CAJ | 학술논문

对于大规模出行轨迹数据进行出行方式研究时，除了要对行程中OD(起点-终点)进行提取，还要对其间交通方式进行判别。然而，一段行程中，往往包含多种交通方式，如何更精细地从中提取多种交通方式，提升最终交通规划效果，是目前出行方式研究的关键问题。在使用移动智能终端采集出行轨迹的基础上，对出行轨迹进行不同交通方式的转换点提取，最终提出了演绎性时序聚类分割算法进行出行轨迹的分段，并对其进行实验验证。结果表明算法对于分割不同交通方式段，达到了很高的精度。
대우대규모출행궤적수거진행출행방식연구시，제료요대행정중OD(기점-종점)진행제취，환요대기간교통방식진행판별。연이，일단행정중，왕왕포함다충교통방식，여하경정세지종중제취다충교통방식，제승최종교통규화효과，시목전출행방식연구적관건문제。재사용이동지능종단채집출행궤적적기출상，대출행궤적진행불동교통방식적전환점제취，최종제출료연역성시서취류분할산법진행출행궤적적분단，병대기진행실험험증。결과표명산법대우분할불동교통방식단，체도료흔고적정도。
When studying transportation mode with large-scale travel trajectory data,need to not only extract the origin and destination model from the trip,but also determine the transportation mode. However,a journey often contains a variety of transportation modes. How to extract the travel patterns and enhance the effect of the final transportation planning is the key problem of transportation research. Based on mobile intelligent terminal to collect travel paths and the point of the travel path of different transportation mode,put forward the apri-ority sequential clustering segmentation algorithm for segmentation of the travel path. The method is verified by experiment. Results show that the algorithm for separating different transportation period is of very high accuracy.