Automotive HMI

Overview: R&D project to develop an application for Android-based in-vehicle information system. The team consisted of approximately 10 members (PM + 5-7 software engineers + 2 HF/UX researchers) worked for the project.

Goal: Designing driving quality monitoring & reporting application for in-vehicle system to provide drivers real-time & post-driving feedback how safe/risky their driving is.

My role: As the HF&UX lead in the team, I contributed to UI design conducting evaluations by performing literature reviews for pain-point analysis of current driving scoring applications, as well as user interviews and interaction reviews on the prototypes. 

Outcomes: 

• Compiled and reported to the development team the essential elements needed to make calculated driving quality scores and advice from the system easily understandable and convincing for users. 

• The application was delivered to the product team (Huawei HiCar).

Goal: Establishing an evaluation method for in-vehicle input methods.   

My work: As a project member and a project liaison, I contributed to identifying research issues, setting up of project goals and schedule, managed progress, facilitated communication among stakeholders, conducted a part of data analysis and the final reporting.

Outcomes: 

• Proposed a procedure for conducting usability evaluations of input methods for in-vehicle information systems. 

• Identified important evaluation criteria of input methods for in-vehicle information systems. 

• Provided benchmarks for evaluating new input methods 

• These contributions aim to streamline the process of evaluating future input methods. 

• The resutls were reported to the client(Toyota Motor Corporation)

Kuriyagawa, Y.,Kageyama, I., Watanabe, S., Kuramoto, H., Mizobuchi, S., Nawa, K. and Kumon, H. (2010) Evaluating Human Machine Interface of In-Vehicle Information Systems, FISITA 2010 (International Federation of Automotive Engineering Societies) congress proceedings, F2010-H-013.

Goal: Developing "Smart Driver Notification (SDN)" system which is an adaptive UI to manage system notification timing and priority based on the estimated driver workload.

My work: As the HF&UX lead in the project team, I conducted literature reviews to identify factors to raise drivers cognitive workload, planed, designed and conducted user studies, which included test course driving as well as laboratory experiments for concept validation. 

Outcomes: 

• Compiled a list of factors considered to influence cognitive load, such as weather and road conditions, and assigned weights to the impact of each factor on cognitive load based on scoring from multiple drivers. 

• The weighting data here was utilized in the development of a reasoning algorithm to adjust the timing of system messages depending on the situation. 

• A prototype of the Safe Driver Notification system, incorporating the reasoning system, was developed by the development team.