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Keywords = waypoint-tracking

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10 pages, 1924 KiB  
Article
A Waypoint-Based Flow Capture Location Model for Siting Facilities on Transportation Networks
by Joni Downs, Yujie Hu and Ran Tao
Future Transp. 2025, 5(3), 93; https://doi.org/10.3390/futuretransp5030093 (registering DOI) - 1 Aug 2025
Viewed by 69
Abstract
We introduce a waypoint-based flow capture location model (WbFCLM) for siting facilities on networks with the objective of maximally capturing flows. The advantages of the waypoint-based formulation are that (1) demand is modeled along observed trajectories rather than assumed travel paths, and (2) [...] Read more.
We introduce a waypoint-based flow capture location model (WbFCLM) for siting facilities on networks with the objective of maximally capturing flows. The advantages of the waypoint-based formulation are that (1) demand is modeled along observed trajectories rather than assumed travel paths, and (2) demand is allowed to vary across geographic space. We demonstrate the WbFCLM using a test dataset derived from vehicle tracking data. Though solving the WbFCLM can require considerable computing power, it can be used to site facilities on networks where both flows and demand vary spatially. Full article
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19 pages, 3520 KiB  
Article
Vision-Guided Maritime UAV Rescue System with Optimized GPS Path Planning and Dual-Target Tracking
by Suli Wang, Yang Zhao, Chang Zhou, Xiaodong Ma, Zijun Jiao, Zesheng Zhou, Xiaolu Liu, Tianhai Peng and Changxing Shao
Drones 2025, 9(7), 502; https://doi.org/10.3390/drones9070502 - 16 Jul 2025
Viewed by 493
Abstract
With the global increase in maritime activities, the frequency of maritime accidents has risen, underscoring the urgent need for faster and more efficient search and rescue (SAR) solutions. This study presents an intelligent unmanned aerial vehicle (UAV)-based maritime rescue system that combines GPS-driven [...] Read more.
With the global increase in maritime activities, the frequency of maritime accidents has risen, underscoring the urgent need for faster and more efficient search and rescue (SAR) solutions. This study presents an intelligent unmanned aerial vehicle (UAV)-based maritime rescue system that combines GPS-driven dynamic path planning with vision-based dual-target detection and tracking. Developed within the Gazebo simulation environment and based on modular ROS architecture, the system supports stable takeoff and smooth transitions between multi-rotor and fixed-wing flight modes. An external command module enables real-time waypoint updates. This study proposes three path-planning schemes based on the characteristics of drones. Comparative experiments have demonstrated that the triangular path is the optimal route. Compared with the other schemes, this path reduces the flight distance by 30–40%. Robust target recognition is achieved using a darknet-ROS implementation of the YOLOv4 model, enhanced with data augmentation to improve performance in complex maritime conditions. A monocular vision-based ranging algorithm ensures accurate distance estimation and continuous tracking of rescue vessels. Furthermore, a dual-target-tracking algorithm—integrating motion prediction with color-based landing zone recognition—achieves a 96% success rate in precision landings under dynamic conditions. Experimental results show a 4% increase in the overall mission success rate compared to traditional SAR methods, along with significant gains in responsiveness and reliability. This research delivers a technically innovative and cost-effective UAV solution, offering strong potential for real-world maritime emergency response applications. Full article
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26 pages, 6918 KiB  
Article
Coordinated Reentry Guidance with A* and Deep Reinforcement Learning for Hypersonic Morphing Vehicles Under Multiple No-Fly Zones
by Cunyu Bao, Xingchen Li, Weile Xu, Guojian Tang and Wen Yao
Aerospace 2025, 12(7), 591; https://doi.org/10.3390/aerospace12070591 - 30 Jun 2025
Viewed by 350
Abstract
Hypersonic morphing vehicles (HMVs), renowned for their adaptive structural reconfiguration and cross-domain maneuverability, confront formidable reentry guidance challenges under multiple no-fly zones, stringent path constraints, and nonlinear dynamics exacerbated by morphing-induced aerodynamic uncertainties. To address these issues, this study proposes a hierarchical framework [...] Read more.
