Enforcement Engineering: A Scientific and Proactive Approach to the Simultaneous Reduction of Crime and Improvement of Road Safety

执法工程：同时减少犯罪和改善道路安全的科学和积极的方法

• 批准号: RGPIN-2014-05980
• 负责人: Park, Peter
• 金额: $ 1.46万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=636256
• 关键词: Enforcement; Engineering; Scientific; Proactive; Approach

Under the traditional enforcement systems, enforcement officers and city engineers typically wait until a location is identified as a problem area for crimes or traffic collisions before taking law enforcement action. Enforcement may then involve an automatic system or field officers. Either approach is reactive rather than proactive. In contrast, the proposed “enforcement engineering” strategies are based on data-driven, scientific analysis. This approach is more sophisticated, intelligence-led, and predictive in the sense that enforcement strategies target areas where, because high numbers of crimes and collisions are predicted, enforcement will be more efficient and can contribute to crime and collision prevention. The main goal of the proposed research program is twofold: 1) to introduce and establish a new, data-driven and analytical engineering program of enforcement designed to simultaneously and proactively reduce the expected number of future crimes and collisions; and 2) to develop a sustainable and commercializable mobile enforcement dispatch system (e.g., iPhone or Android Apps) designed to provide hands-on assistance for the various enforcement strategies of field agencies across Canada. Reactive enforcement based heavily on past history, elements of intuition, and even some random input (911 calls) is highly likely to be less cost-effective than proactive enforcement based on prevention and focused data supported intelligence and analysis, especially if the proactive enforcement can be designed to reduce crimes and collisions simultaneously. Due to the development of advanced geospatial and geostatistical technologies, and due to the modern GIS techniques, it is now possible to predict and identify hotspots associated with a high number of crimes and collisions. It is also possible to identify hotspots where particular types of crimes and collisions overlap. The overlapping hotspots are known to vary by time of day, day in the week, and month, and the shortest patrol routes to reach the hotspots will also vary. The proposed mobile enforcement dispatch system will broadcast the overlapping hotspots and the shortest patrol routes to field enforcement officers’ handheld devices on a real-time basis. Scientific enforcement engineering has an additional advantage. Some members of the public, including some City Council members, are suspicious of the motivation underlying existing law enforcement actions and complain of profiling or revenue-driven ticketing. Without clear justification based on scientific data analysis that determines the areas, times, and routes for specific law enforcement, it is difficult to counter these wide-spread suspicions. The proposed study will contribute to reducing the suspicions and is expected to increase the public’s support for various enforcement strategies. Dr. Park and his research team at U of S have recently partnered with Saskatchewan Government Insurance (SGI), the traffic safety authority in Saskatchewan, to develop a GIS based collision mapping system for various cities in Saskatchewan. The system currently analyses spatial collision patterns and uses the patterns mainly to identify potential locations for surface infrastructure improvements. The proposed NSERC DG research will build on the collision mapping system to include the mapping of crimes and various enforcement strategies, and will greatly enhance the real capacity of SGI and U of S in the new and developing area of engineering known as enforcement engineering. The research will advance knowledge in the fields of crime reduction and traffic safety, and will contribute significantly to improving the health and economic and social well-being of Canadians.

在传统的执法系统下，执法人员和城市工程师通常会等到一个地点被确定为犯罪或交通碰撞的问题区域后才采取执法行动。执法可能涉及一个自动系统或外勤人员。这两种方法都是被动的，而不是主动的。相比之下，拟议的“执行工程”策略是基于数据驱动的科学分析。这种方法更为复杂，以情报为主导，并具有预测性，因为执法战略的目标是预测到大量犯罪和碰撞的地区，因此执法将更有效，并有助于预防犯罪和碰撞。拟议研究计划的主要目标是双重的：1)引入和建立一个新的，数据驱动和分析工程执法计划，旨在同时主动减少未来犯罪和碰撞的预期数量；2)开发可持续和可商业化的移动执法调度系统（例如，iPhone或Android应用程序），旨在为加拿大各地实地机构的各种执法策略提供实际帮助。与基于预防和集中数据支持的情报和分析的主动执法相比，严重基于过去历史、直觉元素甚至一些随机输入（911电话）的被动执法很可能成本效益更低，特别是如果主动执法可以同时减少犯罪和碰撞。由于先进的地理空间和地质统计技术的发展，以及现代地理信息系统技术的发展，现在可以预测和识别与大量犯罪和碰撞相关的热点。它还可以识别特定类型的犯罪和碰撞重叠的热点。众所周知，重叠的热点在一天中的时间、一周中的一天和一个月都有所不同，到达热点的最短巡逻路线也会有所不同。拟议的流动执法调度系统将实时向现场执法人员的手持设备广播重叠热点和最短巡逻路线。科学执行工程还有一个额外的优势。一些公众人士，包括一些市议会议员，对现有执法行动背后的动机表示怀疑，并抱怨对罪犯进行定性或以收入为导向的售票。如果没有以科学数据分析为基础，确定具体执法的区域、时间和路线的明确理由，就很难反驳这些广泛存在的怀疑。建议进行的研究有助减少市民的怀疑，并有助提高市民对各项执法策略的支持。朴博士和美国大学的研究小组最近与萨斯喀彻温省交通安全当局萨斯喀彻温省政府保险公司（SGI）合作，开发了基于GIS的萨斯喀彻温省各个城市的碰撞地图系统。该系统目前分析空间碰撞模式，并主要利用这些模式来确定地面基础设施改进的潜在地点。拟议的NSERC DG研究将以碰撞测绘系统为基础，包括犯罪和各种执法策略的测绘，并将大大提高SGI和美国大学在新的和发展中的工程领域的实际能力，即执法工程。这项研究将促进减少犯罪和交通安全领域的知识，并将对改善加拿大人的健康和经济及社会福利作出重大贡献。