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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.

A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An integral part of this System is an Intervention Strategy that uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. Through this strategy, the driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models. This work develops one means to alter the future vehicle states: modulating the driver's brake commands. This control strategy must be considered in relationship to changes in the throttle commands. Three key elements of this strategy are developed in this work.

A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An Intervention Strategy uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. The driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models which is the focus of this work. This work develops one means to alter the future vehicle states: modulating the driver's throttle commands. First, changes to the longitudinal force are translated to changes in engine torque based on the current operating state (torque and speed) of the engine.

Forward Collision Warning (FCW) and Lane Departure Warning (LDW) systems are two active safety systems that have recently been added to the U.S. New Car Assessment Program (NCAP) evaluation. Vehicles that pass confirmation tests may advertise the presence of FCW and LDW alongside the vehicle's star safety rating derived from crash tests. This paper predicts the number of crashes and injured drivers that could be prevented if all vehicles in the U.S. fleet were equipped with production FCW and/or LDW systems. Models of each system were developed using the test track data collected for 16 FCW and 10 LDW systems by the NCAP confirmation tests. These models were used in existing fleetwide benefits models developed for FCW and LDW. The 16 FCW systems evaluated could have potentially prevented between 9% and 53% of all rear-end collisions and prevented between 19% and 60% of injured (MAIS2+) drivers. Earlier warning times prevented more warnings and injuries.

An analysis of the first 35 back-over crashes reported by NHTSA's Special Crash Investigations unit was undertaken with two objectives: (1) to test a hypothesized classification of backing crashes into types, and (2) to characterize scenario-specific conditions that may drive countermeasure development requirements and/or objective test development requirements. Backing crash cases were sorted by type, and then analyzed in terms of key features. Subsequent modeling of these SCI cases was done using an adaptation of the Driving Reliability and Error Analysis Methodology (DREAM) and Cognitive Reliability and Error Analysis Methodology (CREAM) (similar to previous applications, for instance, by Ljung and Sandin to lane departure crashes [10]), which is felt to provide a useful tool for crash avoidance technology development.

Vehicle-to-vehicle (V2V) communication systems can enable a number of wireless-based vehicle features that can improve traffic safety, driver convenience, and roadway efficiency and facilitate many types of in-vehicle services. These systems have an extended communication range that can provide drivers with information about the position and movements of nearby V2Vequipped vehicles. Using this technology, these vehicles are able to communicate roadway events that are beyond the driver's view and provide advisory information that will aid drivers in avoiding collisions or congestion ahead. Given a typical communication range of 300 meters, drivers can potentially receive information well in advance of their arrival to a particular location. The timing and nature of presenting V2V information to the driver will vary depending on the nature and criticality of the scenario.

Dynamic game theory brings together different features that are keys to many situations in control design: optimization behavior, the presence of multiple agents/players, enduring consequences of decisions and robustness with respect to variability in the environment, etc. In the presented methodology, vehicle stability is represented by a cooperative dynamic/difference game such that its two agents (players), namely, the driver and the direct yaw controller (DYC), are working together to provide more stability to the vehicle system. While the driver provides the steering wheel control, the DYC control algorithm is obtained by the Nash game theory to ensure optimal performance as well as robustness to disturbances. The common two-degree of freedom (DOF) vehicle handling performance model is put into discrete form to develop the game equations of motion.

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.

2011 - 56th L. Ray Buckendale Lecture Driver distraction has become an important topic in society and the research community. A telltale sign of how driver distraction has impacted society is evidenced by the designation of the term "distracted driving" as Webster's New World® College Dictionary 2009 Word of the Year. Since the release of a key study directed at commercial vehicle drivers, there have been two U.S. Department of Transportation summits to address the topic, in addition to legislation banning texting-while-driving in commercial motor vehicles. Given that "driver distraction" is a construct without a consensus definition, many studies on driver distraction have focused on its fundamental and theoretical underpinning, which is a critical first step in understanding the phenomenon.

Vehicle stability is maintained by proper interactions between the driver and vehicle stability control system. While driver describes the desired target path by commanding steering angle and acceleration/deceleration rates, vehicle stability controller tends to stabilize higher dynamics of the vehicle by correcting longitudinal, lateral, and roll accelerations. In this paper, a finite-horizon optimal solution to vehicle stability control is introduced in the presence of driver's dynamical decision making structure. The proposed concept is inspired by Nash strategy for exactly known systems with more than two players, in which driver, commanding steering wheel angle, and vehicle stability controller, applying compensated yaw moment through differential braking strategy, are defined as the dynamic players of the 2-player differential linear quadratic game.

