From Effects to Causes: Reversible Simulation and Reverse Exploration of Microscopic Traffic Models

Philipp Andelfinger, Jordan Ivanchev, D. Eckhoff, Wentong Cai, A. Knoll
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引用次数: 3

Abstract

We propose an approach for reverse-in-time exploration of the state space of microscopic traffic simulations starting from a user-specified class of outcomes. As a basis for our approach, we present a reversible execution scheme applicable to common car-following and lane-changing models from the traffic simulation literature. The execution scheme permits perfect reversal of a previous forward simulation, which to our knowledge has not been attempted previously in the context of established traffic simulation models. Further, we perform reverse state space explorations directly from user-specified simulation states, i.e., reverse-in-time model checking. By exploring all sequences of possible previous states from a final state, reachability questions can be answered more conclusively than purely through forward simulations. In a case study, reverse exploration is used to identify conditions that lead to specified accident situations, with running time reductions by factors of more than 20 compared to traditional forward exploration.
从影响到原因:微观交通模型的可逆模拟与反向探索
我们提出了一种从用户指定的结果类别开始对微观交通模拟的状态空间进行逆时探索的方法。作为我们方法的基础,我们从交通仿真文献中提出了一种适用于常见车辆跟随和变道模型的可逆执行方案。执行方案允许对先前的正向模拟进行完美的逆转,据我们所知,这在之前建立的交通模拟模型中还没有尝试过。此外,我们直接从用户指定的仿真状态执行反向状态空间探索,即逆时模型检查。通过从最终状态探索所有可能的先前状态序列,可达性问题可以比纯粹通过前向模拟得到更确凿的答案。在一个案例研究中,反向勘探用于识别导致特定事故情况的条件,与传统的正向勘探相比,运行时间减少了20多倍。
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