基于手机传感器的车辆轨迹实时在线压缩方法

随着具有定位功能的各类便携式移动设备的普及,产生了大量的移动目标时空轨迹数据,庞大的数据规模对轨迹数据管理和分析带来了严峻的挑战.?车辆时空轨迹数据压缩算法,通过监测分析车辆在不同运动行为模式下智能手机内置线性加速度传感器和方向传感器的数据变化规律,识别车辆的转向行为和变速行为,并根据识别结果请求GPS传感器定位,记录...

Real-time Online Compression Method for Vehicle Trajectory Data Based on Smart Phone Sensors

Popularization of various portable mobile devices with positioning function produces massive spatial-temporal trajectory data of moving objects, and the huge data scale has brought severe challenges to trajectory data management and analysis. Therefore, a spatial-temporal trajectory data compression algorithm based on smart phone sensors is proposed. The algorithm recognizes the turning behavior and speed change behavior of the vehicle by monitoring and analyzing the data change law of the linear acceleration sensor and direction sensor built in the smartphone, and requests GPS sensor positioning to record the corresponding trajectory feature points according to the pattern recognition result, so as to realize real-time online compression of vehicle trajectory. The proposed algorithm is compared with the representative trajectory compression algorithms characterized by feature point extraction. The results indicate that it is slightly weaker than the representative trajectory compression algorithms in compression accuracy, its spatial-temporal distance deviation is 0.4 meters more than that of the online NOPW (normalopening?window) algorithm on average, and its spatial distance deviation is 0.6 meters more that of the online NOPW algorithm on average. The real-time performance of the proposed algorithm is strong, and the feature points can be obtained in the current second, the calculation efficiency of the proposed algorithm is high, and the calculation time consumption is reduced by about 30% compared with the DP (douglas-peucker) algorithm, which reduces the amount of network transmission data; It only requests positioning and sampling at key feature points, the compression results is able to adapt to changes in road conditions to some extent, thus it reduces the storage space of the mobile phone, and decreases the power consumption of the mobile phone.