AI Empowered Communication Systems for Intelligent Transportation Systems

Author(s):  
Zhihan Lv ◽  
Ranran Lou ◽  
Amit Kumar Singh
Author(s):  
Qingyan Yang ◽  
Virginia Sisiopiku ◽  
Jim A. Arnold ◽  
Paul Pisano ◽  
Gary G. Nelson

Rural transportation systems have different features and needs than their urban counterparts. To address safety and efficiency concerns in rural environments, advanced rural transportation systems (ARTS) test and deploy appropriate intelligent transportation systems (ITS) technologies, many of which require communication support. However, wireless communication systems that currently serve urban areas often are not available or suitable in rural environments. Thus, a need exists to identify communication solutions that are likely to address successfully the needs and features of ARTS applications. Current and emerging wireless communications systems and technologies have been systematically assessed with respect to rural ITS applications. Wireless communication functions associated with rural ITS functions are first identified. Then requirements for applicable communication technologies in the rural environment are defined. Existing and emerging wireless communication systems and technologies are reviewed and evaluated by a systematic process of assessing rural ITS wireless solutions. Finally, recommendations for future research and operational tests are offered. The analysis results are expected to benefit rural ITS planners by identifying suitable wireless solutions for different rural contexts.


2020 ◽  
Vol 12 (19) ◽  
pp. 8070
Author(s):  
Jiawei Gui ◽  
Qunqi Wu

The transportation utility values calculated by traditional utility methods are not comprehensive. Some objects and factors are ignored in traditional utility methods, and this narrow perspective is their primary drawback. In intelligent transportation systems, it is necessary to calculate transportation utility for promoting public traffic planning and management. To build a sustainable intelligent transportation system, modified utility methods are essential to analyze transportation utility in a comprehensive way with innovative technologies and efficient communication systems. To solve the disadvantages of traditional utility methods, it is necessary to establish a new method to build sustainable public transport in the future. In this study, the Multiple Utility Method and Transportation Utility Method are proposed for public transport planning and management from multiple perspectives. A sample is presented to provide a better description, and 69,174 GPS-equipped taxi data in Haikou are adopted for the application of the Transportation Utility Method. The results show that the transportation utility values calculated by the Transportation Utility Method are more comprehensive than the transportation utility calculated by traditional utility methods. This indicates that it is necessary to calculate transportation utility from multiple perspectives based on the Transportation Utility Method. Future directions could include improving the methods, considering more factors, expanding the data used, and extrapolating this research to other cities around the world with similar urban metrics and urban form.


2020 ◽  
Vol 19 (11) ◽  
pp. 2116-2135
Author(s):  
G.V. Savin

Subject. The article considers functioning and development of process flows of transportation and logistics system of a smart city. Objectives. The study identifies factors and dependencies of the quality of human life on the organization and management of stream processes. Methods. I perform a comparative analysis of previous studies, taking into account the uniquely designed results, and the econometric analysis. Results. The study builds multiple regression models that are associated with stream processes, highlights interdependent indicators of temporary traffic and pollution that affect the indicator of life quality. However, the identified congestion indicator enables to predict the time spent in traffic jams per year for all participants of stream processes. Conclusions. The introduction of modern intelligent transportation systems as a component of the transportation and logistics system of a smart city does not fully solve the problems of congestion in cities at the current rate of urbanization and motorization. A viable solution is to develop cooperative and autonomous intelligent transportation systems based on the logistics approach. This will ensure control over congestion, the reduction of which will contribute to improving the life quality of people in urban areas.


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