MobiDriveScore — A system for mobile sensor based driving analysis: A risk assessment model for improving one's driving
MobiDriveScore — A system for mobile sensor based driving analysis: A risk assessment model for improving one's driving
复制标题
DOI：
10.1109/icsenst.2013.6727671
复制
发表时间：
2013-12
期刊：
影响因子：
--
通讯作者：
T. Chakravarty;Avik Ghose;Chirabrata Bhaumik;Arijit Chowdhury
中科院分区：
文献类型：
--
作者：
T. Chakravarty;Avik Ghose;Chirabrata Bhaumik;Arijit Chowdhury
对驾驶行为的评估和其中的风险估计是远程信息处理和车辆网络技术领域的重要用例，这已经在车队管理和消费者垂直领域引起了兴趣，但最重要的是汽车保险公司。这些公司已经开始将这种分析的结果纳入为客户提供“边开车边付费”的保险计划，该计划根据驾驶员过去的撞车和违规历史来决定初始保费。然后，双方进入大约两个月的评估期（例如），评估期结束时，根据加速度计、GPS和车载诊断（OBD II）数据的分析重新计算保费。然而，由于无法访问保险提供商的设备数据，消费者不知道他或她的评估进度。这种评估的一个主要标准是基于驾驶员对高风险操纵的检测和汇总，这些高风险操纵通常包括硬碰撞、急转弯、硬停车和速度限制违规。在本文中，我们提出了一种新的方法，命名为DRIVESCORE的日常企业，使用该消费者可以评估他/她自己的驾驶模式。因此，消费者可以有意识地减少与他/她的驾驶相关的风险。对于XNUMX DriveScore，仅使用加速度计和GPS传感器进行机动检测，这是现代智能手机的组成部分。通过使用DriveScore，用户可以选择替代路线或选择早一点出行，以提高保险费率并保持安全。这也将有助于积极的司机变得更加被动。已经进行了实验，初步结果的ESTA DriveScore被发现是令人鼓舞的。
Assessment of driving behavior and estimation of risk therein is an important use case for telematics and vehicular networking technology domain, which has gained interest in the fleet management and consumer verticals, but above all with the car insurance firms. These firms have started incorporating the results of such analysis to provide their customers with "pay as you drive" insurance plans, which decide the initial premium based on the driver's past history of crashes and violations. Then the parties enter into an evaluation period of about two months (say), at the end of which premium is recalculated based on analysis of accelerometer, GPS and on-board diagnostic (OBD II) data. However, the consumer has no knowledge of the progress of his or her evaluation due to lack of access to device data from insurance provider. One major criterion of such evaluation is based on the detection and aggregation of high-risk maneuvers by the driver, which typically constitutes of hard bump, sharp cornering, hard stop and speed limit violations. In this paper, we propose a novel method named MobiDriveScore for routine ventures using which the consumer can assess his/her own driving pattern. Thus the consumer can consciously reduce the risk associated with his/her driving by using MobiDriveScore. For MobiDriveScore, detection of maneuvers is done using accelerometer and GPS sensors only, which are integral part of modern day smartphones. Using MobiDriveScore, the user can choose an alternate route or choose to travel a little early to improve upon the premium rates and stay safe. It will also help aggressive drivers to become more passive. Experiments have been conducted and the initial results of MobiDriveScore are found to be encouraging.