This paper introduces Sentinel, an onboard system for intelligent vehicles that guides their lane changing behavior during a freeway incident with the goal of reducing traffic congestion, capacity drop, and delay. When an incident blocking the lanes ahead is detected, Sentinel calculates the probability of leaving the blocked lane(s) before reaching the incident point at each time step. It advises the vehicle to leave the blocked lane(s) when that probability drops below a certain threshold, as the vehicle nears the congestion boundary. By doing this, Sentinel reduces the number of late-stage lane changes of vehicles in the blocked lane(s) trying to move to other lanes, and distributes those maneuvers upstream of the incident point. A simulation case study is conducted in which one lane of a four-lane section of the I-66 interstate highway in the U.S. is temporarily blocked due to an incident, to understand how Sentinel impacts traffic flow and how different parameters - traffic flow, system penetration rate, and incident duration - affect Sentinel's performance. The results show that Sentinel has a positive impact on traffic flow, reducing average delay by up to 37%, particularly when it has a considerable penetration rate. Working alongside Traffic Incident Management Systems (TIMS), Sentinel can be a valuable asset for reducing traffic delay and potentially saving billions of dollars annually in costs associated with congestion caused by freeway incidents.

翻译：本文介绍Sentinel(Sentinel),这是一个智能车辆的船上系统,在高速公路事故发生时引导其车道改变行为,目的是减少交通堵塞、能力下降和延误。当发现堵塞前方车道的事件时,Sentinel计算出每一步到达事故点之前离开被封锁的车道的概率。它建议车辆离开被封锁的车道,如果该概率下降到某一阈值以下,因为车辆接近堵塞边界。通过这样做,Sentinel减少了被封锁车道中试图移动到其他车道的车道的后期车道变化次数,并将这些车道向事件点上游分配。在进行模拟案例研究时,I-66美国跨州高速公路的一条四行道因事故而暂时受阻。它建议车辆离开被封锁的车道,当车道在交通堵塞线附近行驶时,交通流量、系统渗透率和事件持续时间长短等不同参数会影响Sentinel的性能。结果显示,Sentinel(Sentinel)对交通流量流量流量的积极影响,减少平均路流,使交通持续延迟率下降率降低至37,这时, 可能导致资产延迟导致资产管理事故持续成本。