2023 Fiscal Year Research-status Report
Edge-Intelligence-based Control of Next-Generation Vehicles for Cooperative Driving
| Project/Area Number |
23K03898
|
|---|
| Research Institution | Gunma University |
|---|
Principal Investigator |
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
山田 功 群馬大学, 大学院理工学府, 教授 (20240012)
|
|---|
| Project Period (FY) |
2023-04-01 – 2026-03-31
|
| Keywords | Cooperative Driving / Connected vehicle / Edge Computing / Cyber-physical System |
|---|
| Outline of Annual Research Achievements |
Aiming to develop edge intelligence for cooperative driving in various driving contexts, we have researched several aspects, including vehicle control techniques, cloud-based efficient traffic coordination, driving abnormality detection, and enhancing the perception of autonomous vehicles. The key outcome in the first year is the development of a cooperative lookahead driving technology that can improve traffic flows on multi-lane roads when they are affected by any incidents, which has been published in IEEE Transactions on Intelligent Vehicles. Under this technology, a vehicle unilaterally identifies the need and extends the cooperation to other lane vehicles, significantly improving traffic flows. Besides, cooperative driving at Railway level crossings under infra-based edge intelligence has been developed considering the real driving scenario at Shin-Kiryu Fumikiri. This edge computing-based optimal vehicle coordination techniques will be polished further in the following years.
In addition to the above-mentioned cooperative driving technologies, we have investigated two aspects of other driving systems. We are particularly investigating the detection of lanes or driveways on irregular roads and assessing the driving state (including abnormal maneuvering) based on real driving data. The preliminary studies are ongoing, employing various machine-learning and data-driven techniques. Overall, the progress was smoother, and we had better outcomes in the first year than our original plans.
|
| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
We have made significant progress in developing vehicle cooperative control technologies in various scenarios, as international collaborators are also supporting our leading team at Gunma University. The development of other aspects, such as perception of the environment, prediction of traffic, and respective intelligent decision mechanisms, is progressing as initially planned.
|
| Strategy for Future Research Activity |
The edge computing-based perception of the surrounding traffic is crucial for developing cooperative driving technology. Such cooperative techniques are not easily accessible at the low penetration rate of connected vehicles. The key research focus in the next year will be how to use limited information to effectively and precisely predict the surrounding traffic and, based on that, develop a cooperative driving decision scheme. Besides, the achievements in the first year will be further fine-tuned through rigorous examination.
|
| Causes of Carryover |
This amount remained as the original plan was to use it for journal publication fees and international travel expenses. However, both are scheduled in the next year, as one journal manuscript is still under review, and IEEE intelligent vehicle symposium is scheduled in June 2024 in Korea.
|