Hypersonic morphing vehicles (HMVs), renowned for their adaptive structural reconfiguration and cross-domain maneuverability, confront formidable reentry guidance challenges under multiple no-fly zones, stringent path constraints, and nonlinear dynamics exacerbated by morphing-induced aerodynamic uncertainties. To address these issues, this study proposes a hierarchical framework integrating an A-based energy-optimal waypoint planner, a deep deterministic policy gradient (DDPG)-driven morphing policy network, and a quasi-equilibrium glide condition (QEGC) guidance law with continuous sliding mode control. The A* algorithm generates heuristic trajectories circumventing no-fly zones, reducing the evaluation function by 6.2% compared to greedy methods, while DDPG optimizes sweep angles to minimize velocity loss and terminal errors (0.09 km position, 0.01 m/s velocity). The QEGC law ensures robust longitudinal-lateral tracking via smooth hyperbolic tangent switching. Simulations demonstrate generalization across diverse targets (terminal errors < 0.24 km) and robustness under Monte Carlo deviations (0.263 ± 0.184 km range, −12.7 ± 42.93 m/s velocity). This work bridges global trajectory planning with real-time morphing adaptation, advancing intelligent HMV control. Future research will extend this framework to ascent/dive phases and optimize its computational efficiency for onboard deployment. Full article
(This article belongs to the Section Aeronautics)
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22 pages, 2586 KiB  
Article
Model Predictive Control for Autonomous Ship Navigation with COLREG Compliance and Chart-Based Path Planning
by Primož Potočnik
J. Mar. Sci. Eng. 2025, 13(7), 1246; https://doi.org/10.3390/jmse13071246 - 28 Jun 2025
Viewed by 452
Abstract
Autonomous ship navigation systems must ensure safe and efficient route planning while complying with the International Regulations for Preventing Collisions at Sea (COLREGs). This paper presents an integrated navigation framework that combines chart-based global path planning with a Model Predictive Control (MPC) approach [...] Read more.
Autonomous ship navigation systems must ensure safe and efficient route planning while complying with the International Regulations for Preventing Collisions at Sea (COLREGs). This paper presents an integrated navigation framework that combines chart-based global path planning with a Model Predictive Control (MPC) approach for local trajectory tracking and COLREG-compliant collision avoidance. The method generates feasible reference routes using maritime charts and predefined waypoints, while the MPC controller ensures precise path following and dynamic re-planning in response to nearby vessels and coastal obstacles. Coastal features and shorelines are modeled using Global Self-consistent, Hierarchical, High-resolution Geography data, enabling MPC to treat landmasses as static obstacles. Other vessels are represented as dynamic obstacles with varying speeds and headings, and COLREG rules are embedded within the MPC framework to enable rule-compliant maneuvering during encounters. To address real-time computational constraints, a simplified MPC formulation is introduced, balancing predictive accuracy with computational efficiency, making the approach suitable for embedded implementations. The navigation framework is implemented in a MATLAB-based simulation with real-time visualization supporting multi-vessel scenarios and COLREG-aware vessel interactions. Simulation results demonstrate robust performance across diverse maritime scenarios—including complex multi-ship encounters and constrained coastal navigation—while maintaining the shortest safe routes. By seamlessly integrating chart-aware path planning with COLREG-compliant, MPC-based collision avoidance, the proposed framework offers an effective, scalable, and robust solution for autonomous maritime navigation. Full article
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22 pages, 1585 KiB  
Article
Distributed Formation Planning for Unmanned Aerial Vehicles
by Zeming Zhao, Xiaozhen Zhang, Hao Fang and Qingkai Yang
Drones 2025, 9(4), 306; https://doi.org/10.3390/drones9040306 - 14 Apr 2025
Cited by 1 | Viewed by 804
Abstract
Formation flying of multiple unmanned aerial vehicles (UAVs) has attracted much attention for its versatility in cooperative tasks. In this paper, a distributed formation planning method is proposed for UAVs. First, we design a path searching algorithm, swarm-A*, which can enhance the cohesion [...] Read more.
