Safe Motion Planning and Control Framework for Automated Vehicles with Zonotopic TRMPC

Model mismatches can cause multi-dimensional uncertainties for the receding horizon control strategies of automated vehicles(AVs).The uncertainties may lead to potentially hazardous behaviors when the AV tracks ideal trajectories that are individually optimized by the AV's planning layer.To address this issue,this study proposes a safe motion planning and control(SMPAC)framework for AVs.For the control layer,a dynamic model including multi-dimensional uncertainties is established.A zonotopic tube-based robust model predictive control scheme is proposed to constrain the uncertain system in a bounded minimum robust positive invariant set.A flexible tube with varying cross-sections is constructed to reduce the controller conservatism.For the planning layer,a concept of safety sets,representing the geometric boundaries of the ego vehicle and obstacles under uncertainties,is proposed.The safety sets provide the basis for the subsequent evaluation and ranking of the generated trajectories.An efficient collision avoidance algorithm decides the desired trajectory through the intersection detection of the safety sets between the ego vehicle and obstacles.A numerical simulation and hardware-in-the-loop experiment validate the effectiveness and real-time performance of the SMPAC.The result of two driving scenarios indicates that the SMPAC can guarantee the safety of automated driving under multi-dimensional uncertainties.

MPC-based Motion Planning and Control Enables Smarter and Safer Autonomous Marine Vehicles:Perspectives and a Tutorial Survey

Autonomous marine vehicles(AMVs)have received considerable attention in the past few decades,mainly because they play essential roles in broad marine applications such as environmental monitoring and resource exploration.Recent advances in the field of communication technologies,perception capability,computational power and advanced optimization algorithms have stimulated new interest in the development of AMVs.In order to deploy the constrained AMVs in the complex dynamic maritime environment,it is crucial to enhance the guidance and control capabilities through effective and practical planning,and control algorithms.Model predictive control(MPC)has been exceptionally successful in different fields due to its ability to systematically handle constraints while optimizing control performance.This paper aims to provide a review of recent progress in the context of motion planning and control for AMVs from the perceptive of MPC.Finally,future research trends and directions in this substantial research area of AMVs are highlighted.

Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation

Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment.

Information System for Land-Use Planning and Management

In order to maintain the overall social interest in land use and improve the level of land administration, an information system for land-use planning and management （ISLUPM） was established, which is composed of presentation layer, business logic layer and data layer in the general structure. The application support platform of the ISLUPM, built based on COM, COM ＋ and .NET standard components, includes data engine, data management, assemblies, components management, operation management, and interface. Then, an elaboration was made on major functions of the ISLUPM, such as planning revision scheme, planning operation flow, digital processing, thematic analysis and inquiry, and preparation of the chart of reserved land resources. The developed system has been successfully applied to the land-use planning and management work of Longquanyi District, Chengdu, China. It may provide a reference for development of geographic information system （GIS） for land and resources.

Development of ground control station and path planning for autonomous MUAV

For autonomous MUAV,the Ground Control Station(GCS)including hardware and modular software programming such as control modular,navigation modular,display modular and monitor modular becomes important equipment to be developed.This paper emphasizes the global planning and the local replanning arithmetic based on three-dimensional velocity potential field for the moving threats.During the test on the ground and in the sky,GCS show the remote sensing information precisely and send the control command in time.The system can be used to assist in the function of autonomous complex task for MUAV.

Planning and Control of COP-Switch-Based Planar Biped Walking

Efficient walking is one of the main goals of researches on biped robots. A feasible way is to translate the understanding from human walking into robot walking, for example, an artificial control approach on a human like walking structure. In this paper, a walking pattern based on Center of Pressure （COP） switched and modeled after human walking is introduced firstly. Then, a parameterization method for the proposed walking gait is presented. In view of the complication, a multi-space planning method which divides the whole planning task into three sub-spaces, including simplified model space, work space and joint space, is proposed. Furthermore, a finite-state-based control method is also developed to implement the proposed walking pattern. The state switches of this method are driven by sensor events. For convincing verification, a 2D simulation system with a 9-1ink planar biped robot is developed. The simulation results exhibit an efficient walking gait.

