Improving safety of urban roads through speed management

超速驾驶是道路安全的主要障碍之一。管理速度需要交通机构和工程师在设计和运营阶段做出复杂的决策;然而，对这些决策的全面支持仍然缺乏，特别是在与城市道路有关的问题上。结果是加拿大与速度有关的事故越来越多。该研究计划为城市速度管理问题提出了一个整体解决方案。该研究计划的主要组成部分将开发一个基于知识的专家系统，用于选择最佳的速度管理对策或处理方法，以解决特定的超速问题。该系统将联合收割机的驾驶员行为，道路几何信息，以及其他有关速度和安全问题的信息在知识库中，以确定潜在的速度管理对策。为了支持这一发展，拟议的研究计划将首先调查城市街道设计和路边环境对速度和与速度有关的事故的影响。这些信息将成为预测城市道路速度的新算法的基础。这些组件不仅将增强专家系统的知识库，而且还对解决设计阶段的速度管理问题做出了重要贡献。这种积极主动的方法有助于驾驶员自然地降低车速，而不是仅仅通过对策和执法。除了该计划的培训和教育贡献，这有利于加拿大对高素质交通工程师和规划师的日益迫切的需求，拟议的研究计划的专家系统和速度预测算法代表了支持建立更强大的速度管理最佳实践的宝贵和原始的发展。这些不仅将弥合该领域从业者存在的关键差距，还为推进这一不发达但至关重要的交通研究领域提供了坚实的基础和资源。

Excessive driving speed is one of the major obstacles to road safety. Managing speed requires complex decision-making on the part of transportation agencies and engineers at both the design and operational stages; however, comprehensive support for these decisions is still lacking, particularly for issues relating to urban roadways. The result has been an increasing number of speed-related accidents in Canada. This research program proposes a holistic solution to the issue of urban speed management. The major component of this research program will develop a knowledge-based expert system for selecting optimal speed management countermeasures or treatments to address specific speeding problems. The system will combine information on driver behaviours, road geometry, and other information related to speed and safety issues in a knowledge base to identify potential speed management countermeasures. In support of this development, the proposed research program will first investigate the effects of urban street design and the roadside environment on speeds and speeding-related accidents. This information will then form the basis of a novel algorithm to predict speed on urban roads. These components will not only enhance the knowledge base of the expert system, but also make an important contribution to the problem of addressing speed management during the design phase. This proactive approach helps drivers to reduce their speeds naturally, rather than through countermeasures and enforcement alone. In addition to the training and education contributions of this program, which benefit Canada's increasingly urgent need for highly qualified transportation engineers and planners, the proposed research program's expert system and speed prediction algorithm represent valuable and original developments for supporting the establishment of more robust speed management best practices. Not only will these bridge a critical gap that exists for practitioners in the field, they provide a strong foundation and resource for advancing this underdeveloped, yet crucial, area of transportation research.