Formation flying of multiple unmanned aerial vehicles (UAVs) has attracted much attention for its versatility in cooperative tasks. In this paper, a distributed formation planning method is proposed for UAVs. First, we design a path searching algorithm, swarm-A*, which can enhance the cohesion of a swarm, i.e., preventing the disintegration of the swarm when it encounters an obstacle. Then, after waypoint reallocation, a formation trajectory optimization framework is formulated. Smooth formation trajectories for UAVs to travel safely in obstacle-laden environments can be obtained by solving the optimization problem. Next, a tracking controller based on sliding mode control is designed, ensuring that the UAVs follow the planned formation trajectories under dynamic constraints. Finally, numerical simulations and experiments are conducted to validate the effectiveness of the proposed method. Full article
(This article belongs to the Section Drone Communications)
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40 pages, 16671 KiB  
Article
Multi-Mode Flight Simulation and Energy-Aware Coverage Path Planning for a Lift+Cruise QuadPlane
by Akshay Mathur and Ella Atkins
Drones 2025, 9(4), 287; https://doi.org/10.3390/drones9040287 - 8 Apr 2025
Cited by 1 | Viewed by 795
Abstract
This paper describes flight planning supported by modeling, guidance, and feedback control for an electric Vertical Take-Off and Landing (eVTOL) QuadPlane small Uncrewed Aircraft System (sUAS). Five Lift+Cruise sUAS waypoint types are defined and used to construct smooth flight path geometries and acceleration [...] Read more.
This paper describes flight planning supported by modeling, guidance, and feedback control for an electric Vertical Take-Off and Landing (eVTOL) QuadPlane small Uncrewed Aircraft System (sUAS). Five Lift+Cruise sUAS waypoint types are defined and used to construct smooth flight path geometries and acceleration profiles. Novel accelerated coverage flight plan segments for hover (Lift) and coverage (Cruise) waypoint types are defined as a complement to traditional fly-over, fly-by, and Dubins path waypoint transit solutions. Carrot-chasing guidance shows a tradeoff between tracking accuracy and control stability as a function of the carrot time step. Experimentally validated aerodynamic and thrust models for vertical, forward, and hybrid flight modes are developed as a function of airspeed and angle of attack from wind tunnel data. A QuadPlane feedback controller augments classical multicopter and fixed-wing controllers with a hybrid control mode that combines multicopter and aircraft control actuators to add a controllable pitch degree of freedom at the cost of increased energy use. Multi-mode flight simulations show Cruise mode to be the most energy efficient with a relatively large turning radius constraint, while quadrotor mode enables hover and smaller radius turns. Energy efficiency analysis over QuadPlane plans with modest inter-waypoint distances indicates cruise or aircraft mode is 30% more energy efficient overall than quadrotor mode. Energy-aware coverage planner simulation results show fly-coverage (cruise) waypoints are always the most efficient given long distances between waypoints. A Pareto analysis of energy use versus area coverage is presented to analyze waypoint-type tradeoffs in case studies with closely spaced waypoints. Coverage planning and guidance methods from this paper can be applied to any Lift+Cruise aircraft configuration requiring waypoint flight mode optimization over energy and coverage metrics. Full article
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25 pages, 9276 KiB  
Article
Experimental Evaluation of Multi- and Single-Drone Systems with 1D LiDAR Sensors for Stockpile Volume Estimation
by Ahmad Alsayed, Fatemeh Bana, Farshad Arvin, Mark K. Quinn and Mostafa R. A. Nabawy
Aerospace 2025, 12(3), 189; https://doi.org/10.3390/aerospace12030189 - 26 Feb 2025
Viewed by 1098
Abstract
This study examines the application of low-cost 1D LiDAR sensors in drone-based stockpile volume estimation, with a focus on indoor environments. Three approaches were experimentally investigated: (i) a multi-drone system equipped with static, downward-facing 1D LiDAR sensors combined with an adaptive formation control [...] Read more.
