关于利用交通风险数据进行汽车导航的黑客马拉松的报告

S. Ito, K. Zettsu
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引用次数: 4

摘要

汽车驾驶员根据获得的关于沿途事故和交通拥堵的信息来选择他们的路线。近年来,利用各种传感器数据对各种交通风险事件进行临近预报和预测。然而,目前还不清楚如果路线上有交通风险,该如何与司机沟通。在本文中,我们开发了一个环境,使非UI专家能够通过使用交通风险数据快速创建汽车导航原型。这篇论文包含了我们关于使用这个环境举办的黑客马拉松的报告。黑客马拉松的主题是“开发一种新的汽车导航系统,该系统配备了一种机制,可以让驾驶员意识到交通风险,并帮助他们确定最合适的驾驶路线。”来自交通工程领域的23名研究人员和专业人士参加了会议。我们的研究结果给专家们带来了一些共同的问题。从这份报告中获得的信息将非常有利于我们社区确定合作方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Report on a Hackathon for Car Navigation Using Traffic Risk Data
Car drivers select their routes based on the information obtained about accidents and traffic congestion along the route. In recent years, nowcasting and forecasting of various traffic risk events is being performed by using diverse sensor data. However, there is no clarity as yet on what and how to communicate to the driver in case there are traffic risks on the route. In this paper, we have developed an environment that enables non UI experts to quickly create car navigation prototypes by using traffic risk data. This paper includes our report on a hackathon that we held using this environment. The hackathon theme was "Develop a new car navigation system equipped with a mechanism that makes the driver aware of traffic risks and helps them determine the most appropriate driving routes." Twenty three researchers and professionals from the field of traffic engineering participated. Our results have brought certain common problems to the awareness of the experts. The information obtained from this report will be very beneficial for our community to determine the direction of collaboration.
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