Vivek Bhise

Ergonomics in the automotive design process

ERGONOMICS CONCEPTS, ISSUES AND METHODS IN VEHICLE DESIGN Introduction to Automotive Ergonomics Engineering Anthropometry and Biomechanics Occupant Packaging Driver Information Acquisition and Processing Controls, Displays and Interior Layout. Field of Views From Automotive Vehicles Introduction to Field of View Automotive Lighting Entry and Exit From Automotive Vehicles Automotive Exterior Interfaces: Service and Loading/Unloading Tasks Automotive Craftmanship Role of Ergonomics Engineers in the Automotive Design Process ADVANCED TOPICS, MEASUREMENTS, MODELING AND RESEARCH Modeling Driver Vision Driver Performance Measurement Driver Workload Measurement Vehicle Evaluation Methods Special Driver and User Populations Future Research and New Technology Issues Appendices

A Comprehensive HMI Evaluation Process for Automotive Cockpit Design

With ever increasing possibilities of new technological features and tremendous cost pressures, automobile manufacturers have a challenging task in providing their customers with the latest features at affordable costs in shorter design cycles. To ensure that automotive cockpit systems are well-integrated, cost-effective and ergonomically correct, a comprehensive design process has been developed and pilot tested. This paper describes this system. The process consists of a series of steps and interworkings of three cross-functional teams. The steps are: 1) review manufacturers program assumptions and brand strategy; 2) identify product content and features; 3) develop optimum seating package; 4) determine available space for controls and displays; 5) develop design concepts and best in class engineering product system input; 6) develop alternative control and display layouts with ergonomics scores; 7) develop working models of driver interfaces for simulator evaluations; 8) conduct evaluation tests in the driving simulator; 9) make changes to the design as necessary based on the simulator results; 10) develop cost models from selected prototypes; 11) develop supporting system architecture; 12) conduct additional validation tests as needed; 13) conduct validation tests for brand sensor perceptions for materials, feel, harmony/craftsmanship issues using representative subjects; 14) conduct evaluations of visual characteristics; and 15) conduct a comprehensive ergonomics evaluation. Descriptions, inputs and outputs of the steps are described along with interworkings of the mechanical, electrical and human machine interface integration teams that support the process. The process is currently being applied in supporting pre-program engineering work on several vehicle programs and has already provided some unique solutions for improved cockpit designs.

A PC Based Model for Prediction of Visibility and Legibility for a Human Factors Engineer's Tool Box

Target detection and legibility prediction problems are generally considered complex as they require a good understanding of knowledge in photometry, geometry, human visual functions and visual performance measurement. Therefore, only simple geometric or photometric models are generally provided in human factors text books in the forms such as equations, graphs, or nomograms. This paper presents an easy to use but a more comprehensive model developed for a human factors engineering class to understand the variables, photometric measurements and use of human visual threshold data. The model can be easily down-loaded and exercised by a PC user to quickly estimate visibility and legibility in a number of situations. The model serves as a great tool to analyze a number of “what if” scenarios and learn the basics of human visual performance. The model will be an excellent candidate for including in a practicing human factors engineers tool box.

Towards Development of a Methodology to Measure Perception of Quality of Interior Materials

The automotive interior suppliers are challenged to develop materials, that not only perform functionally, but also provide the right combination sensory experience (e.g. visual appeal, tactile feeling) and brand differentiation at very competitive costs. Therefore, the objective of this research presented in this paper is to develop a methodology that can be used to measure customer perception of interior materials and to come up with a unique system for assessing value of different interior materials. The overall methodology involves the application of a number of psychophysical measurement methods (e.g. Semantic Differential Scaling) and statistical methods to assess: 1) overall customer perceived quality of materials, 2) elements (or attributes) of perception, and 3) value of materials from OEMs viewpoint in terms of the measurement of perception of quality divided by a measure of cost. This paper describes results of two pilot studies conducted for the following research phases: 1) Development of a list of adjective pairs to describe scales for overall evaluation/impression of the materials (e.g. Expensive-Cheap, Genuine-Fake, Quality-Shoddy, etc.), 2) Development of adjective pairs to measure elements of perception (e.g. Soft-Hard, Light-Dark, Smooth-Rough, Glossy-Flat, Slippery-Grippy, etc.), 3) Evaluation of a large number of materials of different types (e.g. woods, plastics/composites, fabrics, metallic, etc.) using the scales developed in earlier phases.

Understanding Customer Needs in Designing Automotive Center Consoles

This paper presents results of two studies conducted to determine customer needs in designing future center console designs for automotive products. The first study involved an observational survey of 150 vehicles in three parking lots to determine what items people store in their vehicles and the item locations. The data obtained from the survey provided a list of all the stored items, their distribution and their locations inside the vehicle. Papers, bottles, cups, books, bags and sunglasses were most frequently observed items in the vehicles. The second study was conducted to determine storage preferences of items in the center console. A foam-core center console with velcro surfaces was built inside a minivan. Thirty-six drivers were asked to select items that they would carry most often in their vehicles and place them on the center console surfaces. The resulting layouts of stored items were summarized. The summary data were provided to four teams of industrial design and engineering students to create design concepts for future automotive center consoles.