This study examines the application of low-cost 1D LiDAR sensors in drone-based stockpile volume estimation, with a focus on indoor environments. Three approaches were experimentally investigated: (i) a multi-drone system equipped with static, downward-facing 1D LiDAR sensors combined with an adaptive formation control algorithm; (ii) a single drone with a static, downward-facing 1D LiDAR following a zigzag trajectory; and (iii) a single drone with an actuated 1D LiDAR in an oscillatory fashion to enhance scanning coverage while following a shorter trajectory. The adaptive formation control algorithm, newly developed in this study, synchronises the drones’ waypoint arrivals and facilitates smooth transitions between dynamic formation shapes. Real-world experiments conducted in a motion-tracking indoor facility confirmed the effectiveness of all three approaches in accurately completing scanning tasks, as per intended waypoints allocation. A trapezoidal prism stockpile was scanned, and the volume estimation accuracy of each approach was compared. The multi-drone system achieved an average volumetric error of 1.3%, similar to the single drone with a static sensor, but with less than half the flight time. Meanwhile, the actuated LiDAR system required shorter paths but experienced a higher volumetric error of 4.4%, primarily due to surface reconstruction outliers and common LiDAR bias when scanning at non-vertical angles. Full article
(This article belongs to the Special Issue UAV System Modelling Design and Simulation)
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16 pages, 4058 KiB  
Article
Autonomous Mission Planning for Fixed-Wing Unmanned Aerial Vehicles in Multiscenario Reconnaissance
by Bei Chen, Jiaxin Yan, Zebo Zhou, Rui Lai and Jiejian Lin
Sensors 2025, 25(4), 1176; https://doi.org/10.3390/s25041176 - 14 Feb 2025
Cited by 1 | Viewed by 1171
Abstract
Before a fixed-wing UAV executes target tracking missions, it is essential to identify targets through reconnaissance mission areas using onboard payloads. This paper presents an autonomous mission planning method designed for such reconnaissance operations, enabling effective target identification prior to tracking. Existing planning [...] Read more.
Before a fixed-wing UAV executes target tracking missions, it is essential to identify targets through reconnaissance mission areas using onboard payloads. This paper presents an autonomous mission planning method designed for such reconnaissance operations, enabling effective target identification prior to tracking. Existing planning methods primarily focus on flight performance, energy consumption, and obstacle avoidance, with less attention to integrating payload. Our proposed method emphasizes the combination of two key functions: flight path planning and payload mission planning. In terms of path planning, we introduce a method based on the Hierarchical Traveling Salesman Problem (HTSP), which utilizes the nearest neighbor algorithm to find the optimal visit sequence and entry points for area targets. When dealing with area targets containing no-fly zones, HTSP quickly calculates a set of waypoints required for coverage path planning (CPP) based on the Generalized Traveling Salesman Problem (GTSP), ensuring thorough and effective reconnaissance coverage. In terms of payload mission planning, our proposed method fully considers payload characteristics such as scan resolution, imaging width, and operating modes to generate predefined mission instruction sets. By meticulously analyzing payload constraints, we further optimized the path planning results, ensuring that each instruction meets the payload performance requirements. Finally, simulations validated the effectiveness and superiority of the proposed autonomous mission planning method in reconnaissance tasks. Full article
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27 pages, 10913 KiB  
Article
Observer-Based Sliding Mode Control for Vehicle Way-Point Tracking with Unknown Disturbances and Obstacles
by Jiacheng Song, Mingjie Shen and Yanan Zhang
Actuators 2025, 14(2), 89; https://doi.org/10.3390/act14020089 - 13 Feb 2025
Viewed by 787
Abstract
In this paper, an advanced vehicle way-point tracking control method, including kinematic control, dynamic control and an obstacle avoidance strategy, is introduced. In the kinematic part, a vehicle kinematic model is established, along with the coordinate transformation between the vehicle and its target. [...] Read more.
