In order for critical driver alert systems to be universally effective, they must be designed with the broad population in mind, including people with accessibility concerns. The students on the Arriver team will research and design a driver alert system that specifically targets drivers with accessibility issues such as deafness and color blindness.
Arriver is a next-gen collaboration between Veoneer and Qualcomm Technologies that will enable automakers to bring more safety benefits to more drivers starting 2024. One of the key areas of development for Arriver is human machine interaction between drivers and vehicles, specifically in emerging autonomous driving technologies such as advanced driver assistance systems (ADAS) and automated driving systems (ADS).
In level 2 autonomous driving, ADAS such as adaptive cruise control assist the driver and enhance vehicle safety. Level 3 ADS can actually perform some of the driving tasks, allowing the driver to take their eyes off the road, as long as they stay alert. In these scenarios, the driver has to be fully aware of what is in and out of their control, and when they need to re-assume full control.
Consumer adoption of autonomous technology will depend in large part on how split-second moments in which imminent hazards are about to happen are experienced. Humans must trust automated systems to make the right decisions. In return, these systems must decipher a human driver’s readiness to intervene, as well as respond to a range of driver skill levels and human emotions.
In order for the communication between driver and autonomous car to be the most effective, the human machine interface must work for a wide range of people, including those with accessibility concerns.
The students on the Arriver team will research and design a driver alert system that specifically targets drivers with accessibility issues such as deafness and color blindness.
Improved ADAS HMI makes autonomous vehicles safer and increases consumer adoption. Exploring novel interactions can lead to improvements in adoption and standardization of features. According to the National Institute on Deafness and Other Communication Disorders, about 2 percent of adults in the United States aged 45 to 54 have disabling hearing loss. The rate increases to 8.5 percent for adults aged 55 to 64. Nearly 25 percent of those aged 65 to 74 and 50 percent of those who are 75 and older have disabling hearing loss. Additionally, about 1 in 12 men experience some form of colorblindness (the rate is considerably lower in women). As the driving population increases in the United States, addressing issues such as hearing loss and color blindness will become increasingly important
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System Design (2 students)
Specific Skills: System Design and incorporation of hardware. Sensors, camera, and microphone experience embedded systems, signal processing, etc. Basic knowledge of fast fabrication techniques and mechatronics a plus
Likely Majors: EE, CE, ME (with EECS 314)
Mechatronics Design (1 Student)
Specific Skills: Mechatronics design and system integration. Basic knowledge of fast fabrication techniques a plus
Likely Majors: ME (with EECS 314)
General Programming (1-2 students)
Specific Skills: General programming skills. Completion of EECS 281 HMI development. Video/Audio processing. The project will utilize Unity, C++ and Qt. Interest in human centered design processes.
Likely Majors: EE, CE, CS
User Interface / Accessible Design (1-2 students)
Specific Skills: Human perception and decision-making. User experience from a driver perspective. Experience or interest in inclusive design.
Completion of IOE 333/334 or SI 552 is a
plus. Should have basic coding skills and be willing to learn more about hardware.
Likely Majors: IOE, SI (HCI), Psych, Kines
Design Science and Product/Industrial Design (1 Student)
Specific Skills: Design Science, Design Process, Ethnographic Observation, User Studies, Creative Development/Generation of Solution concepts. Experience or interest in inclusive design.
Human Machine Interface
Likely Majors: ISD-Design Science, ARTDES, Any degree with C-SED minor
Aljohara is a UX researcher at Arriver. Her background is in computer science and she has a Master’s of Information Science from the University of Michigan where she participated on an MDP team. She has been working on the design and research of ADAS since late 2018.
Allen is the product owner responsible for user experience and HMI in Arriver’s Next Generation Supervised area. He has experience working in the automotive industry on infotainment systems, instrument clusters, innovation and design thinking. He has a background in mechanical engineering and human centered design
Michael is an Assistant Professor in the School of Information, where he leads the Information Interaction Lab. His lab investigates new methods, tools and technologies that enable users to interact with information in more natural and powerful ways, and also make it easier for designers to create more usable and effective user interfaces. Previously, he was a postdoctoral researcher and lecturer at the HCI Institute at Carnegie Mellon University and the Department of Computer Science at ETH Zurich, where he also obtained his PhD.
Course Substitutions: Honors, ChE Elective, CS MDE/Capstone, CE MDE, Data Science Capstone, EE MDE, IOE Senior Design, IOE Grad Cognate, ISD Design Sci, ISD AUTO 503, ISD Systems 503, MECHENG 490, SI Elective, SI Grad Cognate
Citizenship Requirements: This project is open to all students.
IP/NDA: Students will sign IP/NDA document(s) that are unique to Arriver
In Person/Remote Participation Options: Work will take place on campus with occasional visits to the Arriver Novi, MI office to hold meetings, access test vehicles, and give presentations as safety protocols allow. (MDP will provide transportation.)
On-Campus Participation Requirements:
- Students on this team must be able to be physically present on campus in Ann Arbor to work on physical prototypes as local safety protocols allow.
Internship/Summer Opportunity: Students will be guaranteed an interview for a 2022 internship. The interviews will take place between January / February 2022.