Building Urban Public Traffic Dynamic Network Based on CPSS: An Integrated Approach of Big Data and AI

Gang Xiong,Zhishuai Li,Huaiyu Wu,Yisheng Lv,Shichao Chen,Fenghua Zhu,Xisong Dong

doi:10.3390/app11031109

Abstract

The extensive proliferation of urban transit cards and smartphones has witnessed the feasibility of the collection of citywide travel behaviors and the estimation of traffic status in real-time. In this paper, an urban public traffic dynamic network based on the cyber-physical-social system (CPSS-UPTDN) is proposed as a universal framework for advanced public transportation systems, which can optimize the urban public transportation based on big data and AI methods. Firstly, we introduce three modules and two loops which composes of the novel framework. Then, the key technologies in CPSS-UPTDN are studied, especially collecting and analyzing traffic information by big data and AI methods, and a particular implementation of CPSS-UPTDN is discussed, namely the artificial system, computational experiments, and parallel execution (ACP) method. Finally, a case study is performed. The data sources include both traffic congestion data from physical space and cellular data from social space, which can improve the prediction performance for traffic status. Furthermore, the service quality of urban public transportation can be promoted by optimizing the bus dispatching based on the parallel execution in our framework.

Highlights

Urban public transportation is the main means to meet the increasing travel demand of metropolitan and alleviate traffic jams [1]
artificial intelligence (AI) methods are used to collect data related to urban transportation, traffic information elements are extracted, and semantic analysis of these data is conducted with the help of natural language processing and other models
The urban public transportation system is not aimed at a single user, but a group of people

Summary

Introduction

Urban public transportation is the main means to meet the increasing travel demand of metropolitan and alleviate traffic jams [1]. The sharing rate of public transportation is increasing inconspicuously. There are still many problems in urban public transportation, such as insufficient transparency and sharing among traffic information, and inconvenient transition among different public transport means, which makes citizens unwilling to travel with public transportation. Advanced public transportation systems (APTS) is an important component of intelligent transportation systems (ITS). Cutting-edge technologies of information and communication are applied for APTS to coordinate commands and control vehicles. With the popularity of intelligent terminals, massive data becomes accessible and is analyzed by artificial intelligence (AI), greatly enriching APTS.

Methods

Results

Conclusion