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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.

Fuel consumption reduction on medium-duty tactical truck has and continues to be a significant initiative for the U.S. Army. The Crankshaft-Integrated-Starter-Generator (C-ISG) is one of the parallel hybrid propulsions to improve the fuel economy. The C-ISG configuration is attractive because one electric machine can be used to propel the vehicle, to start the engine, and to be function as a generator. The C-ISG has been implemented in one M1083A1 5-ton tactical cargo truck. This paper presents the experimental assessments of the C-ISG hybrid truck characteristics. The experimental assessments include all electric range for on- and off-road mission cycles and fuel consumption for the high voltage battery charging. Stationary tests related to the charging profile of the battery pack and the silent watch time duration is also conducted.

Lithium-ion polymer battery has been widely used for vehicle onboard electric energy storage ranging from 12V SLI (Starting, Lighting, and Ignition), 48V mild hybrid electric, to 300V battery electric vehicle. Formulation on cell parameters acquired from minimum numbers of experiments, the modeling and simulation could be an effective approach in predicting battery performance, thermal effectiveness, and degradation. This paper describes the modeling, simulation, and validation of Lithium-Nickel-Manganese-Cobalt-Oxide (LiNiMnCoO2) based cell with 3.6V nominal voltage and 20Ah capacity. Constant current 20A, 40A, 60A, and 80A discharge tests are conducted in the computer-controlled cycler and temperature chamber. Discharging voltage curves and cell surface temperature distributions are recorded in each discharging test. A three-dimensional cell model is constructed in the COMSOL multi-physics platform based on the cell parameters.

With the mass movement toward electrification and renewable technologies, the scope of innovation of electrification has gone beyond the automotive industry into areas such as electric motorcycle applications. This paper provides a discussion of the methodology and complexities of converting an internal combustion motorcycle to an electric motorcycle. In developing this methodology, performance goals including, speed limits, range, weight, charge times, as well as riding styles will be examined and discussed. Based on the goals of this paper, parts capable of reaching the performance targets are selected accordingly. Documentation of the build process will be presented along with the constraints, pitfalls, and difficulties associated with the process of the project. The step-by-step process that is developed can be used as a guideline for future build and should be used as necessary.

The ‘boundary of space’ model representing all possible positions which may be occupied by a mechanism during its normal range of motion (for all positions and orientations) is called the work envelope. In the robotic domain, it is also known as the robot operating envelope or workspace. Several researchers have investigated workspace boundaries for different degrees of freedom (DOF), joint types and kinematic structures utilizing many approaches. The work envelope provides essential boundary information, which is critical for safety and layout concerns, but the work envelope information does not by itself determine the reach feasibility of a desired configuration. The effect of orientation is not captured as well as the coupling related to operational parameters. Included in this are spatial occupancy concerns due to linking multiple kinematic chains, which is an issue with multi-tasking machine tools, and manufacturing cells.

When performing trajectory planning for robotic applications, there are many aspects to consider, such as the reach conditions, joint and end-effector velocities, accelerations and jerk conditions, etc. The reach conditions are dependent on the end-effector orientations and the robot kinematic structure. The reach condition feasibility is the first consideration to be addressed prior to optimizing a solution. The ‘functional’ work space or work window represents a region of feasible reach conditions, and is a sub-set of the work envelope. It is not intuitive to define. Consequently, 2D solution approaches are proposed. The 3D travel paths are decomposed to a 2D representation via radial projections. Forward kinematic representations are employed to define a 2D boundary curve for each desired end effector orientation.

The Dimensional Model of Driver Demand is extended to include Auditory-Vocal (i.e., pure “voice” tasks), and Mixed-Mode tasks (i.e., a combination of Auditory-Vocal mode with visual-only, or with Visual-Manual modes). The extended model was validated with data from 24 participants using the 2014 Toyota Corolla infotainment system in a video-based surrogate driving venue. Twenty-two driver performance metrics were collected, including total eyes-off-road time (TEORT), mean single glance duration (MSGD), and proportion of long single glances (LGP). Other key metrics included response time (RT) and miss rate to a Tactile Detection Response Task (TDRT). The 22 metrics were simplified using Principal Component Analysis to two dimensions. The major dimension, explaining 60% of total variance, we interpret as the attentional effects of cognitive demand. The minor dimension, explaining 20% of total variance, we interpret as physical demand.

