We consider the problem of correct motion planning for T-intersection merge-ins of arbitrary geometry and vehicle density. A merge-in support system has to estimate the chances that a gap between two consecutive vehicles can be taken successfully. In contrast to previous models based on heuristic gap size rules, we present an approach which optimizes the integral risk of the situation using parametrized velocity ramps. It accounts for the risks from curves and all involved vehicles (front and rear on all paths) with a so-called survival analysis. For comparison, we also introduce a specially designed extension of the Intelligent Driver Model (IDM) for entering intersections. We show in a quantitative statistical evaluation that the survival method provides advantages in terms of lower absolute risk (i.e., no crash happens) and better risk-utility tradeoff (i.e., making better use of appearing gaps). Furthermore, our approach generalizes to more complex situations with additional risk sources.

翻译：我们针对任意几何构型和车辆密度的T型交叉口汇入问题，研究了正确的运动规划方法。汇入辅助系统需评估两辆连续车辆之间空隙可被成功利用的概率。与以往基于启发式空隙大小规则的模型不同，本文提出一种利用参数化速度斜坡优化场景综合风险的方法。该方法通过所谓的生存分析，综合考虑弯道风险及所有相关车辆（路径上前方与后方车辆）的影响。作为对比，我们还引入了一种特制的智能驾驶员模型（IDM）扩展版本用于交叉口汇入场景。定量统计评估表明，生存分析法在降低绝对风险（即避免碰撞）和优化风险-效用权衡（即更有效利用出现的空隙）方面具有优势。此外，该方法可推广至包含额外风险源的更复杂场景。