论文标题
Simra：使用众包来识别自行车交通中热点小姐附近
SimRa: Using Crowdsourcing to Identify Near Miss Hotspots in Bicycle Traffic
论文作者
论文摘要
自行车流量的模态份额增加是减少排放并解决与交通相关问题的关键机制。但是，缺乏（感知的）安全性会使人们无法更频繁地使用自行车。为了提高自行车交通的安全性，城市规划人员需要概述事故，接近事件和自行车路线。但是，此类信息目前尚不可用。在本文中，我们描述了Simra，这是一个平台，用于使用基于智能手机的众包收集自行车路线的数据以及几乎没有事件。我们还描述了如何根据收集的数据来识别近距离热点附近的危险，并提出了一个评分模型。
An increased modal share of bicycle traffic is a key mechanism to reduce emissions and solve traffic-related problems. However, a lack of (perceived) safety keeps people from using their bikes more frequently. To improve safety in bicycle traffic, city planners need an overview of accidents, near miss incidents, and bike routes. Such information, however, is currently not available. In this paper, we describe SimRa, a platform for collecting data on bicycle routes and near miss incidents using smartphone-based crowdsourcing. We also describe how we identify dangerous near miss hotspots based on the collected data and propose a scoring model.