Relationship of customer needs to electric vehicle performance

This paper presents results of sensitivity analyses performed by exercising an electric vehicle model to understand relationship between customer based vehicle requirements (e.g. size, carrying capacity, weight, aerodynamics, 0–60 mph acceleration time, maximum velocity ) to electric vehicle characteristics (motor and battery specs.), energy consumption during different trips, and running costs for a trip. The electric vehicle model was developed by using available knowledge from mechanics, electrical powertrain and battery technologies. Velocity-distance trajectories of three trips (suburban, city commuter, and freeway) were measured and used as inputs to the model. The model was run under the combinations of the following variables and levels: a) vehicle weight: 2500 lbs small car and 4500 lbs midsize SUV, b) payload load: driver only and five occupants plus luggage, c) time for maximum acceleration from 0 to 60 mph: 4 sec, 7 sec and 10 sec, d) coefficient of drag (CD): 0.25 and 0.35, and e) trip purpose: suburban, city commuter, and freeway. The following model outputs were evaluated: 1) motor power (hp), 2) energy consumed per mile (KWh/mile), and 3) trip costs (cents/trip).

Evaluation of the PVM Methodology to Evaluate Vehicle Interior Packages

Programmable vehicle models (PVMs) are used in industry to quickly and economically compare ergonomic characteristics between different vehicle package arrangements. Presented in this paper are results from a series of three studies conducted to determine the applicability and limitations of the methodology of using a PVM. The study had four major objectives: determine if the PVM can accurately repeat package configurations; determine if subjects have the ability to judge interior package characteristics; determine if measurements of subjects in position are repeatable; and determine if the evaluations of vehicle configurations programmed in the PVM provide similar test results to the evaluations made by the subjects in actual vehicles. Overall, the validity of using the PVM as a design tool has been verified, but accurate representation of a vehicle package and other influencing surfaces is the key issue in future usefulness of the PVM as a design tool.

ACE Driving Simulator and Its Applications to Evaluate Driver Interfaces

A fixed base driving simulator, operating procedure and software system have been developed by a team of automotive suppliers. The system is designed to provide quick feedback to the product designers in early concept generation and validation phases of new automotive human-machine interface (HMI) architecture strategies and interfaces of in-vehicle devices. This paper presents a description of the simulator system, illustrations on its evaluation performance and results of two experiments conducted to evaluate different radio designs by involving different radio and non-radio tasks (such as increase/decrease radio volume, eject a CD and insert a new CD, answer a cell phone, dial a telephone number, etc.). The simulator consists of a reconfigurable cab with quick-change attachments to mount various controls and displays in package positions. A number of drivers are asked to drive the simulator and perform a number of tasks when prompted by pre-recorded voice commands. The entire data collection and data analysis procedure is developed such that new experiments can be configured, implemented and analyzed quickly and with the least amount of a human analysts involvement. The system generates reports showing graphs of driver behavior, performance measures, and subjective impressions of drivers for different tasks associated in operating/using various in-vehicle controls and displays. Findings show that the simulator and the HMI evaluation process provide a very powerful method to evaluate tasks associated with new in-vehicle devices and to compare the measures obtained from tests with similar data obtained from the evaluation of other in-vehicle devices.

Effect of Windshield Veiling Glare on Driver Visibility

This paper presents results of a veiling glare prediction model that was developed by modeling veiling glare luminance measurements and by using Blackwells visual contrast threshold data. A critical visibility condition for a driver approaching a tunnel with the sunlight falling on the windshield and attempting to detect a target inside the tunnel was modeled. The luminance of windshield reflections of 38 instrument panel samples was measured in a specially designed veiling glare simulator by varying the sun angle, the windshield angle, and the instrument panel angle. The measurements were used to develop a regression model to predict the veiling glare coefficient as a function of windshield angle, sun angle, instrument panel angle, and instrument panel material gloss value. The developed visibility–distance prediction model was exercised by varying eight factors: (a) windshield angle, (b) instrument panel angle, (c) sun angle, (d) sun illumination incident on the windshield, (e) gloss level of the instrument panel material, (f) drivers age, (g) target size, and (h) illumination incident on the target in the tunnel. For example, under a worst-case situation of 45,000-lux sunlight illumination incident on the windshield, a 65-year-old driver will not be able to see a 2-ft2 10% reflectance target while approaching a dark tunnel with 100 lux of tunnel lighting. In contrast, if the tunnel lighting is raised to 5,000 lux, the 65-year-old driver can see the target from 650 ft, and a 25-year-old can see it from 4,900 ft.

Development of Specifications for the UM-D's Low Mass Vehicle for China, India and the United States

This paper presents results of a research project conducted to develop a methodology and to refine the specifications of a small, low mass, low cost vehicle being developed at the University of Michigan-Dearborn. The challenge was to assure that the design would meet the needs and expectations of customers in three different countries, namely, China, India and the United States. U.S, Chinese and Indian students studying on the university campus represented customers from their respective countries for our surveys and provided us with the necessary data on: 1) Importance of various vehicle level attributes to the entry level small car customer, 2) Preferences to various features, and 3) Direction magnitude estimation on parameters to size the vehicle for each of the three markets. Our specification process involved: a) Development of a generic vehicle level Quality Function Deployment (QFD) analysis to relate customer needs to engineering attributes, b) Conducting a literature survey of various existing requirements and regulations on vehicles, c) Using importance ratings on various customer needs and vehicle attributes obtained from our subjects from the three countries, d) Sizing the vehicle for respective markets from the direction magnitude scaling, and e) Selecting base and optional feature content for the three markets from the customer ratings. The results of the analyses showed that: 1) Low vehicle cost emerged as the single most important vehicle level attribute from the QFD chart. 2) Fuel efficiency, durability and serviceability, from the customer importance rating survey, were the most important vehicle attributes, 3) One vehicle configuration would not be suitable for all the three markets without some modifications to satisfy the significant differences observed among the three countries. For example, a HVAC system was absolutely necessary to 94% of U.S. customers, but Indian customers had no need for it. Fog lamps were absolutely necessary to about 76% of Chinese customers but only less than 16% of U.S. customers and only about 6% of Indian Customers wanted them. 4) Indian customers wanted smaller wheelbase as compared to the U.S. and Chinese customers.