Dr. Akito Higatani | Intelligent Sensors | Best Researcher Award

Dr. Akito Higatani, Hanshin Expressway Co., Ltd., Japan

Akito Higatani is an accomplished professional in traffic engineering, currently serving as Assistant Manager in the Planning Department at Hanshin Expressway Co., Ltd. With a career spanning 18 years, he has made significant contributions to the field through his research and practical insights into traffic management and efficiency. Dr. Higatani’s academic journey began at Kyoto University, Japan, where he earned his Bachelor’s degree in Engineering from the Undergraduate School of Global Engineering, specializing in Transportation Engineering and Management. He continued his studies at Kyoto University, obtaining a Master’s degree in Urban Management, focusing on traffic efficiency in urban expressways. His doctoral studies also at Kyoto University culminated in a Doctor of Engineering degree, where his research focused on planning patrolling schedules in urban expressway networks considering traffic incidents and network performance fluctuations. Dr. Higatani has contributed extensively to the field through peer-reviewed papers and presentations at international conferences. His research, such as studying traffic volume fluctuations and travel time reliability measures in the Hanshin Expressway Network, has been instrumental in advancing understanding and strategies in traffic engineering.

Professional Profile:

SCOPUS

Education:

Akito Higatani pursued his academic journey at Kyoto University, Japan, specializing in Transportation Engineering and Management.

Bachelor of Engineering (Undergraduate School of Global Engineering, April 2000 – March 2004): Akito completed his undergraduate studies with a focus on Transportation Engineering and Management. His graduation thesis investigated traffic flow observation using image data.
Master of Engineering (Department of Urban Management, April 2004 – March 2006): Continuing his studies at Kyoto University, Akito delved deeper into urban traffic management, particularly focusing on traffic efficiency at merging sections of urban expressways using image data.
Doctor of Engineering (Department of Urban Management, April 2012 – March 2015): Akito pursued his doctoral studies, specializing in planning patrolling schedules within urban expressway networks. His dissertation focused on optimizing schedules considering traffic incidents and network performance fluctuations.

Work Experience:

Akito Higatani has accumulated extensive experience in traffic engineering and management, primarily at Hanshin Expressway Co., Ltd.

Assistant Manager, Planning Department: Akito has been serving as an Assistant Manager since joining Hanshin Expressway in April 2006. His role involves strategic planning within the Planning Department, focusing on optimizing traffic flow and efficiency across the expressway network.

Academic Achievements:

Akito Higatani has contributed significantly to the field of traffic engineering through peer-reviewed publications and conference presentations:

Publication top Notes:

Assessing the Impacts of Autonomous Vehicles on Road Congestion Using Microsimulation

An investigation into the appropriateness of car-following models in assessing autonomous vehicles

Driving simulator experiment on speed reduction during earthquake on an urban expressway

A study of traffic volume fluctuation considering traffic incidents in hanshin expressway network

Slippage test of frictional high strength bolted joints with adhesives for corroded damaged steel members

Introduction Best Wearable Sensing Technology

Welcome to the prestigious ‘Best Wearable Sensing Technology‘ award, celebrating innovation and excellence in the field of wearable sensor technology. This award recognizes breakthroughs that have the potential to revolutionize how we monitor and interact with our environment and ourselves.

Award Eligibility:

The award is open to individuals and teams worldwide who have developed groundbreaking wearable sensing technology. There are no age limits, and both academic and industry professionals are eligible to apply. Qualifications should demonstrate a significant contribution to the field, such as patents, publications, or successful product launches.

Evaluation Criteria:

Submissions will be evaluated based on the following criteria:

Innovation: Uniqueness and originality of the technology.

Practicality: Feasibility and usability of the technology.

Impact: Potential impact on society, healthcare, or other relevant fields.

Submission Requirements:

Applicants must submit a detailed description of their wearable sensing technology, including its design, functionality, and potential impact. Supporting documents, such as research papers, patents, or product prototypes, should also be included. Submissions will be evaluated based on innovation, practicality, and potential impact.

Recognition:

Winners will be announced on [Announcement Date] and will receive [Prize Details]. They will also have the opportunity to present their technology at [Event Details] and receive recognition in [Media Outlets].

Community Impact:

The ‘Best Wearable Sensing Technology‘ award aims to not only recognize technological innovation but also to encourage collaboration and knowledge sharing within the wearable sensor technology community.

Biography:

Include a brief biography highlighting your achievements and contributions to the field of wearable sensing technology.

Abstract and Supporting Files:

Submissions should include an abstract highlighting the key features and benefits of the technology. Supporting files such as videos, images, or technical documentation are encouraged.