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.

本文介绍了一种用于交通场景风险评估的方法，主要关注可视性受限的路口场景。通过使用局部动态地图进行光线投射以获得视野区域，识别存在潜在风险的场景实体并进行碰撞风险评估，得出用于评估驾驶人行为的风险指标，并通过实际场景验证其有效性。