Vivek D. Bhise

Modeling Vision with Headlights in a Systems Context

The Headlamp Evaluation Model accepts as input the candlepower patterns of the headlamp system being evaluated and provides a measures of driver visual performance based on a large number of simulated seeing distance tests and glare discomfort checks on a standardized test route. The output of the Model, termed the Figure of Merit, is the percentage of the distance traveled by the simulated driver on the standardized test route in which the seeing distance to pedestrians and pavement lines, and the discomfort glare levels experienced by opposing drivers, simultaneously meet certain acceptance criteria. /SASI/

PREDICTING DRIVER SEEING DISTANCE IN NATURAL RAINFALL

Four field studies were conducted in natural rainfall to develop a model for predicting distances at which drivers are able to see other vehicles in the roadway at various time periods following stoppage of a windshield-wiper stroke. The seeing distance prediction was developed as a function of rain intensity, rain accumulation time, and ambient daylight illumination. Two situations were studied; in the first, drivers seated in a stationary vehicle detected moving vehicles, and in the second, moving drivers detected a stationary vehicle. Useful seeing distance models were developed from the field studies. Seeing distances predicted from the models developed from these earlier studies were compared with seeing distances obtained in a subsequent validation field test. Results indicated that average error in the prediction of seeing distances ranges from 9% to 23%.

DRIVER HEAD MOVEMENTS IN LEFT OUTSIDE MIRROR VIEWING

Two field studies were conducted on public roads to measure driver head movements while using the left outside passenger car mirror. The first study measured the effects of mirror width in the presence or absence of overtaking traffic. The second study was conducted in no overtaking traffic with one mirror width and used an improved photographic technique.

Effects of Shared Secondary Controls and Operational Modes on Performance and Perceived Workload During a Simulated Driving Task

During a simulated driving task, subjects were prompted to actuate specific shared (mode-based) secondary controls, which required subjects to ensure that the proper mode was active before actuating the control. The independent variables were number of controls, number of operational modes, and number of functions assigned to a control. The dependent variables included performance time, speed and lane deviations, error measures, and subjective ratings. Subjects perceived higher workloads and took longer to complete the secondary task as the number of controls and number of functions increased. The number of operational modes had no effect on secondary control performance while subjective ratings indicated little or no significant differences between multiple and single mode systems. Comparing systems with identical number of functions, a system that reduces the number of controls by assigning a set of functions (in which each function belongs to a different mode) to each control may be preferable to a system that dedicates each function to a single control.

Automotive Field of View Analysis Using Polar Plots

This paper describes how polar plots are constructed and used to evaluate fields of view from vehicles. A polar plot presents a drivers three dimensional view of the vehicle structure, such as window openings or mirrors, and the subjects outside of the vehicle, such as other vehicles in adjacent lanes, in a two dimensional (or polar) field. The paper includes examples of polar plots and illustrates how they can be used by an automotive designer to evaluate many specific problems. Example problems illustrated include (1) angular locations of pillars; (2) monocular and binocular obscurations caused by pillars; (3) hood visibility; (4) visibility of adjacent vehicles; and (5) fields of view available from planar and convex mirrors. For the covering abstract of the conference see IRRD 875189.

A Driver Glare-Discomfort Model to Evaluate Automotive Stop Lamp Brightness

Laboratory and field studies were conducted to explore the applicability of previously reported laboratory-based discomfort glare threshold data to the prediction of the discomfort level drivers may experience due to glare from the stop lamps of a lead vehicle. The results show that the BCD (Borderline between Comfort and Discomfort) threshold brightness data developed by Putnam and Faucett (1951)* can be used to predict various discomfort levels experienced by the driver under field conditions. A prototype glare-discomfort model was developed which predicts driver discomfort as a function of distance between the two vehicles, lamp intensity, size, and the drivers adaptation to ambient luminance levels. The model incorporates a threshold multiplier to account for differences between the BCD thresholds and field-observed glare-discomfort ratings due to glare-exposure duration and multiple-glare sources.

Identification of Steady Burning Red Lamps as Tail or Stop Signal in Night Driving

A three phase investigation was conducted to assess the probabilities of identifying steady burning red signals as tail or stop lamps as a function of their intensity and size and the drivers adaptation brightness.