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首页> 外文期刊>The Open Transportation Journal >Application of Geographical Information System Techniques to Determine High Crash-Prone Areas in the Fort Peck Indian Reservation
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Application of Geographical Information System Techniques to Determine High Crash-Prone Areas in the Fort Peck Indian Reservation

机译：地理信息系统技术在堡垒佩克印度预约中确定高碰撞地区的应用

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Background: Historically, Indian reservations have been struggling with higher crash rates than the rest of the United States. In an effort to improve roadway safety in these areas, different agencies are working to address this disparity. For any safety improvement program, identifying high risk crash locations is the first step to determine contributing factors of crashes and select corresponding countermeasures. Methods: This study proposes an approach to determine crash-prone areas using Geographic Information System (GIS) techniques through creating crash severity maps and Network Kernel Density Estimation (NetKDE). These two maps were assessed to determine the high-risk road segments having a high crash rate, and high injury severity. However, since the statistical significance of the hotspots cannot be evaluated in NetKDE, this study employed Getis-Ord Gi* (d) statistics to ascertain statistically significant crash hotspots. Finally, maps generated through these two methods were assessed to determine statistically significant high-risk road segments. Moreover, temporal analysis of the crash pattern was performed using spider graphs to explore the variance throughout the day. Results: Within the Fort Peck Indian Reservation, some parts of the US highway 13, BIA Route 1, and US highway 2 are among the many segments being identified as high-risk road segments in this analysis. Also, although some residential roads have PDO crashes, they have been detected as high priority areas due to high crash occurrence. The temporal analysis revealed that crash patterns were almost similar on the weekdays reaching the peak at traffic peak hours, but during the weekend, crashes mostly occurred at midnight. Conclusion: The study would provide tribes with the tool to identify locations demanding immediate safety concerns. This study can be used as a template for other tribes to perform spatial and temporal analysis of the crash patterns to identify high risk crash locations on their roadways.
机译：背景：历史上，印度保留一直在努力争取高于美国的困境。在这些领域提高道路安全的努力，不同的各机构正在努力解决这种差异。对于任何安全改进计划，识别高风险碰撞位置是确定崩溃的贡献因素的第一步，并选择相应的对策。方法：本研究提出了一种方法，可以使用地理信息系统（GIS）技术来确定崩溃易于区域，通过创建崩溃严重性映射和网络内核密度估计（NETKDE）。评估这两张地图以确定具有高碰撞率的高风险道路段，以及高损伤严重程度。但是，由于热点的统计显着性无法在NetKDE中评估，因此本研究采用了Getis-Ord Gi *（d）统计数据来确定统计上大量的崩溃热点。最后，评估了通过这两种方法生成的地图，以确定统计上显着的高风险道路段。此外，使用蜘蛛图进行碰撞模式的时间分析，以探讨全天的方差。结果：在堡垒Peck印度预订中，美国高速公路13号公路1号和美国高速公路2的部分地区是在该分析中被确定为高风险道路段的许多细分。此外，虽然一些住宅道路具有PDO崩溃，但由于高碰撞发生，它们被检测为高优先级区域。时间分析表明，在流量高峰时段的平日达到峰值时，坠机模式几乎相似，但在周末，崩溃主要发生在午夜。结论：该研究将提供与该工具的部落，以确定要求立即安全问题的地点。本研究可以用作其他部落的模板，以对碰撞模式进行空间和时间分析，以识别其道路上的高风险碰撞位置。

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