论文标题
循环：检测移动运动传感器的自行车交通中的错过事件
CycleSense: Detecting Near Miss Incidents in Bicycle Traffic from Mobile Motion Sensors
论文作者
论文摘要
在全球城市，汽车会导致健康和交通问题，可以通过增加的自行车份额来部分缓解这些问题。但是，由于缺乏安全性，许多人避免骑自行车。对于城市规划者来说，解决这个问题很难，因为他们缺乏见解，骑自行车的人会感到安全，而他们却没有。为了获得此类见解，我们在以前的工作中提出了众包平台Simra，该平台使骑自行车的人可以记录其乘车并在Intindentsvia Miss Miss a智能手机应用程序附近报告。在本文中，我们介绍了循环，这是信号亲筛和机器学习技术的组合，该技术部分自动检测了近乎错过的事件，从而使婚姻事件的报告更加容易。使用Simra数据集，我们评估了将其与Simra使用的基线方法进行比较，并表明其重要的改善了事件检测。
In cities worldwide, cars cause health and traffic problems whichcould be partly mitigated through an increased modal share of bicycles. Many people, however, avoid cycling due to a lack of perceived safety. For city planners, addressing this is hard as they lack insights intowhere cyclists feel safe and where they do not. To gain such insights,we have in previous work proposed the crowdsourcing platform SimRa,which allows cyclists to record their rides and report near miss incidentsvia a smartphone app. In this paper, we present CycleSense, a combination of signal pro-cessing and Machine Learning techniques, which partially automatesthe detection of near miss incidents, thus making the reporting of nearmiss incidents easier. Using the SimRa data set, we evaluate CycleSenseby comparing it to a baseline method used by SimRa and show that itsignificantly improves incident detection.
