Situational Awareness, Driver’s Trust in Automated Driving Systems and Secondary Task Performance

Driver assistance systems, also called automated driving systems, allow drivers to immerse themselves in non-driving-related tasks. Unfortunately, drivers may not trust the automated driving system, which prevents either handing over the driving task or fully focusing on the secondary task. We assert that enhancing situational awareness can increase a driver's trust in automation. Situational awareness should increase a driver's trust and lead to better secondary task performance. This study manipulated driversʼ situational awareness by providing them with different types of information: the control condition provided no information to the driver, the low condition provided a status update, while the high condition provided a status update and a suggested course of action. Data collected included measures of trust, trusting behavior, and task performance through surveys, eye-tracking, and heart rate data. Results show that situational awareness both promoted and moderated the impact of trust in the automated vehicle, leading to better secondary task performance. This result was evident in measures of self-reported trust and trusting behavior.This research was supported in part by the Automotive Research Center (ARC) at the University of Michigan, with funding from government contract Department of the Army W56HZV-14-2-0001 through the U. S. Army Tank Automotive Research, Development, and Engineering Center (TARDEC). The authors acknowledge and greatly appreciate the guidance of Victor Paul (TARDEC), Ben Haynes (TARDEC), and Jason Metcalfe (ARL) in helping design the study. The authors would also like to thank Quantum Signal, LLC, for providing its ANVEL software and invaluable development support.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148141/1/SA Trust - SAE- Public.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148141/4/Petersen et al. 2019.pdfDescription of Petersen et al. 2019.pdf : Final Publication Versio

Accessible Autonomy: Exploring Inclusive Autonomous Vehicle Design and Interaction for People who are Blind and Visually Impaired

Autonomous vehicles are poised to revolutionize independent travel for millions of people experiencing transportation-limiting visual impairments worldwide. However, the current trajectory of automotive technology is rife with roadblocks to accessible interaction and inclusion for this demographic. Inaccessible (visually dependent) interfaces and lack of information access throughout the trip are surmountable, yet nevertheless critical barriers to this potentially lifechanging technology. To address these challenges, the programmatic dissertation research presented here includes ten studies, three published papers, and three submitted papers in high impact outlets that together address accessibility across the complete trip of transportation. The first paper began with a thorough review of the fully autonomous vehicle (FAV) and blind and visually impaired (BVI) literature, as well as the underlying policy landscape. Results guided prejourney ridesharing needs among BVI users, which were addressed in paper two via a survey with (n=90) transit service drivers, interviews with (n=12) BVI users, and prototype design evaluations with (n=6) users, all contributing to the Autonomous Vehicle Assistant: an award-winning and accessible ridesharing app. A subsequent study with (n=12) users, presented in paper three, focused on prejourney mapping to provide critical information access in future FAVs. Accessible in-vehicle interactions were explored in the fourth paper through a survey with (n=187) BVI users. Results prioritized nonvisual information about the trip and indicated the importance of situational awareness. This effort informed the design and evaluation of an ultrasonic haptic HMI intended to promote situational awareness with (n=14) participants (paper five), leading to a novel gestural-audio interface with (n=23) users (paper six). Strong support from users across these studies suggested positive outcomes in pursuit of actionable situational awareness and control. Cumulative results from this dissertation research program represent, to our knowledge, the single most comprehensive approach to FAV BVI accessibility to date. By considering both pre-journey and in-vehicle accessibility, results pave the way for autonomous driving experiences that enable meaningful interaction for BVI users across the complete trip of transportation. This new mode of accessible travel is predicted to transform independent travel for millions of people with visual impairment, leading to increased independence, mobility, and quality of life

Improving Drivers’ Behaviour When Partial Driving Automation Fails

With the advent of automated vehicle systems, the role of drivers has changed to a more supervisory role. However, it is known that all vehicles with Level 2 (L2) systems have a very specific operational design domain (ODD) and can only function on limited conditions. Hence, it is important for drivers to perceive the situations properly and regain the control from the L2 system when needed. As suggested by past research, designing an informative interface could help drivers in their new supervision and intervention role while driving with L2 vehicles by providing feedback to drivers when hazards or event that may cause system failure are detected. On the other hand there are many situations where these vehicles cannot detect hazards and provide any feedback prior to the event. In these cases, training programs which provide drivers with an experience of these system limitations and allow them to practice dealing with such limitations can prove to be effective countermeasures. The objective of the current study is to employ different methods (designing HMI and training drivers) to increase drivers’ situational awareness regarding operational design domain (ODD) and improve drivers performance in transfer of control situations while driving with level 2 (L2) automation features. This study includes two experiments- in first experiment, an informative dashboard interface was designed and tested through three phases (observation, prototyping, testing). Results from the testing phase showed that drivers who received the newly designed dashboards took back control more effectively and had more situational awareness compared to the control group. In the second experiment, a PC-based training program was designed and tested to improve drivers takeover response and situational awareness when L2 systems reach their ODD limits. Results showed drivers in the PC-based training group took back control more effectively when L2 systems reached their ODD limits and had more situational awareness compared to the drivers who received user manual or placebo training

Supporting People with Vision Impairments in Automated Vehicles: Challenge and Opportunities

Autonomous and automated vehicles (AVs) will provide many opportunities for mobility and independence for peoplewith vision impairments (PwVI). This project provides insights on the challenges and potential barriers to their adoptionof AVs. We examine adoption and use of ridesharing services. We study ridesharing as a proxy for AVs as they are asimilar means of single-rider transportation for PwVI through observations and interviews. We also investigateperceptions towards autonomous vehicles and prototypes to address perceived barriers to AV use through design focusgroups with blind and low vision people. From these studies, we provide recommendations to AV manufacturers andsuppliers for how to best design vehicles and interactive systems that people with vision impairments trust.United States Department of Transportationhttps://deepblue.lib.umich.edu/bitstream/2027.42/156054/3/Supporting People with Vision Impairments in Automated Vehicles - Challenges and Opportunities.pd