Cirrocumulus, Nimbostratus and Stratocumulus depiction in X-Plane 11 is planned for the near future. Maxx-XP, in co-operation with Sundog Software, and X-Aviation are excited to bring you another game changing experience to the weather rendering in X-Plane 11! SkyMaxx Pro v5 is an X-Plane cloud and sky replacement engine boasting all-new technology for X-Plane that it's almost like having an all-new sim!įSGRW Integration!: The FS Global Real Weather engine is able to process a wide variety of cloud identifiers, such as Cirrus, Cumulus, Stratus, Cumulonimbus and Towering Cumulus. X-Plane's most popular and best-selling add-on is back as version 5, and with some great new features! SkyMaxx Pro v5 - A revolutionary weather rendering engine for X-Plane 11!
Simulation and comparative studies validate that the proposed algorithms effectively carry out the adjustable speed navigation and mapping of autonomous vehicles based on road conditions in various real-world scenarios.Want the best weather in X-Plane? Buy SkyMaxx Pro v5 and Real Weather Connector for amazing immersion! To verify the theoretical advantages of the developed algorithms, we perform comparative experiments under various scenarios. In addition, a local reactive navigator is developed that builds environmental maps locally while avoiding dynamic and unknown obstacles.
The proposed Bat-Pigeon algorithm navigates the autonomous vehicle to decelerate around small crack areas while planning a collision-free path with the least travel time. Take advantage of the same individual speed update rule, we integrate the global search of the Pigeon-inspired optimization (PIO) algorithm and the local search by the Bat algorithm (BA), which can effectively improve the speed and performance of the convergence algorithm.
Then, in light of the obtained location of cracks and obstacles, a Bat-Pigeon algorithm (BPA) is proposed to conduct adjustable speed navigation of autonomous vehicles. Based on the obtained image of the road environment, an image processing algorithm to accurately locate the crack is developed. Therefore, in this paper, we propose an adjustable speed navigation method in light of crack detection for autonomous vehicle path planning, which can automatically adjust the speed in the cracked areas of the road. In this case, while the autonomous vehicles pass through these cracked areas at high speed, it will increase the sense of bumps and even deviate from the originally planned route, which may potentially cause vehicle damage. However, due to the long-term use of roads and lack of maintenance, the roads that autonomous vehicles need to pass inevitably have cracks. Autonomous vehicles have nowadays received widespread attention, and path planning is one of the most important components of its autonomous operation.
0 kommentar(er)