In this paper, an advanced vehicle way-point tracking control method, including kinematic control, dynamic control and an obstacle avoidance strategy, is introduced. In the kinematic part, a vehicle kinematic model is established, along with the coordinate transformation between the vehicle and its target. A way-point tracking control law is developed to optimize the vehicle’s movement along predefined way-points. In the dynamic part, a dynamic model considering the actual disturbances and losses is established. An observer compensation technique is utilized to monitor and mitigate disturbances, while sliding mode control, enhanced by a HyperSpiral algorithm, ensures accurate and stable tracking performance. Furthermore, to tackle real-world path planning challenges, an improved way-point tracking obstacle-avoidance algorithm is developed to generate effective way-points for navigating around obstacles. Finally, simulation results validate that the vehicle consistently tracks target way-points in complex scenarios, highlighting the robustness and effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Integrated Intelligent Vehicle Dynamics and Control)
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22 pages, 1772 KiB  
Article
Autonomous Sea Floor Coverage with Constrained Input Autonomous Underwater Vehicles: Integrated Path Planning and Control
by Athanasios K. Gkesoulis, Panagiotis Georgakis, George C. Karras and Charalampos P. Bechlioulis
Sensors 2025, 25(4), 1023; https://doi.org/10.3390/s25041023 - 9 Feb 2025
Cited by 2 | Viewed by 850
Abstract
Autonomous underwater vehicles (AUVs) tasked with seafloor coverage require a robust integration of path planning and control strategies to operate in adverse real-world environments including obstacles, disturbances, and physical constraints. In this work, we present a fully integrated framework that combines an optimal [...] Read more.
Autonomous underwater vehicles (AUVs) tasked with seafloor coverage require a robust integration of path planning and control strategies to operate in adverse real-world environments including obstacles, disturbances, and physical constraints. In this work, we present a fully integrated framework that combines an optimal coverage path planning approach with a robust constrained control algorithm. The path planner leverages a priori information of the target area to achieve maximal coverage, minimize path turns, and ensure obstacle avoidance. On the control side, we employ a reference modification technique that guarantees prescribed waypoint tracking performance under input constraints. The resulting integrated solution is validated in a high-fidelity simulation environment employing ROS, Gazebo, and ArduSub Software-in-the-Loop (SITL) on a BlueROV2 platform. The simulation results demonstrate the synergy between path planning and control, illustrating the framework’s effectiveness and readiness for practical seafloor operations such as underwater debris detection. Full article
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18 pages, 13307 KiB  
Article
Redesign of a Towing Mobile Robot Control Architecture and Implementation of Outdoor Experiments Using the Transverse Function Approach
by Bartłomiej Krysiak, Dariusz Pazderski, Jarosław Majchrzak, Marcin Kotlarek, Piotr Mieszała, Mateusz Michalski, Krzysztof Maciołek and Paweł Nowak
Appl. Sci. 2025, 15(3), 1566; https://doi.org/10.3390/app15031566 - 4 Feb 2025
Viewed by 961
Abstract
This article discusses the redesign of a towing mobile robot to obtain a modern system for implementing mobile robot control research. Controller architecture issues are presented, and a selected control algorithm is considered in detail. The reconstruction of the robot is also intended [...] Read more.
This article discusses the redesign of a towing mobile robot to obtain a modern system for implementing mobile robot control research. Controller architecture issues are presented, and a selected control algorithm is considered in detail. The reconstruction of the robot is also intended to ensure that the current standards for the electronic architecture controlling the robot are met and that this architecture can be easily developed to include components related to the safety of the robot’s operation. The discussion of the control architecture is divided into a description of the high-level controller responsible for the position stabilization algorithm and a description of the low-level controller responsible for the drive motor control and robot safety. The high-level control algorithm is responsible for a trajectory tracking task realized with use of a transverse function approach algorithm. A time elastic band algorithm was also used to generate a reference trajectory, allowing the robot to be guided through waypoints. The low-level controller is comprehensively described with details on the industrial controller architecture used, the communication between the controller modules, and the interaction of these modules with the on-board computer. The redesign of the towing mobile robot was summarized by the implementation of outdoor experiments where the task of driving through reference points was completed. Full article
(This article belongs to the Special Issue Recent Advances in Autonomous Systems and Robotics, 2nd Edition)
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18 pages, 11052 KiB  
Article
A Robust Path Tracking Controller for Autonomous Mobility with Control Delay Compensation Using Backstepping Control
by Munjung Jang, Sehwan Kim, Byeonghun Yoo and Kwangseok Oh
Actuators 2024, 13(12), 508; https://doi.org/10.3390/act13120508 - 9 Dec 2024
Cited by 2 | Viewed by 1176
Abstract
Control delay phenomena, such as time delays and actuator lags, can compromise the control performance of autonomous mobility systems, leading to increased control errors. Therefore, it is essential to develop a control delay compensation algorithm. This paper proposes a Lyapunov-based backstepping steering control [...] Read more.
