基于IC卡数据的公交下车站点区间不确定性客流推导方法
The method of deriving passenger flow of bus alighting stops based on smart card data and interval uncertainty

在交通大数据背景下，针对现有公交客流推导研究中站点客流皆为固定单一值与实际波动区间值不符的问题，利用区间不确定性理论，以及公交IC卡数据与GPS数据相结合，得到上车站点的公交区间客流。对公交刷卡行为进行分析，考虑乘客个体出行特征和乘客出行距离于站点吸引权重中，得到下车站点客流推导概率模型，结合区间不确定性理论，得到下车站点客流区间值。以深圳市的21路公交IC卡数据和GPS数据为例进行实例分析。通过对推导结果的合理性分析，表明得到的公交区间不确定性客流，更符合实际，算法流程清晰，具有更好的可靠性。
In the context of large traffic data, for the existing passenger traffic OD derivation study passenger flow OD are fixed single value and the actual fluctuation interval value does not match the problem, the use of interval uncertainty theory, bus IC card data and GPS data combined, respectively To carry out on and off the station section of the passenger flow optimization, get off the bus station bus section OD. Integration of bus IC card data and GPS data, the use of interval uncertainty theory to get on the passenger flow interval value. The passenger travel behavior is analyzed, considering the passenger travel characteristics and passenger travel distance in the site to attract the weight, get off the station passenger flow derivation probability model, using interval uncertainty theory, get off the station passenger flow interval value. Taking the IC bus data and GPS data of 21 bus routes in Shenzhen as an example. Through the analysis of the rationality of the results, it shows that the OD of the passenger flow is more realistic, the algorithm is clear and the reliability is better