関係的局所動的マップを用いた遮蔽リスクに対する交差点警告システム
Intersection Warning System for Occlusion Risks using Relational Local Dynamic Maps
局所動的マップ上でレイキャストを行い視界を推定し、遮蔽されたリスク対象の最悪ケース軌道を予測して衝突リスクを評価する交差点警告システムを提案し、実世界で検証した。
著者: Florian Damerow, Yuda Li, Tim Puphal, Benedict Flade, Julian Eggert
分類: cs.RO, cs.AI
原文アブストラクト
This work addresses the task of risk evaluation in traffic scenarios with limited observability due to restricted sensorial coverage. Here, we concentrate on intersection scenarios that are difficult to access visually. To identify the area of sight, we employ ray casting on a local dynamic map providing geometrical information and road infrastructure. Based on the area with reduced visibility, we first model scene entities that pose a potential risk without being visually perceivable yet. Then, we predict a worst-case trajectory in the survival analysis for collision risk estimation. Resulting risk indicators are utilized to evaluate the driver's current behavior, to warn the driver in critical situations, to give suggestions on how to act safely or to plan safe trajectories. We validate our approach by applying the resulting intersection warning system on real world scenarios. The proposed system's behavior reveals to mimic the general behavior of a correctly acting human driver.