This paper outlines the development of a simulation-based process for assessing the handling performance of a given set of tires on a specific vehicle. Based on force and moment data, a Pacejka tire model was developed for each of the five sets of tires used in this study. To begin with, simple handling metrics including under-steer gradient were calculated using cornering stiffness derived from the Pacejka model. This Pacejka tire model was subsequently combined with a 3DOF non-linear vehicle model to create a simulation model in MATLAB/Simulink®. Other handling metrics were calculated based on simulation results to step and sinusoidal (General Motors Company) steering inputs. Calculated performance metrics include yaw velocity overshoot, yaw velocity response time, lateral acceleration response time and steering sensitivity. In addition to this, the phase lag in lateral acceleration and yaw rate of the vehicle to a sinusoidal steering input were also calculated.

One seminal question that faces a vehicle's driver (either human or computer) is predicting the capability of the vehicle as it encounters upcoming terrain. A Location-Aware Adaptive Vehicle Dynamics (LAAVD) System is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. In contrast to current active safety systems, this system is predictive rather than reactive. This work provides the conceptual groundwork for the proposed system. The LAAVD System employs a predictor-corrector method in which the driver's input commands (throttle, brake, steering) and upcoming driving environment (terrain, traffic, weather) are predicted. An Intervention Strategy uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. The driver's throttle and brake control are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority.

In order to evaluate a human surrogate, the human and surrogate response must be defined. The purpose of this study was to evaluate the response of cadaver subjects to blunt impacts to the frontal bone, nasal bone and maxilla. Force-displacement corridors were developed based on the impact response of each region. Variation in the force-displacement response of the cadaver subjects due to the occurrence of fracture and fracture severity was demonstrated. Additionally, impacts were performed at matched locations using the Facial and Ocular CountermeasUre Safety (FOCUS) headform. The FOCUS headform is capable of measuring forces imposed onto facial structures using internal load cells. Based on the tests performed in this study, the nasal region of the FOCUS headform was found to be the most sensitive to impact location. Due to a wide range in geometrical characteristics, the nasal impact response varied significantly, resulting in wide corridors for human response.

To help drivers monitor the road and to reduce blind spots, Camera/Video Imaging Systems (C/VISs) display live video from cameras mounted on the truck's exterior to drivers using displays inside the truck cabin. This study investigated drivers' performance with C/VISs in a real-world trucking operation. Twelve commercial drivers' performance with and without a C/VIS was continuously recorded while they each drove for four months. Half of the drivers used a commercially available C/VIS that had a side-view camera on each fender. The other drivers used an advanced C/VIS (A-C/VIS) that had side-view cameras, a rear-view camera, and night-vision capabilities. This paper presents the study's final results and expands on the preliminary results that were previously reported. Detailed analyses of drivers' involvement in Safety-Critical Events (SCEs), their lane change performance, and their opinions of the C/VISs are presented.

Approximately 28,000 crashes involving combination unit trucks occur each year when they are making lane changes, merges, or turns. One contributing factor in these crashes is inadequate visibility for truck drivers. Recent advances in video technology have heightened the prospect of improving commercial vehicle safety by improving drivers' vision around the truck. For such video systems to be implemented on heavy trucks, the systems/driver interface should be demonstrated as viable through research. This paper presents the Camera/Video Imaging Systems (C/VISs) developed at Virginia Tech Transportation Institute (VTTI), the methodology used to test them, and some results obtained.

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.

This paper discusses radio usage habits observed during analysis of 700 hours of video sampled from the 100-Car Naturalistic Driving Study database. Analysts used large-scale printouts of each vehicle's radio faceplate and recorded interactions based on video analysis of hand movement and location (without the assistance of audio recordings). The duration and specific manipulations or adjustments were recorded for each interaction. The results summarize the length and type of interactions, most often-used controls, and total percentage of time drivers interacted with the radio.

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).

Assessing driver drowsiness and providing timely alerts is the basis for drowsy driver monitoring systems. Though technologies are available that claim to reliably provide this function, they tend to be single-metric systems that may not be sufficiently robust for real-world operation. To address this issue, a prototype system that integrated two drowsiness measures was developed. The prototype combined machine-vision-based drowsy driver monitoring technology and the analysis of driver/vehicle performance parameters with the goal of more reliably assessing driver drowsiness. The prototype concept, called PERCLOS+, used PERCLOS (a slow eye-closure measure) in combination with lane deviation (to assess driver performance). Based on preliminary on-road tests, the prototype was found to be more robust than a single-metric system.

Driver distraction, defined here as engaging in a secondary task or activity that is not central to the primary task of driving, has been shown to be a contributing factor for many crashes. The secondary tasks and other activities in which drivers choose to engage while driving is also known to be highly varied, including very complex activities(e.g., text messaging on a cellular device) to very simple activities (e.g., selecting a radio preset). Several important distinctions affect the relative risk of engaging in these tasks. Recent data from large-scale instrumented vehicle studies (i.e., “naturalistic” driving studies like the recently released “100 car study” (1)) have begun to provide data where the relative risk, in terms of crash and near crash involvement, can be directly assessed for differing secondary tasks. These data have provided some important insights into the features that create risk.