Analysis on Improved Dijkstra Algorithm in Intelligent Transportation System

2013 ◽  
Vol 385-386 ◽  
pp. 877-881
Author(s):  
Hao Yu Wang ◽  
Chao Jun Ji ◽  
Xiao Juan Ji
Keyword(s):  
Real Time ◽  
Shortest Path ◽  
Traffic Congestion ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Dijkstra Algorithm ◽  
Key Technology ◽  
The Core ◽  
The City

Intelligent transportation system (ITS) is a complicated system, and selecting the shortest path is the core of the system. In order to ease traffic congestion of the city, through solving the shortest path, the key technology in realizing the function of ITS, and based on the analysis of traditional Dijkstra algorithm, the paper puts forward the improved algorithm. The new algorithm includes two parts, that is, preprocessing and real-time pruning research, and the effect of pruning totally depends on the division of specific diagram.

Shortest Path Optimization Algorithm in Intelligent Transportation System

2013 ◽  
Vol 325-326 ◽  
pp. 1778-1782
Author(s):  
Hao Yu Wang ◽  
Yi Zheng ◽  
Xiao Juan Ji
Keyword(s):  
Shortest Path ◽  
Optimization Algorithm ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Urban Traffic ◽  
Algorithm Analysis ◽  
Dijkstra Algorithm ◽  
Key Technology ◽  
Smooth Flow

To ensure the smooth flow of urban traffic, through analysis of shortest path solution, the key technology to the realization of intelligent transportation system, and on the basis of traditional Dijkstra algorithm analysis, a new optimization algorithm is put forward.

scholarly journals Novel Routing Algorithm for Autonomous Vehicles in Smart Transportation System

2021 ◽  
Vol 3 (3) ◽  
pp. 164-179
Author(s):  
Haoxiang Wang
Keyword(s):  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Intelligent Transportation System ◽  
Autonomous Vehicle ◽  
Routing Algorithm ◽  
Transportation System ◽  
Traffic Condition ◽  
Smart Transportation ◽  
Centralized Management ◽  
The City

In recent times Automation is emerging every day and bloomed in every sector. Intelligent Transportation System (ITS) is one of the important branches of Automation. The major constrain in the transportation system is traffic congestion. This slurps the individual’s time and consequently pollutes the environment. A centralized management is required for optimizing the transportation system. The current traffic condition is predicted by evaluating the historical data and thereby it reduces the traffic congestion. The periodic update of traffic condition in each and every street of the city is obtained and the data is transferred to the autonomous vehicle. These data are obtained from the simulation results of transportation prediction tool SUMO. It is proved that our proposed work reduces the traffic congestion and maintains ease traffic flow and preserves the fleet management.

Study on Path Optimization Method of Traffic Guidance System under the Condition of the Car Networking

2014 ◽  
Vol 624 ◽  
pp. 567-570
Author(s):  
Dan Ping Wang ◽  
Kun Yuan Hu
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
System Integration ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Guidance System ◽  
Wide Range ◽  
Computer Communication Network

Intelligent Transportation System is the primary means of solving the city traffic problem. The information technology, the communication, the electronic control technology and the system integration technology and so on applies effectively in the transportation system by researching rationale model, thus establishes real-time, accurate, the highly effective traffic management system plays the role in the wide range. Traffic flow guidance system is one of cores of Intelligent Transportation Systems. It is based on modern technologies, such as computer, communication network, and so on. Supplying the most superior travel way and the real-time transportation information according to the beginning and ending point of the journey. The journey can promptly understand in the transportation status of road network according to the guidance system, then choosing the best route to reach destination.

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