astar algorithm (also calls as A* algorithm) is often applied into robot path planning because of its simple, high efficiency and optimized path, but some disadvantages are also in it. The path by the tradition A* alg...
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ISBN:
(纸本)9781538632574
astar algorithm (also calls as A* algorithm) is often applied into robot path planning because of its simple, high efficiency and optimized path, but some disadvantages are also in it. The path by the tradition A* algorithm often contains many redundant points and inflection points. In order to reduce these points, the improved A* algorithm is put forward in this paper, which simplified the path nodes by using the smoothing method and reduced the inflection points by weighted processing of evaluation function. In addition, the actual width of the robot is taken into account when the robot bypasses obstacles, and the concept of node priority to the process of generating sub-nodes is proposed to solving it. The simulation results proves the effectiveness of the improved A* algorithm.
IOT (Internet of Thins) has received some recent attention in information technology research. One reason is that IOT provides a platform that can improve the economic effectiveness and save cost. The other reason is ...
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ISBN:
(纸本)9783642324260
IOT (Internet of Thins) has received some recent attention in information technology research. One reason is that IOT provides a platform that can improve the economic effectiveness and save cost. The other reason is that IOT provides technical support for the development of global economy. This paper describes an application of IOT in Shopping System, the Shopping System that would give the shoppers some services based on the position search. The Shopping System uses the location algorithm to get the shoppers' position in the indoor environment and is able to produce the shortest route from the shoppers to the merchandise based on astar algorithm, with a minimal amount of market map information. In the end, the limitations of the application are also discussed, together with possible directions for extending our future work toward better Shopping System.
Intelligent transportation system (ITS) applications are expected to provide a more efficient, effective, reliable, and safe driving experience, which can minimize road traffic congestion resulting in a better traffic...
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ISBN:
(纸本)9781628410587
Intelligent transportation system (ITS) applications are expected to provide a more efficient, effective, reliable, and safe driving experience, which can minimize road traffic congestion resulting in a better traffic flow management. To efficiently manage traffic flows, in this paper, we compare the effectiveness of two well-known vehicle routing algorithms: the Dijkstra's shortest path algorithm and the A* (astar) algorithm in terms of the total travel time and the travel distance. To this end, we built a generic ITS test-bed and created several real-world driving scenarios using field and simulation data to evaluate the performance of these two routing algorithms. The dataset used in our simulation is six weeks traffic volume data from 08/01/2012 to 09/27/2012 in the Maryland (MD)/Washington DC and Virginia (VA) area. Our simulation data shows that an increase in network size results in scalability problems as the efficiency and effectiveness of these algorithms diminishes in larger road networks with greater traffic volume densities, flow rates, and congested conditions. In addition, the imprecision of the road network increases as the network size and the traffic volume density increases. Our study shows that the ability of these vehicular routing algorithms to adaptively route traffic depends on the size and type of road networks, and the current roadway conditions.
Aiming at the problem that online ride-hailing drivers often empty their cars to replenish fuel at gas stations when their cars run out of gas, a new order assignment algorithm is proposed. According to the vehicle fu...
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Aiming at the problem that online ride-hailing drivers often empty their cars to replenish fuel at gas stations when their cars run out of gas, a new order assignment algorithm is proposed. According to the vehicle fuel volume reported by the driver to the platform, the vehicle with low fuel volume will be automatically assigned to the destination close to the gas station orders, and the driver will be reminded to go to the nearby gas station to reduce the empty vehicle round-trip rate. First of all, orders are classified into ordinary orders and refuelling orders, so that when the vehicle is short of fuel, the driver can be assigned to the refuelling orders with destinations close to gas stations. Then, a new order allocation mathematical model is established. This paper solves the order assignment problem based on the heap-optimized Dijkstra's algorithm and astar algorithm. Experimental results show that the algorithm can intelligently allocate orders for drivers with insufficient fuel to their destinations closer to the gas station, shorten the distance the driver drives empty to the gas station to replenish fuel, and reduce the empty vehicle round-trip rate. When using Dijkstra's algorithm and astar algorithm to solve the order allocation problem, there is no significant difference in their processing time.
In order to improve the working efficiency of high speed and high precision AGV, the method of path planning in dispatching system is studied, and an improved astar algorithm is proposed, which can reduce the number o...
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In order to improve the working efficiency of high speed and high precision AGV, the method of path planning in dispatching system is studied, and an improved astar algorithm is proposed, which can reduce the number of inflection points needed in path planning. The weight ratio of AGV going straight and turning is raised. The improved algorithm is applied to AGV path planning, which improves the efficiency of the algorithm. Experimental results show that the efficiency of this algorithm is higher than that of traditional astar algorithm in the application of specific enterprise projects.
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