Online Routing for Autonomous Vehicle Cruise Systems with Fuel Constraints

Autonomous ground/aerial vehicles (UGVs/UAVs) boost many potential applications over past few years, but it usually takes a long time or a large price to fully recharge or refuel a vehicle, so it is extremely important to make efficient routing decisions for autonomous vehicles with limited fuel cap...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of intelligent & robotic systems Jg. 104; H. 4; S. 68
Hauptverfasser: Li, Longjiang, Liang, Haoyang, Wang, Jie, Yang, Jianjun, Li, Yonggang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Dordrecht Springer Netherlands 01.04.2022
Springer
Springer Nature B.V
Schlagworte:
Algorithms
Artificial Intelligence
Autonomous vehicles
Complexity
Computational geometry
Control
Convexity
Driverless cars
Electrical Engineering
Engineering
Fuel
Fuel consumption
Mechanical Engineering
Mechatronics
Mixed integer
Optimization
Performance degradation
Polynomials
Robotics
Route planning
Short Paper
Shortest-path problems
Solution space
Topical collection on Unmanned Systems
Unmanned aerial vehicles
Online algorithms
Computation complexity
Fuel constraints
Autonomous vehicles
Cruising problems
ISSN:0921-0296, 1573-0409
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Autonomous ground/aerial vehicles (UGVs/UAVs) boost many potential applications over past few years, but it usually takes a long time or a large price to fully recharge or refuel a vehicle, so it is extremely important to make efficient routing decisions for autonomous vehicles with limited fuel capacity. This paper elaborates the uninterrupted cruising requirements for autonomous vehicles and the influence of limited fuel capacity on the routing policies. We provide a proof that the basic cruising problem is NP-hard in the general case, though the previous work formulated it as a polynomial problem based on some oversimplified assumptions, which result in a degraded performance under the condition of limited fuel capacity. This is formulated as a mixed-integer non-convex optimization problem, which is difficult to solve in general. Furthermore, we observed that the nature of the limited fuel capacity is a limitation on the solution space of the cruising problem, which motivated us to construct an efficient heuristic solution by applying the fuel constraints iteratively on the shortest path that can be obtained in polynomial time. Since targets are usually requested in an online way in real cruising applications, we design a sliding window-based algorithm, so that a tradeoff can be made between the routing efficiency and the computation complexity by adjusting the window size. Finally, the simulation results show that the proposed scheme reduces the computation complexity by at least 13 times, simultaneously with performance improvements by about 7% in terms of fuel consumption than the alternative algorithms.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0921-0296
1573-0409
DOI:10.1007/s10846-021-01530-y