heavy Trucks project was developed to investigate methods to reduce or mitigate those crashes where a heavy truck has been struck from behind by another vehicle. Researchers also utilized what had been learned in the rear-end crash avoidance work with light vehicles that was conducted by the National Highway Traffic Safety Administration (NHTSA) with Virginia Tech Transportation Institute (VTTI) serving as the prime research organization. ERS crash countermeasures investigated included passive conspicuity markings, visual signals, and auditory signals.

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.

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.

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.

Vehicle headlamps and roadway lighting are the major sources of illumination at night. These sources affect contrast - defined as the luminance difference of an object from its background - which drives visibility at night. However, the combined effect of vehicle headlamps and intersection lighting on object contrast has not been reported previously. In this study, the interactive effects of vehicle headlamps and overhead lighting on object contrast were explored based on earlier work that examined drivers’ visibility under three intersection lighting designs (illuminated approach, illuminated box, and illuminated approach + box). The goals of this study were to: 1) quantify object luminance and contrast as a function of a vehicle’s headlamps and its distance to an intersection using the three lighting designs; and, 2) to assess whether contrast influences visual performance and perceived visibility in a highly dynamic intersection environment.

This study presents a method for determining the time to collision (TTC) at which a driver of the striking vehicle in a real-world, lead vehicle stopped (LVS) rear-end collision applied the brakes. The method employs real-world cases that were extracted from the National Automotive Sampling System / Crashworthiness Data System (NASS / CDS) years 2000 to 2009. Selected cases had an Event Data Recorder (EDR) recovered from the striking vehicle that contained pre-crash vehicle speed and brake application. Of 59 cases with complete EDR records, 12 cases (20%) of drivers appeared not to apply the brakes at all prior to the collision. The method was demonstrated using 47 rear-end cases in which there was driver braking. The average braking deceleration for those cases with sufficient vehicle speed information was found to be 0.52 g's. The average TTC that braking was initiated at was found to vary in the sample population from 1.1 to 1.4 seconds.

Four crash modes are overrepresented in traffic fatalities: run-off-road crashes, non-tracking run-off-road crashes, head-on crashes, and pedestrian crashes. Two advanced driver assist systems developed to help prevent tracking run-off-road crashes and head-on crashes are lane departure warning (LDW) and lane keeping assist (LKA). LDW acts to warn the driver when they are encroaching the lane boundary, whereas LKA performs automatic steering to prevent the vehicle from departing the lane. The objective of this research was to use real-world crash data to estimate current LDW and LKA system effectiveness in reducing run-off-road crashes and cross-centerline head-on crashes. All passenger vehicles that experienced a lane departure from 2017 to 2019 in the Crash Investigation Sampling System (CISS) were analyzed.

Driver Assistance and Autonomous Driving features are becoming nearly ubiquitous in new vehicles. The intent of the Driver Assistant features is to assist the driver in making safer decisions. The intent of Autonomous Driving features is to execute vehicle maneuvers, without human intervention, in a safe manner. The overall goal of Driver Assistance and Autonomous Driving features is to reduce accidents, injuries, and deaths with a comforting driving experience. However, different drivers can react differently to advanced automated driving technology. It is therefore important to consider and improve the adaptability of these advances based on driver behavior. In this paper, a human-centric approach is adopted to provide an enriching driving experience. We perform data analysis of the naturalistic behavior of drivers when performing lane change maneuvers by extracting features from extensive Second Strategic Highway Research Program (SHRP2) data of over 5,400,000 data files.