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.

Recent advances on urban taxi sharing systems with the path arrival probability

2020 ◽  
Vol 13 ◽  
Author(s):  
Dui Hongyan ◽  
Zhang Chi
Keyword(s):  
Failure Probability ◽  
Traffic Congestion ◽  
Optimal Strategy ◽  
Time Windows ◽  
Optimal Path ◽  
Route Planning ◽  
Driving Time ◽  
Load Rate ◽  
Travel Efficiency ◽  
Arrival Probability

Background : Taxi sharing is an emerging transportation arrangement that helps improve the passengers’ travel efficiency and reduce costs. This study proposes an urban taxi sharing system. Methods: Considering each side congestion of the transport network, their corresponding reliability and failure probability are analyzed. Under the constraints of the number of passengers and their own time windows, the analysis is performed on passengers whose optimal path is inclusive. Results: According to the optimal strategy, the different passengers can be arranged into the same taxi to realize the taxi sharing. Then the shared taxi route can be optimized. Conclusion: Due to the reasonable vehicle route planning and passenger combination, these can effectively alleviate the traffic congestion, save the driving time, reduce the taxi no-load rate, and save the driving distance. At last, a numerical example is used to demonstrate the proposed method.

Optimal path planning with modified A-Star algorithm for stealth unmanned aerial vehicles in 3D network radar environment

2021 ◽  
pp. 095441002110073
Author(s):  
Zhe Zhang ◽  
Jian Wu ◽  
Jiyang Dai ◽  
Cheng He
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Optimal Path ◽  
Radar System ◽  
Planning Method ◽  
Optimal Path Planning ◽  
Aerial Vehicles ◽  
3D Network ◽  
Planning Scheme ◽  
Estimation Function

For stealth unmanned aerial vehicles (UAVs), path security and search efficiency of penetration paths are the two most important factors in performing missions. This article investigates an optimal penetration path planning method that simultaneously considers the principles of kinematics, the dynamic radar cross-section of stealth UAVs, and the network radar system. By introducing the radar threat estimation function and a 3D bidirectional sector multilayer variable step search strategy into the conventional A-Star algorithm, a modified A-Star algorithm was proposed which aims to satisfy waypoint accuracy and the algorithm searching efficiency. Next, using the proposed penetration path planning method, new waypoints were selected simultaneously which satisfy the attitude angle constraints and rank-K fusion criterion of the radar system. Furthermore, for comparative analysis of different algorithms, the conventional A-Star algorithm, bidirectional multilayer A-Star algorithm, and modified A-Star algorithm were utilized to settle the penetration path problem that UAVs experience under various threat scenarios. Finally, the simulation results indicate that the paths obtained by employing the modified algorithm have optimal path costs and higher safety in a 3D complex network radar environment, which show the effectiveness of the proposed path planning scheme.

Rule 210 Oral hearing

2018 ◽  
Author(s):  
Andreas von Falck ◽  
Stephan Dorn
Keyword(s):  
Fixed Time ◽  
Time Limit ◽  
Sufficient Time

The date for the oral hearing will be set as soon as possible after the date of receipt of the application for provisional measures. There is no fixed time limit for summoning the parties to the oral hearing; however, there must be sufficient time for the opponent to engage a lawyer and to prepare his defence. This is a requirement of fair and equitable proceedings (Art 42(2) UPCA) and of the fundamental right to be heard (Art 56(2) UPCA).

scholarly journals A Hybrid Tabu Search and 2-opt Path Programming for Mission Route Planning of Multiple Robots under Range Limitations

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 534 ◽  
Author(s):  
Meng-Tse Lee ◽  
Bo-Yu Chen ◽  
Ying-Chih Lai
Keyword(s):  
Tabu Search ◽  
Large Scale ◽  
Optimal Path ◽  
Route Planning ◽  
Unmanned Vehicles ◽  
Programming Algorithm ◽  
Second Phase ◽  
Two Phase ◽  
Exchange Method ◽  
Unmanned Vehicle

The application of an unmanned vehicle system allows for accelerating the performance of various tasks. Due to limited capacities, such as battery power, it is almost impossible for a single unmanned vehicle to complete a large-scale mission area. An unmanned vehicle swarm has the potential to distribute tasks and coordinate the operations of many robots/drones with very little operator intervention. Therefore, multiple unmanned vehicles are required to execute a set of well-planned mission routes, in order to minimize time and energy consumption. A two-phase heuristic algorithm was used to pursue this goal. In the first phase, a tabu search and the 2-opt node exchange method were used to generate a single optimal path for all target nodes; the solution was then split into multiple clusters according to vehicle numbers as an initial solution for each. In the second phase, a tabu algorithm combined with a 2-opt path exchange was used to further improve the in-route and cross-route solutions for each route. This diversification strategy allowed for approaching the global optimal solution, rather than a regional one with less CPU time. After these algorithms were coded, a group of three robot cars was used to validate this hybrid path programming algorithm.

scholarly journals Research on aircraft route planning optimization problem with multi-constraints and dual-targets

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Qianyu Zhang ◽  
Xianfeng Ding ◽  
Jingyu Zhou ◽  
Yi Nie
Keyword(s):  
Path Length ◽  
Model Simulation ◽  
Optimal Path ◽  
Route Planning ◽  
Solution Time ◽  
Planning Model ◽  
Data Set ◽  
Positioning Errors ◽  
Core Technology ◽  
Planning Algorithm

Abstract As the core technology in the field of aircraft, the route planning has attracted much attention. However, due to the complexity of the structure and performance constraints of the aircraft, the route planning algorithm does not have well universality, so it cannot be used in a complex environment. In the paper, a multi-constraints and dual-targets aircraft route planning model was established for the real-time requirements of space flight, the dynamic changes of flight environment with time, the accuracy requirements of positioning errors in the safety area, and the minimum turning radius constraints. Based on the directed graph and dynamic programming ideas, the model simulation and model validation were carried out with the data of F question in the “16th Graduate Mathematical Modeling Contest”. The results showed that the optimal path length obtained in data set 1 was 124.61 km, the number of corrections was 11 times, the solution time was 2.3768 seconds, the optimal path length obtained in data set 2 was 110.00 km, and the number of corrections was 12 times. The solution time was 0.0168 seconds. Multi-constraints and dual-targets aircraft route planning model can plan the flight path of the aircraft intuitively and timely, which confirmed the effectiveness of the model.

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.

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