Search Results

A combined biodynamic and vehicle model is used to assess the vibration and performance of a human operator performing driving and other tasks. The other tasks include reaching, pointing and tracking by the driver and/or passenger. This analysis requires the coordinated use of separate and mature software programs for anthropometrics, vehicle dynamics, biodynamics, and systems analysis. The total package is called AVB-DYN, an acronym for Anthropometrics, Vehicle and Bio-DYNamics. The biodynamic component of AVB-DYN is described, and then compared with an experiment that studied human operator in-vehicle reaching performance using the U.S. Army TACOM Ride Motion Simulator.

Ground vehicle dynamic stability, including spinout and rollover, is highly dependent on maneuvering conditions and the nonlinear force response characteristics of tires. Depending on vehicle configuration, unstable behavior requires high, sustained lateral acceleration, and some maneuver induced excitation of the roll and yaw mode dynamics. Dynamic instability in some vehicles can be induced by a steering reversal maneuver that involves sustained limit performance lateral acceleration. Using a validated vehicle dynamics simulation, analysis is presented to illustrate what constitutes a critical stability sensitive maneuver. Two example test cases are used to show that a critical stability sensitive maneuver must be more severe than a single lane change. Even reaching tire saturation limits during an aggressive single lane change does not give the sustained lateral acceleration required to provoke instability conditions.

This paper describes a human factors simulation study of the decision making behavior of drivers attempting to avoid nonrecurring congestion by diverting to alternate routes with the aid of in-vehicle navigation systems. This study is the first phase of a two part project in which the second phase will apply the driver behavior data to a simulation model analysis of traffic flow. The object of the driver behavior experiment was to compare the effect of various experimental navigation systems on driver route diversion and alternate route selection. The experimental navigation system configurations included three map based systems with varying amounts of situation information and a non map based route guidance system. The overall study results indicated that navigation system characteristics can have a significant effect on driver diversion behavior, with better systems allowing more anticipation of traffic congestion.

This paper describes a laboratory simulation study of driver reaction to in-vehicle navigation systems. The study included a pre-test questionnaire on demographic background and commuting behavior, simulation testing of navigation decision making, and a post-test questionnaire on navigation behavior and reactions to in-vehicle navigation systems and the laboratory simulation. A total of 277 subjects, both male and female, were employed over a wide range of ages. Test subjects were assigned to one of four navigation system groups or a no-system control group for the purpose of comparing system performance. The simulation task required subjects to experience a commuting ‘drive’ on a Southern California freeway route and minimize trip time by diverting off the main route to avoid congestion. Subjects were given orientation and training on the simulation and their navigation system condition, and were motivated by rewards and penalties to minimize trip time.

This paper describes a low cost, PC based driving simulation that includes a complete vehicle dynamics model (VDM), photo realistic visual display, torque feedback for steering feel and realistic sound generation. The VDM runs in real-time on Intel based PCs. The model, referred to as VDANL (Vehicle Dynamics Analysis, Non-Linear) has been developed and validated for a range of vehicles over the last decade and has been previously used for computer simulation analysis. The model's lateral and longitudinal dynamics have 17 degrees of freedom for a single unit vehicle and 33 degrees of freedom for an articulated vehicle. The model also includes a complete drive train including engine, transmission and front and rear drive differentials, and complete, power assisted braking and steering systems. A comprehensive tire model (STIREMOD) generates lateral and longitudinal forces and aligning torque based on normal load, camber angle and horizontal (lateral and longitudinal) slip.

Maneuverable round and ramair parachutes are flown by professional forestry firefighters, search and rescue personnel, and military combat teams when deployment by fixed or rotary aircraft is inappropriate. Parachute flight training requires the development of perceptual skills in canopy control, guidance, and energy management. These parachutists must learn to accurately sense motion visual cues, and predict and manage their trajectory. Parachute guidance and control can only be acquired through repeated practice. Canopy control training has been traditionally limited to a classroom lecture topic. There was no opportunity for the immediate student/instructor dialogue available during the extensive dual flight training used for conventional aircraft, where instruction can occur during the numerous practice landings available via rapid touch-and-go techniques.

