Affiliations: [a]
Xi’an University of Technology, Xi’an City, Shan Xi Province, China
| [b]
College of Information and Communication, National University of Defense, China
Correspondence:
[*]
Corresponding author. Rong Fei, Xi’an University of Technology, JinHua Road No. 5, Xi’An City, Shan Xi Province, China. E-mail: annyfei@hotmail.com.
Abstract: Using the Semi-Markov decision model, we start with the real road map datum with a constructed logic network and construct the complex road network with random moving characteristics. First we translate the crowdsoured map datum into the vectorgraph in road network by the ArcGIS with the conversion of longitudinal and Latitude Coordinates to planar coordinates. In the motion simulation model all objects are sorted by the time of state change, and the moving object with the closest state change time to the current time are set at the front of the queue. And then, the moving object motion model based crowdsourced map datum is simulated. The experimental results for fitting and analysing the distribution rules of in-degree and out-degree show that the designed model can satisfy the Poission Distribution Rule on the cross node of Road Network based Uniform Distribution of moving object random motion, which conform to the characteristics of Distance Space and small-world network.
Keywords: Semi-markov model, real road map, moving object, distribution rule, motion simulation model
