Probabilistic Conflict Detection for Piecewise Straight Paths
Per-Johan Nordlund, Fredrik Gustafsson · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2008
We consider probabilistic methods for detecting conflicts as a function of predicted trajectory. A conflict is an event representing collision or imminent collision between vehicles or objects. The computations use state estimate and covariance from a target tracking filter based on sensor readings. Existing work is primarily concerned with risk estimation at a certain time instant, while the focus here is to compute the integrated risk over the critical time horizon. This novel formulation leads to evaluating the probability for level-crossing. The analytic expression involves a multi-dimensional integral which is hardly tractable in practice. Further, a huge number of Monte Carlo simulations would be needed to get sufficient reliability for the small risks that the applications often require. Instead, we propose a sound numerical approximation that leads to evaluating a one-dimensional integral which is suitable for real-time implementations.