This paper presents an analysis of driver/vehicle performance over a range of maneuvering conditions including accident avoidance scenarios involving vehicle limit performance handling. Driver behavior is considered in the same dynamic analysis terms as vehicle response in order to give appropriate closed-loop measures of total system maneuvering capability and handling stability. A driver control structure is developed along with closed-loop system stability constraints on model parameters over a wide range of vehicle maneuvering conditions. Example simulation runs are presented for several accident avoidance scenarios.

The U.S. Army uses the root mean square and power spectral density of elevation to characterize road/terrain (off-road) roughness for durability. This paper describes research aimed toward improving these metrics. The focus is on taking previously developed metrics and applying them to mathematically generated terrains to determine how each metric discerns the relative roughness of the terrains from a vehicle durability perspective. Multiple terrains for each roughness level were evaluated to determine the variability for each terrain rating metric. One method currently under consideration is running a relatively simple, yet vehicle class specific, model over a given terrain and using predicted vehicle response(s) to classify or characterize the terrain.

Lateral/directional dynamics involve vehicle yawing, rolling and lateral translation motions and dynamic stability concerns directional behavior (i.e. spinout) and rollover. Previous research has considered field test and computer simulation methods and results concerning lateral/directional stability. This paper summarizes measurements and simulation analysis of a wide range of vehicles regarding directional and rollover stability. Directional stability is noted to be strongly influenced by lateral load transfer distribution (LTD) between the front and rear axles LTD influences tire side force saturation properties, and should be set up so that side forces at the rear axle do not saturate before the front axle under hard maneuvering conditions in order to avoid limit oversteer and spinout.

A combined biodynamic and vehicle model is used to assess the vibration and performance of a human operator performing driving and other tasks. The other tasks include reaching, pointing and tracking by the driver and/or passenger. This analysis requires the coordinated use of separate and mature software programs for anthropometrics, vehicle dynamics, biodynamics, and systems analysis. The total package is called AVB-DYN, an acronym for Anthropometrics, Vehicle, and Bio-DYNamics. The objectives and architecture are discussed, and then a preliminary version of this package is demonstrated in an example where a HMMWV (High Mobility Multipurpose Wheeled Vehicle) operator is performing a driving task.

Dynamic stability is influenced by vehicle and tire characteristics and operating conditions, including speed and control inputs. Under limit performance operating conditions, maneuvering can force a vehicle into oversteer and high sideslip. The high sideslip results in limit cornering conditions, which might proceed to spinout, or result in tip-up and rollover. Oversteer and spinout result from rear axle tire side force saturation. Tip-up and rollover occur when tire side forces are sufficient to induce lateral acceleration that will overcome the stabilizing moment of vehicle weight. With the use of computer simulation and generic vehicle designs, this paper explores the vehicle and tire characteristics and maneuvering conditions that lead to loss of directional control and potential tip-up and rollover.

This paper describes the results of an experiment concerning driver behavior in car following tasks. The motivation for this experiment was a desire to understand typical driver car following behavior as a guide for setting the automatic control characteristics of an ACC (Adaptive Cruise Control) system. Testing was conducted under both test track and open road driving conditions. The results indicate that car following is carried out under much lower bandwidth conditions than typical steering processes. Dynamic analysis shows driver time delay in response to lead vehicle velocity change on the order of several seconds. Typical longitudinal acceleration distributions show standard deviations of less than 0.05 g (acceleration due to gravity).

This paper describes the driver/vehicle modeling aspects of a computer simulation that can respond to highway engineering descriptions of roadways. The driver model interacts with a complete vehicle dynamics model that has been described previously. The roadway path is described in terms of horizontal and vertical curvature and cross slopes of lanes, shoulders, side slopes and ditches. Terrain queries are made by the vehicle dynamics to locate tires on the roadway cross-section, and to define vehicle path and road curvature at some distance down the road. The driver model controls steering to maintain lateral lane position. Speed is maintained at a speed limit on tangents, and decreased as needed to maintain safe lateral acceleration. Because the bandwidth of longitudinal (speed) control is much lower than lateral/directional (steering) control, the driver model looks further ahead for speed control than for steering.

