Lane-change detection

变道检测

• 批准号: 522430-2018
• 负责人: Labbe, Aurélie
• 金额: $ 0.91万
• 依托单位: HEC Montréal
• 依托单位国家: 加拿大
• 项目类别: Engage Plus Grants Program
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=656239
• 关键词: Lane; change; detection

Since the end of 2013, Intact Insurance has offered usage-based insurance programs designed to leverage**data-driven technologies and improve insurance products, by collecting driving data from customers using**either a GPS dongle connected to the vehicle's on-board computer or a smartphone application. In this context,**vehicle position and other sensor data, such as acceleration, wheel rotation, and magnetic azimuth, are recorded**when available. This data is used to characterize driving behavior and, in particular, to detect risky events such**as speeding, harsh breaking, hard acceleration, sharp turns or abrupt lane changes. Along with other contextual**information such as historical risk of a given road, road conditions, other cars' behaviour and speed limits,**these data have the potential to provide better customer segmentation along with risk and cost prediction,**which in turn could help Intact Insurance provide the most competitive pricing to their customers. In order to**build customer-specific road safety indicators and risk factors based on i) where and when the client drives**(contextual information), and ii) how the client drives (driving profile), complex automated procedures must be**developed. The main objective of this research is to tackle issues related to driver's behaviour profiling through**the development and validation of a measure for lane change detection.**Specifically, we propose in this project to investigate how the use of accelerometers and gyroscopes data**collected through the Intact smartphone applications "my Driving Discount" or "automerit" can improve lane**change detection. We also propose to evaluate the minimum data frequency required to achieve a reasonable**detection.

自2013年底以来，完整保险提供了基于使用情况的保险计划，旨在利用**数据驱动的技术，通过使用**连接到车载电脑或智能手机应用程序的GPS加密狗收集客户的驾驶数据，从而改进保险产品。在这种情况下，**车辆位置和其他传感器数据，如加速度、车轮旋转和磁方位角，在可用时被记录**。这些数据被用来描述驾驶行为，特别是检测危险事件，如超速、急刹车、加速、急转弯或突然变道。连同其他背景**信息，如给定道路的历史风险、路况、其他车辆的行为和速度限制，**这些数据有可能提供更好的客户细分以及风险和成本预测，**这反过来可以帮助完整保险为他们的客户提供最具竞争力的定价。为了**根据i)客户驾驶地点和时间**(上下文信息)以及ii)客户如何驾驶(驾驶概况)来**建立特定于客户的道路安全指标和风险因素，必须**开发复杂的自动化程序。这项研究的主要目的是通过**车道变更检测方法的开发和验证来解决与驾驶员行为特征相关的问题。**具体地说，我们在这个项目中建议调查使用加速计和陀螺仪**通过完整的智能手机应用程序“My Driving Discount”或“Automerit”收集的数据**如何改进车道变更检测**。我们还建议评估实现合理**检测所需的最低数据频率。