Transport Systems are equipped with multiple systems that collect large quantities of data every day, every hour, or even every second, at various forms and by different technologies. This means the traffic and transport data in many cases are ‘voluminous’, are generated at a high ‘velocity’, have a high ‘variety’, and have a considerable ‘veracity’. The challenge today is to process this big data to derive meaningful results and insights.\u00a0All modes of a transport network face a form of this challenge, large amounts of trajectory data, count data, and traffic signal control data are generated in the road network, while transit systems (rail, bus, ferry) generate large volumes of data from their automatic fare collection and vehicle location technologies. Shared mobility and combined mobility solutions such as Mobility as a Service (MaaS) or Infrastructure as a Service (IaaS), generate a multi-modal and door-to-door trip and activity information.\u00a0This special issue is calling for papers that address one aspect of this big data challenge whether the data management side or operations and control of an existing system or improving the planning of the transport infrastructure in the future.\u00a0 Some aspects of the data side and the method side are listed below.
\nVarious Data Sources:\u00a0Traffic Sensors for traffic count, occupancy, and speed;\u00a0Automatic data collection technologies, such as Bluetooth, WiFi, GPS, Image Processing, and Video Processing;\u00a0Smart Phone Data including Global Positioning System (GPS) tracks;\u00a0Smart Card Data from public transport Automatic Fare Collection (AFC) Systems;\u00a0Automatic Vehicle Location from trains, buses, bikes, and ferries;\u00a0Traffic Signal Control Systems;\u00a0Autonomous Vehicle and Connected Vehicle Systems.
\nMethodologies:\u00a0Visualization of Big Data Sources;\u00a0Cleaning, Management, and Storage technologies;\u00a0Development of Performance measures, indices, and indicators;\u00a0Data Analytics and Analysis Methods;\u00a0Application of Artificial Intelligence and Machine Learning methods;\u00a0Optimization of Transport Infrastructure;\u00a0Data Fusion and Error handling;\u00a0Network control methods based on the Macroscopic Fundamental Diagram (MFD);\u00a0Control algorithms to improve safety, efficiency, social welfare, and environmental impacts.<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"template":"","format":"standard","topic":[192,555,430,628,308,644,576,597,598,446,625,669,622,571,635,523,459,528,465,467,676,615,469,470,545,567,572,637,616,481,604,681,596,234,606,673,682,674,575,685,683],"country":[55],"nsj_language":[57],"class_list":["post-1329","call_for_papers","type-call_for_papers","status-publish","format-standard","hentry","topic-artificial-intelligence","topic-automation","topic-big-data","topic-clean-technologies","topic-complex-systems","topic-data-analysis-processes","topic-data-management","topic-data-sensing-and-analysis","topic-decision-support-systems","topic-digital-technologies","topic-dynamic-models","topic-enabling-technologies","topic-environmental-impact","topic-environmental-technologies","topic-future-developments","topic-green-infrastructures","topic-green-mobility","topic-human-computer-interface","topic-ict","topic-industry-4-0","topic-infrastructures","topic-innovative-technologies","topic-interdisciplinarity-approach","topic-internet-of-things","topic-machine-learning","topic-methodology","topic-monitoring","topic-networks","topic-performance-evaluation","topic-process-management","topic-process-modeling-and-simulation","topic-remote-sensing","topic-risk-management","topic-robotics","topic-safety-and-security","topic-smart-devices","topic-smart-infrastructure","topic-smart-systems","topic-smart-tools","topic-transport-infrastructures","topic-transports","country-switzerland","nsj_language-english"],"acf":[],"yoast_head":"\n