This paper discusses recent developments and application of driving simulators. Simulation of driving via films has been used for a number of years as a driver education tool. More recently, interactive simulators have been developed for research and training applications. Improvements are accelerating due to a combination of ongoing research needs, and general state of the art advances in hardware and software technology. Modern simulator requirements are reviewed from the point of view of both driver characteristics (vision, audition, proprioception, vestibular motion sensation) and task demands (e.g., steering and speed control, risk perception, decision making, general workload level). A variety of simulator applications are summarized, including comparison with subsequent field tests. These applications include studies involving drunk driving and risk taking, reduced visibility and delineation, and signing.

The U.S. Army uses the root mean square and power spectral density of elevation to characterize road/terrain (off-road) roughness for durability. This paper describes research aimed toward improving these metrics. The focus is on taking previously developed metrics and applying them to mathematically generated terrains to determine how each metric discerns the relative roughness of the terrains from a vehicle durability perspective. Multiple terrains for each roughness level were evaluated to determine the variability for each terrain rating metric. One method currently under consideration is running a relatively simple, yet vehicle class specific, model over a given terrain and using predicted vehicle response(s) to classify or characterize the terrain.

Interactive driving simulation is attractive for a variety of applications, including screening, training and licensing, due to considerations of safety, control and repeatability. However, widespread dissemination of these applications will require modest cost simulator systems. Low cost simulation is possible given the application of PC level technology, which is capable of providing reasonable fidelity in visual, auditory and control feel cuing. This paper describes a PC based simulation with high fidelity vehicle dynamics, which provides an easily programmable visual data base and performance measurement system, and good fidelity auditory and steering torque feel cuing. This simulation has been used in a variety of applications including screening truck drivers for the effects of fatigue, research on real time monitoring for driver drowsiness and measurement of the interference effect of in-vehicle IVHS tasks on driving performance.

Interactive simulation requires providing appropriate sensory cuing and stimulus/response dynamics to the driver. Sensory feedback can include visual, auditory, motion, and proprioceptive cues. Stimulus/response dynamics involve reactions of the feedback cuing to driver control inputs including steering, throttle and brakes. The stimulus/response dynamics include both simulated vehicle dynamics, and the response dynamics of the simulation hardware including computer processing delays. Typically, simulation realism will increase with sensory fidelity and stimulus/response dynamics that are equivalent to real-world conditions (i.e. without excessive time delay or phase lag). This paper discusses requirements for sensory cuing and stimulus/response dynamics in real-time, interactive driving simulation, and describes a modest fixed-base (i.e. no motion) device designed with these considerations in mind.

Motion cueing algorithms can improve the perceived realism of a driving simulator, however, data on the effects on driver performance and simulator sickness remain scarce. Two novel motion cueing algorithms varying in concept and complexity were developed for a limited maneuvering workspace, hexapod/Stuart type motion platform. The RideCue algorithm uses a simple swing motion concept while OverTilt Track algorithm uses optimal pre-positioning to account for maneuver characteristics for coordinating tilt adjustments. An experiment was conducted on the US Army Tank Automotive Research, Development and Engineering Center (TARDEC) Ride Motion Simulator (RMS) platform comparing the two novel motion cueing algorithms to a pre-existing algorithm and a no-motion condition.

Computer simulation and real-time, interactive approaches for analysis, interactive driving simulation, and hardware-in-the-loop testing are finding increasing application in the research and development of advanced automotive concepts, highway design, etc. Vehicle dynamics models serve a variety of purposes in simulation. A model must have sufficient complexity for a given application but should not be overly complicated. In interactive driving simulation, vehicle dynamics models must provide appropriate computation for sensory feedback such as visual, motion, auditory, and proprioceptive cuing. In stability and handling simulations, various modes must be properly represented, including lateral/directional and longitudinal degrees of freedom. Limit performance effects of tire saturation that lead to plow out, spin out, and skidding require adequate tire force response models.

This paper reviews and expands previously published driver steering control models. The driver model is structured to control vehicle heading angle and lane position. Field test data are used to validate model structure. The closed-loop stability of the driver/vehicle system is analyzed using a two degree of freedom vehicle dynamics approximation. This analysis is used to develop constraints among the various driver model parameters and their dependence on vehicle characteristics. Driver/vehicle model approximations are also used to explore the effects of driver behavior on steering performance.