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Reconstitution of the Journeys to Crime and Location of Their Origin in the Context of a Crime Series. A Raster Solution for a Real Case Study

机译:在犯罪系列背景下重构犯罪之旅并确定犯罪根源。实际案例的栅格解决方案

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In the region of Charleroi (Belgium), a series of criminal acts were committed by the same group, using the same vehicle. The events were located in space and time. The car used during these criminal activities was stolen (first event) and was later retrieved (last event) after a period of 4 days of offences. Police recorded a crucial clue: the total mileage covered by the vehicle between the first and the last event was estimated with an admissible approximation. Thanks to this information, we were able to choose the most probable journey-to-crime among several scenarios. These depended on the combination of cost surfaces built with distance propagation algorithms starting from each criminal event in raster mode. The distance propagations were limited to the road network and the combinations of the cost surfaces had to respect the chronology of the facts. The most plausible scenario suggested that the criminals hided the car into a withdrawal site between their activities. In order to improve the precision of the location of this withdrawal site, we used a multi-criteria analysis taking account of the journey of the vehicle and other environment variables. At the end of these treatments, the small stretch of road that we isolated actually included the withdrawal site, as confirmed by the police later.
机译:在沙勒罗瓦(比利时)地区,同一团体使用同一工具实施了一系列犯罪行为。这些事件位于时空之中。在这些犯罪活动中使用的汽车被盗(第一次事件),经过4天的违法行为之后被取回(最后一次事件)。警方记录了一个关键线索:在第一个事件和最后一个事件之间,车辆行驶的总行驶里程是可以估计的。借助这些信息,我们能够在几种情况下选择最可能的犯罪旅程。这些依赖于使用距离传播算法构建的成本表面的组合,这些算法是从光栅模式中的每个犯罪事件开始的。距离传播仅限于道路网络,成本面的组合必须遵守事实的时间顺序。最合理的情况表明,犯罪分子在两次活动之间将汽车藏在了撤离地点。为了提高撤离地点的定位精度,我们使用了多标准分析,考虑了车辆的行程和其他环境变量。在这些治疗结束后,我们隔离的那条小路实际上包括了撤离地点,随后警方证实了这一点。

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