Autonomous collision avoidance control system design based on driving environment risk potential prediction
| Project/Area Number |
24560251
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Dynamics/Control
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| Research Institution | Tokyo University of Agriculture and Technology |
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Principal Investigator |
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| Project Period (FY) |
2012-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥5,460,000 (Direct Cost: ¥4,200,000、Indirect Cost: ¥1,260,000)
Fiscal Year 2014: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2013: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2012: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
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| Keywords | 交通機械制御 / 予防安全 / 自動運転 / 自動車の運動力学 / 運転支援 / 最適制御 / ポテンシャルフィールド / 障害物回避 / 機械力学・制御 / 電気自動車 / 交通事故 / 知能ロボティクス |
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| Outline of Final Research Achievements |
This paper proposes a motion planning and a braking/steering control for autonomous vehicles based on the combination of the optimal control theory and the potential field. This paper focuses on a parked car overtaking scenario as one of typical scenarios which the concept of risk potential can be applied. In the lateral motion control, the performance index in terms of the artificial risk potentials of road boundaries and an obstacle is optimized with respect to a number of candidate lateral accelerations. The artificial potential field is defined based on experienced driver characteristics analysis. In the longitudinal motion control, the performance index in terms of the artificial risk potential of the occluded pedestrian is optimized with respect to a number of candidate decelerations. The desired vehicle motion is calculated by optimizing the defined performance index and the results fit well with the data of the experienced drivers who drive defensively in urban roadway.
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Report
(4 results)
Research Products
(14 results)
