环路图
宏
人气
系统动力学
运输工程
毒物控制
风险分析(工程)
政策分析
宏观层面
计算机科学
工程类
业务
经济
医学
心理学
社会心理学
经济体制
环境卫生
人工智能
法学
政治学
程序设计语言
作者
Yihan Goh,Peter E.D. Love
出处
期刊:Safety Science
[Elsevier]
日期:2012-08-01
卷期号:50 (7): 1594-1605
被引量:62
标识
DOI:10.1016/j.ssci.2012.03.002
摘要
System dynamics (SDs) is a methodology that can be used to understand the behavior and dynamics of complex systems over time. SD utilizes a range of tools and techniques such as influence and causal loop diagrams, computer simulation and optimization. SD has been used to facilitate the analysis of complex physical and social systems, e.g. water resources, climate change and industrial accidents. One of the key reasons for its growing popularity is that it allows policy experimentation and facilitates the discussion of ‘what-if’ scenarios. Within the realm of road traffic research, SD has been primarily used to examine micro level issues such as the interactions between the driver, infrastructure and the vehicle. Even though such micro level analysis are important, macro traffic safety policies can create more sustainable systems that pre-empt safety issues and reduce likelihood of traffic accidents. This paper develops two models to demonstrate how the methodology of SD can facilitate and encourage macro and meso level analysis of traffic safety policy. The first model is used to assess policy options so as to encourage the purchase of cars with higher safety ratings. The second model, is used to evaluate the impact of public transport policies on travel time and traffic safety considerations. The strength and weaknesses of the SD methodology in road transport/safety analysis are also examined. It is suggested that SD is most appropriate for formulating macro level policy as it can account for the dynamic complexity associated with the road transport system.
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