Control delay phenomena, such as time delays and actuator lags, can compromise the control performance of autonomous mobility systems, leading to increased control errors. Therefore, it is essential to develop a control delay compensation algorithm. This paper proposes a Lyapunov-based backstepping steering control algorithm to compensate for control delays in autonomous mobility systems. To estimate the control delay in the steering system, the Recursive Least Squares (RLS) algorithm was employed to calculate the time constant in real time. The control delay was estimated using an RLS designed based on a first-order differential equation. A backstepping steering controller was developed to calculate the desired steering angle using simplified error dynamics for reference path tracking. The control errors, specifically the lateral preview and yaw angle errors, were derived by calculating the path error between the current position and the waypoint. The performance of the proposed control algorithm was evaluated using the DC motor and CarMaker software 8.1.1(IPG Automotive, Karlsruhe, Germany) under scenarios involving sinusoidal input and four-curved loop and S-curved paths respectively. Full article
(This article belongs to the Special Issue Integrated Intelligent Vehicle Dynamics and Control)
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17 pages, 8396 KiB  
Article
Design and Testing of a Tractor Automatic Navigation System Based on Dynamic Path Search and a Fuzzy Stanley Model
by Bingbo Cui, Xinyu Cui, Xinhua Wei, Yongyun Zhu, Zhen Ma, Yan Zhao and Yufei Liu
Agriculture 2024, 14(12), 2136; https://doi.org/10.3390/agriculture14122136 - 25 Nov 2024
Cited by 15 | Viewed by 1440
Abstract
Smart agriculture development mainly depends on the intelligence and reliability of autonomous agricultural machinery. Automatic navigation systems (ANSs) play a key role in intelligent agricultural machinery design, as they not only reduce farmers’ workloads but also improve their land utilization rates. In this [...] Read more.
Smart agriculture development mainly depends on the intelligence and reliability of autonomous agricultural machinery. Automatic navigation systems (ANSs) play a key role in intelligent agricultural machinery design, as they not only reduce farmers’ workloads but also improve their land utilization rates. In this paper, a tractor ANS based on dynamic path search and a fuzzy Stanley model (FSM) was designed, and its capability for whole-field path tracking was tested. First, the tracking performance of the steering control module was validated after the automatic reconstruction of the tractor platform. Then, a navigation decision system was established based on a unified reference waypoint search framework, where the path generation for whole-field coverage was presented. Finally, the gain coefficient of the Stanley model (SM) was adjusted adaptively according to the tracking error by utilizing the fuzzy logic controller. Subsequently, the developed tractor ANS was tested in the field. The experiment’s results indicate that the FSM outperformed the SM in straight path tracking and whole-field path tracking. When the tractor traveled at a speed of 1 m/s, the maximum lateral tracking error for the straight path was 10 cm, and the average lateral tracking error was 5.2 cm, showing improvements of 16.7% and 10.3% compared to the SM. Whole-field autonomous navigation showed that the maximum lateral tracking error was improved from 34 cm for the SM to 27 cm for the FSM, a reduction of approximately 20.6%, illustrating the superiority of the FSM in the application of whole-field path tracking. As the maximum tracking error of whole-field autonomous navigation appears in the turning stage, where tractors often stop working, the designed ANS satisfies the requirements of a self-driving system for unmanned tractors. Full article
(This article belongs to the Section Agricultural Technology)
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18 pages, 5232 KiB  
Article
Vehicle and Pedestrian Traffic Signal Performance Measures Using LiDAR-Derived Trajectory Data
by Enrique D. Saldivar-Carranza, Jairaj Desai, Andrew Thompson, Mark Taylor, James Sturdevant and Darcy M. Bullock
Sensors 2024, 24(19), 6410; https://doi.org/10.3390/s24196410 - 3 Oct 2024
Viewed by 1964
Abstract
Light Detection and Ranging (LiDAR) sensors at signalized intersections can accurately track the movement of virtually all objects passing through at high sampling rates. This study presents methodologies to estimate vehicle and pedestrian traffic signal performance measures using LiDAR trajectory data. Over 15,000,000 [...] Read more.
