Sustainable road safety engineering research program: community-based, macro-level collision prediction models

道路碰撞造成的巨大经济和社会负担被认为是一个全球性的流行病问题。可持续发展与道路安全规划联系在一起，因为道路安全问题的根本原因在于建立的社区形式助长了对驾驶的过度依赖。传统的道路安全工程依赖于反应性方法，这种方法致力于改善道路安全，以应对已确定的危险道路位置。然而，只有在存在碰撞历史之后，才能确定一个地点是危险的，道路安全问题才能得到解决，这通常是在多年的碰撞之后，而且在已建成的社区中成本很高。为了将道路碰撞的发生率和严重程度降低到当前不可接受的高水平以下，研究人员正在寻求更积极的方法，在社区规划阶段明确考虑道路安全，在已建成道路出现问题之前。然而，缺乏可靠的、以实证科学为基础的道路安全规划工具，来对土地利用和交通规划采取这种积极主动的方法。宏观碰撞预测模型的发展有可能解决这一知识鸿沟。然而，它们的开发过程复杂、数据密集、耗时，需要广泛的交通、地理空间、统计和回归建模过程的知识和使用。需要进行研究，以完善、自动化并促进从业者对其开发和使用，从而提高主动工程方法的有效性，以规划和改善道路安全。可持续道路安全工程研究计划将通过以下目标提供以科学为基础的研究，以解决这一知识差距：1)开发宏观层面的碰撞预测模型，以促进可持续发展和道路安全规划；2)开发数据提取和开发的自动化流程，促进这些模型的质量和使用的一致性；以及3)促进土地使用和交通规划者和工程师向这些新的经验工具转移并广泛使用这些新的经验工具，以减轻道路碰撞给社会带来的负担。

The enormity of the economic and social burden of injuries due to road collisions has been cited as a global problem of epidemic proportions. Sustainable development is linked with road safety planning because the root cause of the road safety problem lies in a built community form that nurtures over dependence on driving. Traditional road safety engineering has relied on a reactive approach, which works to improve road safety in reaction to identified hazardous road locations. However, only after a collision history exists can a location be identified as hazardous and the road safety problem fixed, often after years of collisions and at high cost in built communities. To reduce the incidence and severity of road collisions below unacceptably high current levels, researchers are pursuing more proactive methods, to explicitly consider road safety at the community planning stage, before problems occur on built roads. However, there is a lack of reliable empirical science-based road safety planning tools to conduct this proactive approach to land use and transportation planning. The development of macro-level collision prediction models has the potential to address this knowledge gap. However, their development process is complex, data intensive, and time consuming, and requires extensive knowledge and use of transportation, geo-spatial, statistical, and regression modelling processes. Research is needed to refine, automate, and facilitate their development and use by practitioners, and thereby increase the effectiveness of the proactive engineering approach to road safety planning and improvement. The Sustainable Road Safety Engineering Research Program will provide science-based research to address this knowledge gap, via the following objectives: 1) Develop macro-level collision prediction models that facilitate sustainable development and road safety planning; 2) Develop automated processes for data extraction and development of these models that facilitate consistency in their quality and use; and, 3) Promote the transfer to and widespread use of these new empirical tools by land use and transportation planners and engineers, to remove the burden imposed by road collisions on society.