Multi-aircraft Collaborative Route Planning Scheme Based on Coevolution

2020 ◽  
Author(s):  
Hongbo Li ◽  
Jinbo Bai
Keyword(s):  
Route Planning ◽  
Planning Scheme

scholarly journals Anti-Congestion Route Planning Scheme Based on Dijkstra Algorithm for Automatic Valet Parking System

2019 ◽  
Vol 9 (23) ◽  
pp. 5016 ◽  
Author(s):  
Yu ◽  
Jiang ◽  
Hua
Keyword(s):  
Intelligent Transportation System ◽  
New Technology ◽  
Influence Factors ◽  
Route Planning ◽  
Parking Space ◽  
Dijkstra Algorithm ◽  
Static State ◽  
Shortest Route ◽  
Planning Scheme ◽  
Parking Lot

Based on the Dijkstra algorithm, with the parking parameters in the static state, the shortest route to each parking space of the parking lot without dynamic influence factors can be calculated. In the new technology background of the combination of the V2X environment and driverless technology, the dynamic influence factors, for example, the lanes occupancy situation caused by parking, can be considered to improve the shortest route with the new scheme in this paper. Then the final route that costs the least time to reach each parking space will be calculated. This is very important for the development of the intelligent transportation system in the parking lot environment.

A privacy-preserving route planning scheme for the Internet of Vehicles

2021 ◽  
pp. 102680
Author(s):  
Ugur Ilker Atmaca ◽  
Carsten Maple ◽  
Gregory Epiphaniou ◽  
Mehrdad Dianati
Keyword(s):  
Route Planning ◽  
Privacy Preserving ◽  
The Internet ◽  
Internet Of Vehicles ◽  
Planning Scheme

scholarly journals A Novel Route Planning Scheme Based on Dynamic Time Variables

2021 ◽  
Vol 2068 (1) ◽  
pp. 012022
Author(s):  
Jinghe Zhang ◽  
Lei Li ◽  
Yuechao Zhang ◽  
Shaofeng Cheng ◽  
Weidong Fang
Keyword(s):  
Optimal Path ◽  
Route Planning ◽  
Fixed Time ◽  
Sufficient Time ◽  
Planning Scheme ◽  
Stay Time ◽  
Time Requirements ◽  
Current Value ◽  
Time Variables ◽  
Dynamic Time

Abstract In this paper, the processing method of dynamic time variables in the route planning nodethat we designed involves the field of route planning, including determining the route time and stay time, combining the floating reserved time to determine the redundancy; after the entity has visited a node, the current value is calculated Redundancy: According to the calculated redundancy value, combined with the preset redundancy threshold, the entity’s route and stay time are reminded. By converting the dynamic time variable into a fixed value, the model can complete the search for the optimal path within a limited time. At the same time, the concept of reserved floating time is introduced, thereby retaining the dynamic characteristics of time, so that visitors can have sufficient time stay, and can complete the stay according to the fixed time requirements, can effectively track the stay time and make corresponding processing in the corresponding situation to ensure the stay ability. The proposed scheme has better performance.

scholarly journals Vision-Based Behavior Planning for Lunar or Planetary Exploration Rover on Flat Surface

2017 ◽  
Vol 29 (5) ◽  
pp. 847-855 ◽  
Author(s):  
Riho Ejiri ◽  
Takashi Kubota ◽  
Ichiro Nakatani ◽  
◽  
Keyword(s):  
Flat Surface ◽  
Route Planning ◽  
Image Data ◽  
Planetary Exploration ◽  
The Moon ◽  
Planetary Rover ◽  
Planning Scheme ◽  
Mission Period ◽  
Flat Ground ◽  
Navigation Method

Lunar or planetary exploration rovers are expected to have the ability to move across an area as wide as possible in an unknown environment during a limited mission period. Hence, they need an efficient navigation method. Most of the surface of the moon or planets consists of flat ground, sand, and scattered rocks. In a simple flat sandy terrain with some rocks, rough route planning is sufficient for a lunar or planetary rover to avoid obstacles and reach an assigned point. This paper proposes an efficient vision-based planning scheme for exploration rovers on a flat surface with scattered obstacles. In the proposed scheme, dangerous areas are robustly extracted by processing image data, and the degree of danger is defined. A rough routing plan and sensing plan are simultaneously constructed based on the dangerous-area extraction results. The effectiveness of the proposed scheme is discussed based on the results of some simulations and simple experiments.

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