Light Detection and Ranging (LiDAR) sensors at signalized intersections can accurately track the movement of virtually all objects passing through at high sampling rates. This study presents methodologies to estimate vehicle and pedestrian traffic signal performance measures using LiDAR trajectory data. Over 15,000,000 vehicle and 170,000 pedestrian waypoints detected during a 24 h period at an intersection in Utah are analyzed to describe the proposed techniques. Sampled trajectories are linear referenced to generate Purdue Probe Diagrams (PPDs). Vehicle-based PPDs are used to estimate movement level turning counts, 85th percentile queue lengths (85QL), arrivals on green (AOG), highway capacity manual (HCM) level of service (LOS), split failures (SF), and downstream blockage (DSB) by time of day (TOD). Pedestrian-based PPDs are used to estimate wait times and the proportion of people that traverse multiple crosswalks. Although vehicle signal performance can be estimated from several days of aggregated connected vehicle (CV) data, LiDAR data provides the ability to measure performance in real time. Furthermore, LiDAR can measure pedestrian speeds. At the studied location, the 15th percentile pedestrian walking speed was estimated to be 3.9 ft/s. The ability to directly measure these pedestrian speeds allows agencies to consider alternative crossing times than those suggested by the Manual on Uniform Traffic Control Devices (MUTCD). Full article
(This article belongs to the Section Radar Sensors)
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13 pages, 9196 KiB  
Article
Development of a Robotic Platform with Autonomous Navigation System for Agriculture
by Jamil de Almeida Baltazar, André Luiz de Freitas Coelho, Domingos Sárvio Magalhães Valente, Daniel Marçal de Queiroz and Flora Maria de Melo Villar
AgriEngineering 2024, 6(3), 3362-3374; https://doi.org/10.3390/agriengineering6030192 - 17 Sep 2024
Cited by 3 | Viewed by 2012
Abstract
The development of autonomous agricultural robots using a global navigation satellite system aided by real-time kinematics and an inertial measurement unit for position and orientation determination must address the accuracy, reliability, and cost of these components. This study aims to develop and evaluate [...] Read more.
The development of autonomous agricultural robots using a global navigation satellite system aided by real-time kinematics and an inertial measurement unit for position and orientation determination must address the accuracy, reliability, and cost of these components. This study aims to develop and evaluate a robotic platform with autonomous navigation using low-cost components. A navigation algorithm was developed based on the kinematics of a differential vehicle, combined with a proportional and integral steering controller that followed a point-to-point route until the desired route was completed. Two route mapping methods were tested. The performance of the platform control algorithm was evaluated by following a predefined route and calculating metrics such as the maximum cross-track error, mean absolute error, standard deviation of the error, and root mean squared error. The strategy of planning routes with closer waypoints reduces cross-track errors. The results showed that when adopting waypoints every 3 m, better performance was obtained compared to waypoints only at the vertices, with maximum cross-track error being 44.4% lower, MAE 64.1% lower, SD 39.4% lower, and RMSE 52.5% lower. This study demonstrates the feasibility of developing autonomous agricultural robots with low-cost components and highlights the importance of careful route planning to optimize navigation accuracy. Full article
(This article belongs to the Section Agricultural Mechanization and Machinery)
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