Towards the applications of multi-agent techniques in intelligent transportation systems

2004 ◽  
Author(s):  
Zhang Jin ◽  
Wang Hui ◽  
Li Ping
Keyword(s):  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Multi Agent

An Intelligent Transportation Systems Model Based on Multi-Agent Technology

2014 ◽  
Vol 484-485 ◽  
pp. 1101-1105
Author(s):  
Jing Ya Chen
Keyword(s):  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Control Agent ◽  
Transportation Systems ◽  
Agent Technology ◽  
Loosely Coupled ◽  
Systems Model ◽  
Multi Agent

Intelligent transportation system based on multi-agent, become a important method, also is to solve the complex traffic problems. In the geography of the property of the agent in the heterogeneous environment cause implementation difficulties such as interoperability requirements, make the agent of unity between software platforms as a potential infrastructure. This paper puts forward a model and the more intelligent transportation system based on SOA. The model includes four major parts: infrastructure, services, agency, and coordination agent. Elements The model of the agent into different levels and groups, including organization agent, regional control agent, agent, road section road intersection vehicle control agent, the acting to complete different function and goal. Based on the SOA multi-agent technology, can realize the cross-platform loosely coupled, and interoperability and heritage reuse in distributed and heterogeneous network traffic system.

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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