Search Results

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.

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.

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.

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.