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: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=677146
• 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某个位置被确定为犯罪或交通碰撞的问题区域后才采取执法行动。然后，执法可能涉及自动系统或现场官员。这两种方法都是被动的，而不是主动的。相比之下，拟议的"执法工程"战略是基于数据驱动的科学分析。这种方法更加复杂，以情报为主导，具有预测性，因为执法战略针对的是那些由于预测犯罪和碰撞数量高而执法效率更高并有助于预防犯罪和碰撞的地区。 拟议的研究计划的主要目标是双重的：1）引入和建立一个新的，数据驱动和分析的执法工程计划，旨在同时和主动减少未来犯罪和碰撞的预期数量;和2）开发一个可持续的和可商业化的移动的执法调度系统（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战略提供实际帮助。 被动执法主要基于过去的历史，直觉的元素，甚至一些随机输入（911呼叫）很可能比基于预防和集中数据支持的情报和分析的主动执法成本效益低，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理统计技术的发展，并由于现代地理信息系统技术，现在有可能预测和确定与大量犯罪和碰撞有关的热点。还可以查明某些类型的犯罪和冲突重叠的热点。已知重叠的热点因一天中的时间、一周中的一天和一个月而异，到达热点的最短巡逻路线也会有所不同。拟议的移动的执法调度系统将向实地执法人员的手持设备实时广播重叠的热点和最短的巡逻路线。 科学的执法工程有一个额外的优势。一些公众，包括一些市理事会成员，对现有执法行动的动机表示怀疑，并抱怨貌相或以收入为导向的罚单。如果没有基于科学数据分析的明确理由来确定具体执法的区域，时间和路线，就很难反驳这些广泛的怀疑。拟议的研究将有助于减少怀疑，并预计将增加公众对各种执法战略的支持。 Park博士和他在S大学的研究团队最近与萨斯喀彻温省交通安全管理局萨斯喀彻温省政府保险公司（SGI）合作，为萨斯喀彻温省的各个城市开发了一个基于GIS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改进地面基础设施的潜在地点。拟议的NSERC DG研究将建立在冲突映射系统的基础上，包括犯罪和各种执法策略的映射，并将大大提高SGI和美国在新的和发展中的工程领域称为执法工程的真实的能力。这项研究将增进减少犯罪和交通安全领域的知识，并将大大有助于改善加拿大人的健康以及经济和社会福祉。