Prediction of Deceleration Amount of Vehicle Speed in Snowy Urban Roads Using Weather Information and Traffic Data
Prediction of Deceleration Amount of Vehicle Speed in Snowy Urban Roads Using Weather Information and Traffic Data
复制标题
DOI：
10.1109/itsc.2015.366
复制
发表时间：
2015-09
期刊：
影响因子：
--
通讯作者：
Ryosuke Tanimura;Akihito Hiromori;T. Umedu;Hirozumi Yamaguchi;T. Higashino
中科院分区：
文献类型：
--
作者：
Ryosuke Tanimura;Akihito Hiromori;T. Umedu;Hirozumi Yamaguchi;T. Higashino
在多雪的国家，大雪对交通流量有很大的影响。城市道路积雪严重影响车辆行驶，道路两侧积雪堆积严重，影响车辆正常行驶。在本文中，我们提出了一种新的方法来预测车辆的速度在每个路段在雪城。该估算有助于地方政府的城市交通规划或居民的出行规划。我们收集前一天的最高温度、日照时数、积雪深度、降雪量、当前新降雪量等天气信息，以及夏季平均车速、前一天车速等通过浮动车数据获得的各路段的车辆交通数据。我们已经建立了一个速度模型的车辆在积雪条件下的每个路段作为这些因素的线性组合。然后，我们列举了可能会有一定的影响，在雪地条件下的车辆速度的多个因素，并得出了它们的权重，通过多元回归分析。我们已经将所提出的方法应用于主要路段在日本札幌市，并推导出多元回归函数使用真实的天气信息和车辆交通数据。我们已经表明，我们提出的模型可以预测七天的速度减速，误差很小。
In snowy countries, heavy snow has a large influence on traffic flows. Snow on urban roads disturbs traveling of vehicles as a huge amount of snow is piled up on roadsides, which often obstructs smooth driving. In this paper, we propose a novel method to predict the speed of vehicles on each road segment in snowy cities. This estimation is helpful for urban traffic planning of local government or trip planning of residents. We collect weather information such as the highest temperature, daylight hours, snow depth and snowfall of the previous day and current new snowfall and vehicular traffic data of each road segment obtained from floating car data such as the average speed in summer and the speed of the previous day. We have built a speed model of vehicles for each road segment in snowy conditions as a linear combination of those factors. Then we enumerate multiple factors which might have some influence on vehicle speed in snowy conditions and have derived their weights by using multiple regression analysis. We have applied the proposed method to major road segments in Sapporo City, Japan and derived multiple regression functions using real weather information and vehicular traffic data. We have shown that our proposed model can predict the speed deceleration for seven days with small errors.