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A Heuristic-Based Population Synthesis Method for Micro-Simulation in Transportation
Chengxiang Zhuge,Xia Li,Chia-An Ku,Jian Gao,Hui Zhang 대한토목학회 2017 KSCE Journal of Civil Engineering Vol.21 No.6
Population synthesis is extensively required by a number of micro-simulation models in transportation. A heuristic-based population synthesis method called Pop-H was proposed to overcome the following two limitations that received less attention. The first limitation is that one target marginal distribution can be well met by various sets of household weights that can be used to generate different sets of population and thus it is a problem that which set of household weights is the real one. Secondly, the population synthesis is commonly viewed as an optimization problem, and minimizing the Mean Absolute Percentage Error of control variables is generally used as the objective function. The Standard Deviation of control variables is also crucial in some cases, which, however receives scant attention. In response to these two limitations, the heuristic-based population synthesis method works in the following way: the Pop-H algorithm starts with the initial set of household weights derived from a sample data and calculates the final set of household weights by iteratively adjusting the initial set in a defined way with the objective function taking into account both Mean Absolute Percentage Error and Standard Deviation of control variables. Finally, the medium-sized city of Baoding, China was used as the case study. The sensitivity test was firstly done to examine four key parameters of the Pop-H algorithm, and then the algorithm was applied to create the population for the whole city.
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Detecting Taxi Travel Patterns using GPS Trajectory Data: A Case Study of Beijing
Hui Zhang,Baiying Shi,Chengxiang Zhuge,Wei Wang 대한토목학회 2019 KSCE JOURNAL OF CIVIL ENGINEERING Vol.23 No.4
GPS trajectory is a valuable source to understand the operational status of taxicabs and identify the traffic demand and congestions. This study attempts to use 24-hour taxi trajectory data to investigate the attributes of taxicabs such as the distance of occupied distance, number of active taxicabs in different hours, average trip speed in different hour, coverage area of a taxicab, average radius of a taxicab, occupied rate and service times. The results show that the highest speed of taxicabs occur in the 3:00 am when there is the smallest number of active taxicabs running on the road. Moreover, the average occupied rate is 0.59 and the average service times are 19.8 in a day. Finally, a latent class analysis model is used to make the segment of taxicabs by their attributes. Four operational patterns have been found including ‘downtown preference type’, ‘long-distance preference type’, ‘suburbs preference type’ and ‘free preference type’. This study can shed light on understanding the operational status of taxicabs and gives suggestions for operators and passengers for better managing and using taxicabs.
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