In the Intelligent Transportation Systems, integration of different components of the classical driver-vehicle-infrastructure system is supported by advances in technology and communications. This study presents a general road safety analysis framework that exploits different types of data on traffic, geometry, and accidents to develop a Road Safety Analysis Center and an on-board Road Safety Driver Advisory. The Road Safety Analysis Center considers different sources of data: accident inventories, road geometry, and floating car data, which reveal drivers' behavior. Floating car data are also exploited to derive mathematically the longitudinal parameters of ancient roads, which are crucial to estimate safety conditions in curves. The critical points of the network are revealed by an aggregate analysis of accidents distribution on the roads, while the drivers' behaviour is addressed on a disaggregated level, by the evaluation of speeds distributions with a dense spatial detail. The comparison between speeds distributions, safety conditions, and accident occurrence is useful to individuate the portions of the network to be enforced with safety measures and support drivers with an advanced onboard speed advisory system. This methodology is applied to several extra-urban roads in the Latium region, Italy, to individuate roads with higher values of critical indices.

中文翻译：

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基于浮动车数据的道路安全速度和驾驶行为的相关性分析

在智能交通系统中，技术和通讯技术的进步为经典驾驶员，车辆，基础设施系统的不同组件的集成提供了支持。这项研究提出了一个通用的道路安全分析框架，该框架利用有关交通，几何形状和事故的不同类型的数据来开发道路安全分析中心和车载道路安全驾驶员咨询服务。道路安全分析中心考虑了不同的数据源：事故清单，道路几何形状和浮动汽车数据，这些数据可以揭示驾驶员的行为。浮动汽车数据也可用于数学计算古代道路的纵向参数，这对于估算弯道的安全状况至关重要。网络的关键点通过对道路事故分布的综合分析来揭示，而驾驶员的行为则通过评估具有密集空间细节的速度分布在分解的层次上得到解决。速度分布，安全状况和事故发生之间的比较对于通过安全措施个性化要实施的网络部分以及使用先进的机载速度咨询系统为驾驶员提供支持非常有用。此方法适用于意大利Latium地区的多条城市外道路，以区分具有较高临界指数值的道路。事故的发生有助于通过安全措施来区分要实施的网络部分，并通过先进的车载速度咨询系统为驾驶员提供支持。此方法适用于意大利Latium地区的多条城市外道路，以区分具有较高临界指数值的道路。事故的发生有助于通过安全措施来区分要实施的网络部分，并通过先进的机载速度咨询系统为驾驶员提供支持。此方法适用于意大利Latium地区的多条城市外道路，以区分具有更高临界指数值的道路。