Laboratory of Advanced Mobility and Transportation Engineering
As of October 28, 2021
Basic information
Division
Engineering and Policy for Sustainable Environment
* Please go to Courses to see the list of subjects offered by the division.
Laboratory's URL
https://www.eng.hokudai.ac.jp/labo/kyoku/english.html
Faculty members accepting applicants
TAKAHASHI Sho (Assoc. Prof.)
About the laboratory
Description
The main target of our research is to support and develop novel technologies for transportation and information engineering.It covers image/video analysis, data analysis, AI, IoT, visualization, data science, transportation planning, city planning, planning mathematics, traffic information system and driving assessment.
Organization of research
Our laboratory is composed of two faculty members Dr. TAKAHASHI and Dr. HAGIWARA as the same research team. Research activities, seminars, and other events have cooperated with all members. Seminars which are reported research progress from some students are held every week. Basically, all students have a research meeting with the supervisor.
Ongoing projects
The examples of reserach projects are follows:
(1) Avoidance behavior on bicycle trips detection based on multimodal apporach for road management
(2) Effects of Winter road surface on driver's risk avoidance behavior when the vehicle are entering a curve with adaptive cruise control
(3) Development of poor visibility assessment method in winter using images taken by on-board video camera
(4) Effect of speed adjustment delineator on driver's risk avoiding behavior with the merging vehicle while level 2 automated driving
(5) Effects of time-gap settings of adaptive cruise control (ACC) on driver's risk feeling estimated by the car-following situation
(6) Estimating Road Narrowing Condition by in-Vehicle Camera
(7) Visibility level estimation in winter CCTV images based on decision level fusion
(8) Estimating visibility level based on low rank matrix completion using GPV data
(9) Automatic generation of training data for deep learning in AR-based transportation support system
Information for potential applicants
Applicants' background
It will be great if applicants have basic knowledge about transportation engineering, information science, and computational skills. Experimental works in our laboratory always need a spirit of cooperation. We expect that the students proactively work together with the others.
Plan to accept applicants
| Application type | Enrollment semester | Master’s course | Doctoral course | Comments |
|---|---|---|---|---|
| MEXT Scholarship (Uniform call) | Oct. 2022 | 〇 | 〇 | |
| MEXT Embassy | 〇 | 〇 | ||
| e3 Special Selection | Oct. 2022 | 〇 | 〇 |
How to apply
Please follow the application procedure for the respective application category announced at the e3 web page.
Accepting Research Students
We do not accept Research students.
Availability of financial support
Please check the e3 web page for information about the scholarships and other financial support.
Inquiries
If you have any inquiries about the application and admission procedures etc., please contact the e3 office. You can submit your application on-line during the "matching period" irrespective of prior contact with potential supervisor(s).