As vehicles are getting electrified and more intelligent, the energy consumption of the auxiliary system increases rapidly. The auxiliary battery acts as the backbone of the system to support the proper operation of the vehicle. It is important to ensure the auxiliary battery has enough energy to meet the basic loads regardless the vehicle is in park or running. However, the existing methods only focus on auxiliary energy management when the vehicle is in a dynamic event. To fulfill the gap, we propose an intelligent strategy that detects the low state of charge (SOC) condition, temporarily turns down the auxiliary loads based on their priorities and charges the auxiliary battery at the maximum efficiency of the auxiliary power unit. In addition, the proposed strategy allows the vehicle to get the park duration update and make intelligent decisions on charging the auxiliary battery.

Accident statistics have shown that older and obese occupants are less adaptable to existing vehicle occupant restraint systems than ordinary middle-aged male occupants, and tend to have higher injury risk in vehicle crashes. However, the current research on injury mechanism of aging and obese occupants in vehicle frontal impacts is scarce. This paper focuses on the optimization design method of occupant restraint system parameters for specific body type characteristics. Three parameters, namely the force limit value of the force limiter in the seat belt, pretensioner preload of the seat belt and the proportionality coefficient of mass flow rate of the inflator were used for optimization. The objective was to minimize the injury risk probability subjected to constraints of occupant injury indicator values for various body regions as specified in US-NCAP frontal impact tests requirements.

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.

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.

Up to now, there is no standard methodology that addresses how driver distraction is affected by perceptual demand and working memory demand - aside from visual allocation. In 2009, the Peripheral Detection Task (PDT) became a NHTSA recommended measure for driver distraction [1]. Then the PDT task was renamed as the Detection Response Task (DRT) because the International Standards Organization (ISO) has identified this task as a potential method for assessing selective attention in detection of visual, auditory, tactile and haptic events while driving. The DRT is also under consideration for adoption as an ISO standard surrogate test for driver performance for new telematics designs. The Wayne State University (WSU) driver imaging group [2, 3] improved the PDT and created the Enhanced Peripheral Detection Task I (EPDT-I) [4]. The EPDT-I is composed of a simple visual event detection task and a video of a real-world driving scene.

This study undertakes an investigation of the effect of battery charge balance in hybrid electric vehicles (HEVs) on EPA fuel economy label values. EPA's updated method was fully implemented in 2011 and uses equations which weight the contributions of fuel consumption results from multiple dynamometer tests to synthesize city and highway estimates that reflect average U.S. driving patterns. For the US06 and UDDS cycles, the test results used in the computation come from individual phases within the overall certification driving cycles. This methodology causes additional complexities for hybrid vehicles, because although they are required to be charge-balanced over the course of a full drive cycle, they may have net charge or discharge within the individual phases. As a result, the fuel consumption value used in the label value calculation can be skewed.

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 Performance Margin (PM) is defined in this work as the ratio of the required tractive effort to the available tractive effort for the front and rear respectively. This simple definition stems from and incorporates many traditional handling metrics and is robust in its scope of applicability. The PM is implemented in an Intervention Strategy demonstrating its use to avoid situations in which the vehicle exceeds its handling capabilities. Results from a design case study are presented to show the potential efficacy of developing a PM-based control system.

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.

Described in this paper is a component test methodology to evaluate the door trim armrest performance in an Insurance Institute for Highway Safety (IIHS) side impact test and to predict the SID-IIs abdomen injury metrics (rib deflection, deflection rate and V*C). The test methodology consisted of a sub-assembly of two SID-IIs abdomen ribs with spine box, mounted on a linear bearing and allowed to translate in the direction of impact. The spine box with the assembly of two abdominal ribs was rigidly attached to the sliding test fixture, and is stationary at the start of the test. The door trim armrest was mounted on the impactor, which was prescribed the door velocity profile obtained from full-vehicle test. The location and orientation of the armrest relative to the dummy abdomen ribs was maintained the same as in the full-vehicle test.