Analysis of the Development Environment of Urban Intelligent Transportation Systems

2012 ◽  
Vol 598 ◽  
pp. 189-192
Author(s):  
Li Li Qiao ◽  
Wei Wang ◽  
Jian Zhang ◽  
Yong Kai Hu ◽  
Hai Yan Gu ◽  
...  
Keyword(s):  
Information Technology ◽  
Intelligent Transportation Systems ◽  
Local Governments ◽  
Industrial Development ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Development Environment

Researching the development environment (DE) of urban intelligent transportation systems (UITS) can help achieve their healthy and orderly development. This article is based on the development demands of the UITS and gives a summary of the development opportunities and challenges. The analysis shows that the UITS possesses a favorable DE. National and local governments establish a range of policies to promote its development. The existing information facilities and information technology provide powerful support. However, UITS also faces a series of challenges, including management mechanisms, industrial development, availability of capital, and standards.

Quality indicator of the smart city transportation and logistics system

2020 ◽  
Vol 19 (11) ◽  
pp. 2116-2135
Author(s):  
G.V. Savin
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart City ◽  
Urban Areas ◽  
Human Life ◽  
Life Quality ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Logistics System ◽  
Organization And Management

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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