scholarly journals Application of Angle Related Cost Function Optimization for Dynamic Path Planning Algorithm

Algorithms ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 127 ◽  
Author(s):  
Mingbin Zeng ◽  
Xu Yang ◽  
Mengxing Wang ◽  
Bangjiang Xu
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Intelligent Transportation Systems ◽  
Optimal Solution ◽  
Transportation Systems ◽  
Function Optimization ◽  
Dynamic Path Planning ◽  
Planning Algorithm ◽  
Dynamic Path ◽  
Path Planning Algorithm

In recent years, Intelligent Transportation Systems (ITS) have developed a lot. More and more sensors and communication technologies (e.g., cloud computing) are being integrated into cars, which opens up a new design space for vehicular-based applications. In this paper, we present the Spatial Optimized Dynamic Path Planning algorithm. Our contributions are, firstly, to enhance the effective of loading mechanism for road maps by dividing the connected sub-net, and building a spatial index; and secondly, to enhance the effect of the dynamic path planning by optimizing the search direction. We use the real road network and real-time traffic flow data of Karamay city to simulate the effect of our algorithm. Experiments show that our Spatial Optimized Dynamic Path Planning algorithm can significantly reduce the time complexity, and is better suited for use as a real-time navigation system. The algorithm can achieve superior real-time performance and obtain the optimal solution in dynamic path planning.

Dynamic Path Planning Algorithm Based on Chaos Genetic Vehicle Navigation

2011 ◽  
Vol 142 ◽  
pp. 12-15
Author(s):  
Ping Feng
Keyword(s):  
Path Planning ◽  
Search Algorithm ◽  
Traffic Condition ◽  
Planning Time ◽  
Dynamic Path Planning ◽  
Short Period ◽  
Planning Algorithm ◽  
Dynamic Path ◽  
Path Planning Algorithm ◽  
Chaos Genetic Algorithm

The paper puts forward the dynamic path planning algorithm based on improving chaos genetic algorithm by using genetic algorithms and chaos search algorithm. In the practice of navigation, the algorithm can compute at the best path to meet the needs of the navigation in such a short period of planning time. Furthermore,this algorithm can replan a optimum path of the rest paths after the traffic condition in the sudden.

Adaptive Dynamic Path Planning Algorithm for Interception of a Moving Target

2013 ◽  
Vol 5 (3) ◽  
pp. 19-33
Author(s):  
H. H. Triharminto ◽  
A.S. Prabuwono ◽  
T. B. Adji ◽  
N. A. Setiawan
Keyword(s):  
Path Planning ◽  
Dynamic Condition ◽  
Cylindrical Shape ◽  
Moving Target ◽  
C Language ◽  
Dynamic Path Planning ◽  
Planning Algorithm ◽  
Aerial Vehicle ◽  
Dynamic Path ◽  
Path Planning Algorithm

Most of the 3D curve path planning is used to build static path planning. For intercepting of a moving target, the path planning has to be set in a dynamic condition. L+Dumo algorithm which is based on curve is used to intercept a moving target. In the real situations, the Unmanned Aerial Vehicle (UAV) has possibility to intercept a moving target from all direction. It is assumed that environment of the UAV is in 3D Euclidean Space. It means that the UAV has to adapt for all quadrants for interception of a moving target. This research develops a path planning algorithm which enhances the previous L+Dumo algorithm to encounter the possibility quadrants. The enhancement would be simulated in C++ language to determine the accuracy of the algorithm. The simulation is conducted using one UAV and one moving target with random obstacles of cylindrical shape in between both objects. The result shows that the system accuracy is 81.0876%, a level which is able to encounter all possibility quadrants.

scholarly journals A CooperativeQ-Learning Path Planning Algorithm for Origin-Destination Pairs in Urban Road Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaoyong Zhang ◽  
Heng Li ◽  
Jun Peng ◽  
Weirong Liu
Keyword(s):  
Path Planning ◽  
Intelligent Transportation Systems ◽  
Optimal Path ◽  
Road Networks ◽  
Transportation Systems ◽  
Prediction Algorithm ◽  
Urban Road ◽  
Learning Path ◽  
Planning Algorithm ◽  
Path Planning Algorithm

As an important part of intelligent transportation systems, path planning algorithms have been extensively studied in the literature. Most of existing studies are focused on the global optimization of paths to find the optimal path between Origin-Destination (OD) pairs. However, in urban road networks, the optimal path may not be always available when some unknown emergent events occur on the path. Thus a more practical method is to calculate several suboptimal paths instead of finding only one optimal path. In this paper, a cooperativeQ-learning path planning algorithm is proposed to seek a suboptimal multipath set for OD pairs in urban road networks. The road model is abstracted to the form thatQ-learning can be applied firstly. Then the gray prediction algorithm is combined intoQ-learning to find the suboptimal paths with reliable constraints. Simulation results are provided to show the effectiveness of the proposed algorithm.

Research on Path Planning Algorithm in Intelligent Transportation

2014 ◽  
Vol 536-537 ◽  
pp. 833-836
Author(s):  
Jin Peng Tang ◽  
Ling Lin Li
Keyword(s):  
Path Planning ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Traffic Density ◽  
Advantages And Disadvantages ◽  
Key Factor ◽  
Planning Algorithm ◽  
Transportation Vehicle ◽  
Path Planning Algorithm

Path planning is a key factor in intelligent transportation vehicle navigation system, compared to a variety of advantages and disadvantages of the path planning optimization algorithm. According obstacle distribution characteristics similar characteristics to the grid circuit resistor, proposed a Circuit Map path planning algorithm. The city's roads each segment was mapped to the circuit network, and the resistance of the resistor were mapped to with the Weighted sum of road length and width, and traffic density. This can be achieved by solving the circuit that intelligent transportation systems path planning and navigation services.

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