## 3 The Framework of CPSS-UPTDN
### Basic Modules in CPSS-UPTDN  
CPSS-UPTDN consists of three modules and two loops. The distributed storage module is responsible for data storage, the interaction of artificial system module and real system module implements parallel control strategies. At the same time, considering the tremendous traffic data, our framework contains a \"Small Loop for real-time status feedback\" and a \"Big Loop for periodical data update\". In the small loop, it can timely obtain the travel needs of users and give feedback in the small loop. For city-wide analysis, under the low requirement for the real-time situation, the big loop can be used to update data periodically, which requires the prediction methods to timely track global changes. **Distributed storage**: The data set can be acquired from triple space, namely cyber, physical and social space. Traffic data from cyberspace includes public traffic information (bus routes, ticketing, bus stations, routes radiation diagram, transportation hubs, and so on), data from governments, etc. Data in physical space contains surveillance cameras, road traffic network information (road, length and charge information, etc. ), and the acquired data for vehicles includes speed, vehicle information, and congestion of roads, etc. Social space data in various forms is mainly from Internet public opinion data and social networks, such as search engines, news portals, Weibo, and cellular signals, from which travel traces can be extracted. The mass data can be logically stored in Hbase which is developed on hadoop distributed file system (HDFS), which can realize the distributed and parallel computing. **Artificial system**: (1) _Data Acquisition System._ The distributed data is calculated by MapReduce. Data verification and preliminary screening are implemented through man-machine interfaces, which realizes data preprocessing and correlation. (2) _Multi-source Data Fusion and Analysis._ This module is responsible for data cleaning and fusing the cross-space data. To facilitate data processing, the redundant data needs to be eliminated concerning task requirements. Then, the fusion process is performed, which consists of  
Figure 1: The proposed urban public traffic dynamic network based on the cyber-physical-social system (CPSS-UPTDN) is mainly composed of three modules and two loops. two steps. One is called feature-level fusion, which is to predict the traffic parameters based on the feature of existing data. The other is state-level fusion, which judges the traffic state according to the current public transportation status information. The basic pipeline of fusion and analysis includes multi-source information extraction, preprocessing, fusion, target parameter acquisition, and state estimation. (3) _Cyber System (CPSS-UPTDN SubPlatform)_. In CPSS, the cyber system can be constructed as a part of the artificial system to connect the physical system (i.e., objects and environment) with the social system (i.e., humans and social factors). Thus, the construction of the sub-platform is the most important module. **Real system**: (1) _Interactive communication_. CPSS-UPTDN has stringent requirements for rapid and reliable dissemination of traffic-related information. The real-time travel demand generated in the real system is fed back to the artificial system, and relevant computational experiments are designed to predict effective schemes for the real system. With the improvement of Vehicular-communication technologies, real-time capability can be improved further. (2) _Traffic status monitor_. The traffic system can be enhanced by mass qualities distributed sensors, such as on-board units, roadside units, cellphones, public opinion, and GPS. With the various sensors, multi-grained data are collected and updated to the distributed storage module periodically. Based on various transportation scenarios with computational experiments, the behaviors of a real urban public transportation system can be monitored and analyzed.