Back to Top

■ Visual Analytics of Mobility and Transportation: State of the Art and Further Research Directions

Gennady Andrienko, Natalia Andrienko, Wei Chen, Ross Maciejewski, and Ye Zhao, "Visual Analytics of Mobility and Transportation: State of the Art and Further Research Directions", IEEE Transactions on Intelligent Transportation Systems, 2017, vol. 18(8), pp.2232-2249
Paper [AAC+17] surveys the state of the art in visual analytics methods developed for mobility analysis and transportation applications and outlines directions for further research and applications. This paper served a general framework for visual analytics research and development in VaVeL.
Many cities and countries are now striving to create intelligent transportation systems that utilize the current abundance of multisource and multiform data related to the functionality and use of transportation infrastructure to better support human mobility, interests, and lifestyles. Such intelligent transportation systems aim to provide novel services that can enable transportation consumers and managers to be better informed and make safer and more efficient use of the infrastructure. However, the transportation domain is characterized by both complex data and complex problems, which calls for visual analytics approaches. The science of visual analytics is continuing to develop principles, methods, and tools to enable synergistic work between humans and computers through interactive visual interfaces. Such interfaces support the unique capabilities of humans (such as the flexible application of prior knowledge and experiences, creative thinking, and insight) and couple these abilities with machines’ computational strengths, enabling the generation of new knowledge from large and complex data. To date, visualization and visual analytics has played a critical role in enabling domain experts to synthesize, explore and understand their data. In this paper, we describe recent developments in visual analytics that are related to transportation systems and discuss how visual analytics can enable and improve the intelligent transportation systems of the future.