Route planning for multiple Unmanned Aerial Vehicles (UAVs) is a series of translation and rotational steps from a given start location to the destination goal location. The goal of the route planning problem is to determine the most optimal route avoiding any collisions with the obstacles present in the environment. Route planning is an NP-hard optimization problem. In this paper, a newly proposed Salp Swarm Algorithm (SSA) is used, and its performance is compared with deterministic and other Nature-Inspired Algorithms (NIAs). The results illustrate that SSA outperforms all the other meta-heuristic algorithms in route planning for multiple UAVs in a 3D environment.
The earliest hyperloop routes might not be limited to wealthy tech havens like California or the UAE. Missouri officials and Hyperloop One are seriously exploring the possibility of a hyperloop route that would run between Kansas City and St. Louis. As far as hyperloop routes go, however, this is potentially ideal. You might not see routes everywhere you'd like to go, but it could streamline travel in areas where cars take too long and aircraft are impractical.
The paper represents an algorithm for planning safe and optimal routes for transport facilities with unrestricted movement direction that travel within areas with obstacles. Paper explains the algorithm using a ship as an example of such a transport facility. This paper also provides a survey of several existing solutions for the problem. The method employs an evolutionary algorithm to plan several locally optimal routes and a parallel genetic algorithm to create the final route by optimising the abovementioned set of routes. The routes are optimized against the arrival time, assuming that the optimal route is the route with the lowermost arrival time. It is also possible to apply additional restriction to the routes.
Japan Airlines will launch routes linking Narita International Airport with Melbourne and Kona, Hawaii, in September. The airline will operate one flight each way every day on both routes, the carrier said Monday. JAL will launch the Narita-Melbourne route on Sept. 1, covering the second-largest city in Australia. The route will add to the existing one between Narita and Sydney, Australia's biggest city. JAL decided on the move as it expects demand growth thanks to the Japan-Australia economic partnership agreement, which came into force in January 2015.
Dubai's Roads and Transport Authority (RTA) is exploring the use of artificial intelligence (AI) to plot more efficient bus routes based on how they are used throughout the day. Machine learning (ML) algorithms could eventually inform updates to 150 routes used by 2,158 buses across Dubai, the RTA said. The authority trialled the system on ten public bus routes over thirty days, using Nol Card (Dubai's public transport smart card) data to understand patterns such as which bus stops were busy all day, which were primarily used during peak hours and those that were rarely used. The one-month trial cut wasted time on bus routes by 13.3 percent, the RTA reports. Ahmed Mahboub, Executive Director of Smart Services, Corporate Technology Support Services Sector, RTA, commented: "By using machine learning algorithms in analysing the captured data, departments can build up systems and take decisions with reference to abolishing certain stops, or proposing an express service that skips those stops, while ensuring customer needs are always addressed. Such a process will contribute to improving this vital service."