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This paper presents results of a study conducted to compare driving behavior and performance of drivers in two different fixed-base driving simulators (namely, FAAC and STI) while performing a same set of distracting tasks under geometrically similar freeway and traffic conditions. The FAAC simulator had a wider three-screen road view with steering feedback as compared to the STI simulator which had a single screen and narrower road view and had no steering feedback. Twenty four subjects (12 younger and 12 mature) drove each simulator and were asked to perform a set of nine different tasks involving different distracting elements such as, using a cell phone, operating the car radio, retrieving and selecting a map from map pocket in the driver's door, collecting coins to pay toll, etc.

This paper presents results of a study conducted to apply and evaluate the In-Vehicle Information System (IVIS) DEMAnD Model developed recently by the Virginia Polytechnic University's Center for Transportation Research for the Federal Highway Administration. This software-based model allows vehicle design engineers to predict the effects an in-vehicle information system might have on driver performance. The model was exercised under nine different driver attention task levels ranging from simple, such as glancing into a side view mirror, to complex, such as operating an in-vehicle navigation system. The nine driver tasks were evaluated using three different vehicle configurations and two levels of driver-roadway complexity. In addition, real-world information on driver visual performance was also collected during four different tasks for comparison with model predictions of these same functions.

This paper presents results of a study conducted to determine differences in older (over age 55) and younger (under age 35), male and female drivers while entering and exiting vehicles with three different body styles - namely, a large sedan, a minivan and a full-size pick-up truck. Thirty-six drivers (males and females, ages 25 to 89 years) who participated in this study were first measured for their anthropometric, strength and body flexibility measures relevant to the entry/exit tasks. They were asked to first get in each vehicle and adjust their preferred seating position. Then, they were asked to get in the vehicle and their entry time was measured. Their entry maneuver was also video taped and they were asked to rate the level of ease/difficulty (using a 5-point scale) in entering. Similar procedure and measurements were conducted during their exit from each vehicle.

Seat comfort is a highly subjective attribute and depends on a wide range of factors, but the successful prediction of seat comfort from a group of relevant variables can hold the promise of eliminating the need for time-consuming subjective evaluations during the early stages of seat cushion selection and development. This research presents the subjective seat comfort data of a group of 30 participants using a controlled range of seat foam samples, and attempts to correlate this attribute with a) the anthropometric and demographic characteristics of the participants, b) the objective pressure distribution at the body-seat interface and c) properties of the various foam samples that were used for the test.

A method for communication linking the vehicle user and the lighting engineer has been developed to improve the headlight beam pattern development process. A technique called the semantic differential has been used to quantify the user's perception on a large number of attributes of the beam pattern. The basis of the technique utilizes descriptive words used by both drivers and engineers to characterize headlight beam patterns. Beam pattern evaluations conducted in a series of dynamic drive situations formed the initial data base. Subsequent evaluations using this technique have facilitated close and quick interaction between the customer and the engineer during the development of headlight beam patterns.

With recent advances in microprocessors and data storage technologies, vehicle users can now bring or access large amounts of data in vehicles for purposes such as communication (e.g. e-mail, phone books), entertainment (e.g. music and video files), browsing and searching for information (e.g. on-board computers and internet). The challenge for the vehicle designer is how to design data displays and retrieval methods to allow data search and manipulation tasks by managing driver workload at safe acceptable levels. This paper presents a data retrieval menu system developed to assess levels of screens (depth of menu) that may be needed to select required information when a vehicle is equipped with the capability to access audio files, cell phone, PDA, e-mail and “On-star” type functions.

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. Driver head movements during left lane-changing maneuvers were recorded from a lead vehicle equipped with a motion picture camera and a telephoto-zoom lens. Results showed that, in addition to the head turning motions, the drivers made on the average about 2.0 inches of lateral head movements while using one of the four left outside mirror sizes which ranged in width from 2.3 to 10.6 inches. The drivers were also found to make larger lateral head movements when no other vehicles were present in the mirror as compared to when an overtaking vehicle was present. The second study was conducted in no overtaking traffic with one mirror width and used an improved photographic technique.

This paper presents results of revisions to the DETECT model made to include the effects of driver age on visual performance in night driving. This paper will present age related changes made to the subprograms that compute: the visual contrast thresholds, disability glare effects and discomfort glare index. Outputs of runs are presented which illustrate functional relationships of driver age to pedestrian seeing distance and discomfort glare experienced by drivers.

A Headlight Evaluation Model has been developed which provides a broader and more comprehensive method for characterizing the performance of headlamps than is possible in traditional headlight seeing distance field tests. The Headlamp Evaluation Model accepts as input the candlepower patterns of the headlamp system being evaluated and provides a measure 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.

This paper presents quantitative effects of windshield veiling glare on the visibility of targets based on a two part research project. The first part involved measurement and modeling of luminance of veiling glare caused by the reflection of different instrument panel materials under range of conditions defined by combination of windshield angle, instrument panel angle, and sun angle. In the second part, the veiling glare model was incorporated in a visibility prediction model based on visual contrast threshold data. A critical visibility condition of a driver approaching a tunnel with the sunlight falling on his windshield and attempting to detect a target inside the tunnel was studied by conducting sensitivity analyses. The sensitivity analysis showed that a 2 ft diameter 10% reflectance target illuminated by 5000 lux of lighting inside a tunnel visibility distances can be seen from 0 to 3,000 feet depending upon driver's age, vehicle design parameters and sun illumination levels.

This paper presents results of a three-phase research project aimed at understanding how future automotive interior materials should be selected or designed to satisfy the needs of the customers. The first project phase involved development of 22 five-point semantic differential scales to measure visual, visual-tactile, and evaluative characteristics of the materials. Some examples of the adjective pairs used to create the semantic differential scales to measure the perceptual characteristics of the material are: a) Visual: Light vs. Dark, Flat vs. Shiny, etc., b) Visual-Tactile: Smooth vs. Rough, Slippery vs. Sticky, Compressive vs. Non-Compressive, Textured vs. Non-Textured, etc., c) Evaluative (overall perception): Dislike vs. Like, Fake vs. Genuine, Cheap vs. Expensive, etc. In the second phase, 12 younger and 12 older drivers were asked to evaluate a number of different automotive interior materials by using the 22 semantic differential scales.