He Zongjian, Cao Jiannong, Liu Xuefeng, Tang Shaojie
Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China.
Department of Computer and Information Science, Temple University, Philadelphia, PA 19122, USA.
Sensors (Basel). 2014 Jun 30;14(7):11605-28. doi: 10.3390/s140711605.
Seat-level positioning of a smartphone in a vehicle can provide a fine-grained context for many interesting in-vehicle applications, including driver distraction prevention, driving behavior estimation, in-vehicle services customization, etc. However, most of the existing work on in-vehicle positioning relies on special infrastructures, such as the stereo, cigarette lighter adapter or OBD (on-board diagnostic) adapter. In this work, we propose iLoc, an infrastructure-free, in-vehicle, cooperative positioning system via smartphones. iLoc does not require any extra devices and uses only embedded sensors in smartphones to determine the phones' seat-level locations in a car. In iLoc, in-vehicle smartphones automatically collect data during certain kinds of events and cooperatively determine the relative left/right and front/back locations. In addition, iLoc is tolerant to noisy data and possible sensor errors. We evaluate the performance of iLoc using experiments conducted in real driving scenarios. Results show that the positioning accuracy can reach 90% in the majority of cases and around 70% even in the worst-cases.
智能手机在车辆中的座椅高度定位可为许多有趣的车内应用提供细粒度的上下文信息，包括预防驾驶员分心、估计驾驶行为、定制车内服务等。然而，现有的大多数车内定位工作都依赖于特殊的基础设施，如立体声音响、点烟器适配器或车载诊断（OBD）适配器。在这项工作中，我们提出了iLoc，一种通过智能手机实现的无基础设施的车内协同定位系统。iLoc不需要任何额外的设备，仅使用智能手机中的嵌入式传感器来确定手机在汽车中的座椅高度位置。在iLoc中，车内智能手机在特定类型的事件期间自动收集数据，并协同确定相对的左右和前后位置。此外，iLoc能够容忍噪声数据和可能的传感器误差。我们通过在实际驾驶场景中进行的实验来评估iLoc的性能。结果表明，在大多数情况下，定位精度可达90%，即使在最坏的情况下也能达到约70%。
