详情

Development of a Monitoring System for Driver Readiness in Prolonged Automated Driving

项目名称：	Development of a Monitoring System for Driver Readiness in Prolonged Automated Driving
摘要：	Vehicle automation technology is being designed to handle driving tasks for human drivers. However, this technology is not expected to handle all possible driving conditions successfully in the foreseeable future. The system can fail anytime and may require drivers to take over control within a short period of time. Additionally, automation can induce boredom, daydreaming, and drowsiness due to driver inactivity and can worsen driver readiness to take over control of the vehicle. Driver readiness can be measured using their postural data, gaze behaviors, and emotional expressions. Specific thresholds for these measures can be used to alert drivers to be ready to take over from automated driving or avert them from driving, when necessary. This proposal aims to develop a driver readiness monitoring system to improve their takeover performance using a driving simulator study. The objectives are to identify effective measures to define driver readiness and assess the association between divers’ takeover performance and their readiness measures. Researchers will measure (i) driver readiness using postural data, gaze and head orientations, and emotional status from video recordings analyzed with Face Reader software; (ii) drivers’ categorical subjective responses on readiness; and (iii) takeover performance using reaction time, collision rate, and driving behavior. Different machine learning algorithms will be applied for (i) feature extraction, (ii) feature selection, and (iii) developing classification and prediction models for readiness monitoring. The rationales for this research are to: (a) inform policy makers about an effective driver-readiness monitoring system for prolonged automated driving; (b) provide safer driving conditions and address equity during prolonged driving for older adults, and occupational drivers (Uber, taxi, or city transportation) driving long hours; and (c) enhance educational and research infrastructures combining human-computer interactions and machine learning. Stakeholder involvement from the city, state, and automobile manufacturer will strengthen our tech-transfer and project outcome dissemination.
状态：	Active
资金：	150000
资助组织：	Center for Transportation Equity, Decisions, & Dollars；University of Texas at Arlington；Department of Transportation
管理组织：	Center for Transportation Equity, Decisions, & Dollars<==>University of Texas at Arlington
执行机构：	University of Texas at Arlington<==>University of Wisconsin-Madison<==>California State Polytechnic University, San Luis Obispo
主要研究人员：	Deb, Shuchisnigdha；Pande, Anurag；Kan, Chen；Noyce, David A
开始时间：	20220601
预计完成日期：	20230531
主题领域：	Data and Information Technology；Highways；Policy；Safety and Human Factors；Vehicles and Equipment