Tag: Mental models

Emerging Technologies

Mapping Comprehension of ADAS across Different Road Users

This survey study examined how level of knowledge of advanced driver assistance systems (ADAS) varied by driver type, experience, perceptions regarding vehicle technology, attitudes and preferences towards education, and confidence, among others.

October 2023 Technical Report | Report Summary

Autonomous Vehicles

Emerging Technologies

Change in Mental Models of ADAS in Relation to Quantity and Quality of Exposure

This longitudinal driving simulator study assesses how exposure to different amounts and types of edge-case events influence the development and accuracy of drivers’ understanding of vehicle automation.

June 2023 Technical Report | Report Summary

Close up of hand touching vehicle dashboard

Emerging Technologies

User Interactions with Vehicle Automation Technologies: A Review of Previous Research and a Proposed Framework

This research brief reviews recent research and proposes a framework on user perceptions, understanding, and interactions with vehicle automation technology.

January 2023 Research Brief

The Impact of Driver’s Mental Models of Advanced Vehicle Technologies on Safety andThe Impact of Driver’s Mental Models of Advanced Vehicle Technologies on Safety and Performance Performance

Emerging Technologies

Expectations and Understanding of Advanced Driver Assistance Systems among Drivers, Pedestrians, Bicyclists, and Public Transit Riders

The current study examines the perceptions, understanding and expectations of other road users (bicyclists, pedestrians, transit riders) regarding current advanced driver assistance systems (ADAS), as well as more highly automated future technologies.

June 2021 Technical Report | Report Summary

The Impact of Driver’s Mental Models of Advanced Vehicle Technologies on Safety andThe Impact of Driver’s Mental Models of Advanced Vehicle Technologies on Safety and Performance Performance

Emerging Technologies

Driver’s Mental Models of Advanced Vehicle Technologies: A Proposed Framework for Identifying and Predicting Operator Errors

This project proposes a framework for identifying and predicting operator errors when using advanced vehicle technology, such as active driving assistance systems. This research also examined the reporting of system limitations by automobile manufacturers.

February 2021 Technical Report | Report Summary