Grants and Contributions:

Advanced Driver Assistance Systems for Safe Mobility of Aging Population: A Human-in-the-loop Approach

998140

$84,900.00

Jan 1, 2023 - Dec 31, 2025

Driving cessation for many aging people is associated with a poorer quality of life brought about by the loss of mobility and independence, which ultimately can lead to physical and mental health problems such as depression, social isolation, diminished independence, etc. Connected and automated vehicle (CAV) technologies can provide feasible solutions to help ameliorate this problem. Although fully autonomous driving remains the goal of all involved R&D efforts, advanced driving assistance systems (ADASs) are already deployed at a mass scale that provide enhanced safety and warning systems and even enable partial automated driving. Recent year production vehicles are equipped with many ADAS features such as collision imminent braking systems, blind spot warning, automated lane centering, adaptive cruise control, automated parking, etc. All these features can help delay driving cessation for the aging population by compensating for the decline in cognitive capacity required for safe driving. However, current production ADAS systems do not consider driver behavior and intention. Typical implementations of ADAS systems are reactive in nature in that the safety of driving actions (acceleration and steering) are evaluated against the environment (presence of traffic ahead or in blind spots on adjacent lanes) after the fact. The proposed research aims to build an artificial intelligence (AI) based driver intentionality predictor that will augment and enhance typical ADAS systems to transform their nature from reactive to proactive. Since driver gaze directly correlates with driver intentionality and precedes driving action, this project will utilize a driver gaze monitoring system to develop an AI-based tool to predict driver intentionality and action. Such predictions can be used to provide warning or even enable automated vehicle actions, such as braking, speed reduction, collision avoidance. This will significantly improve driving safety and increase availability of mobility for aging people in the following ways: • The time horizon of conventional ADAS systems will be broadened to better include drivers with sub-optimal cognitive function. • Aging population can postpone driving cessation until much later stages in their lives without compromising their independence and the quality of life.

National Research Council Canada

In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.

London, Ontario, CA N6A 5B7

172-2022-2023-Q3-998140

Grant

Grants and Contributions

108162587

Academia

University of Western Ontario

London North Centre

35052

Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives

Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.

541710