Local Path Planning and Tracking Control of Vehicle Collision Avoidance System

Automotive collision avoidance technology can effectively avoid the accidents caused by dangerous traffic conditions or driver's manipulation errors.Moreover,it can promote the development of autonomous driving for intelligent vehicle in intelligent transportation.We present a collision avoidance system,which is composed of an evasive trajectory planner and a path following controller.Considering the stability of the vehicle in the conflict-free process,the evasive trajectory planner is designed by polynomial parametric method and optimized by genetic algorithm.The path following controller is proposed to make the car drive along the designed path by controlling the vehicle's lateral movement.Simulation results show that the vehicle with the proposed controller has good stability in the collision process,and it can ensure the vehicle driving in accordance with the planned trajectory at different speeds.The research results can provide a certain basis for the research and development of automotive collision avoidance technology.

Locomotion Optimization and Manipulation Planning of a Tetrahedron-Based Mobile Mechanism with Binary Control

Locomotion and manipulation optimization is essential for the performance of tetrahedron-based mobile mechanism. Most of current optimization methods are constrained to the continuous actuated system with limited degree of freedom(DOF), which is infeasible to the optimization of binary control multi-DOF system. A novel optimization method using for the locomotion and manipulation of an 18 DOFs tetrahedron-based mechanism called 5-TET is proposed. The optimization objective is to realize the required locomotion by executing the least number of struts.Binary control strategy is adopted, and forward kinematic and tipping dynamic analyses are performed, respectively.Based on a developed genetic algorithm(GA), the optimal number of alternative struts between two adjacent steps is obtained as 5. Finally, a potential manipulation function is proposed, and the energy consumption comparison between optimal 5-TET and the traditional wheeled robot is carried out. The presented locomotion optimization and manipulation planning enrich the research of tetrahedron-based mechanisms and provide the instruction to the successive locomotion and operation planning of multi-DOF mechanisms.

Post-Impact Motion Planning and Tracking Control for Autonomous Vehicles

There is an increasing awareness of the need to reduce traffic accidents and fatality due to vehicle collision.Post-impact hazards can be more serious as the driver may fail to maintain effective control after collisions.To avoid subsequent crash events and to stabilize the vehicle,this paper proposes a post-impact motion planning and stability control method for autonomous vehicles.An enabling motion planning method is proposed for post-impact situations by combining the polynomial curve and artificial potential field while considering obstacle avoidance.A hierarchical controller that consists of an upper and a lower controller is then developed to track the planned motion.In the upper controller,a time-varying linear quadratic regulator is presented to calculate the desired generalized forces.In the lower controller,a nonlinear-optimization-based torque allocation algorithm is proposed to optimally coordinate the actuators to realize the desired generalized forces.The proposed scheme is verified under comprehensive driving scenarios through hardware-in-loop tests.

Leader trajectory planning method considering constraints of formation controller

To ensure safe flight of multiple fixed-wing unmanned aerial vehicles(UAVs)formation,considering trajectory planning and formation control together,a leader trajectory planning method based on the sparse A*algorithm is introduced.Firstly,a formation controller based on prescribed performance theory is designed to control the transient and steady formation configuration,as well as the formation forming time,which not only can form the designated formation configuration but also can guarantee collision avoidance and terrain avoidance theoretically.Next,considering the constraints caused by formation controller on trajectory planning such as the safe distance,turn angle and step length,as well as the constraint of formation shape,a leader trajectory planning method based on sparse A^(*)algorithm is proposed.Simulation results show that the UAV formation can arrive at the destination safely with a short trajectory no matter keeping the formation or encountering formation transformation.

A MySQL-Based Software System of Urban Land Planning Database of Shanghai in China

With the development of the digital city,data and data analysis have become more and more important.The database is the foundation of data analysis.In this paper,the software system of the urban land planning database of Shanghai in China is developed based on MySQL.The conceptual model of the urban land planning database is proposed,and the entities,attributes and connections of this model are discussed.Then the E-R conceptual model is transformed into a logical structure,which is supported by the relational databasemanagement system(DBMS).Based on the conceptual and logical structures,by using Spring Boot as the back-end framework and using MySQL and Java API as the development tools,a platformwith datamanagement,information sharing,map assistance and other functions is established.The functionalmodules in this platformare designed.The results of J Meter test show that the DBMS can add,store and retrieve information data stably,and it has the advantages of fast response and low error rate.The software system of the urban land planning database developed in this paper can improve the efficiency of storing and managing land data,eliminating redundant data and sharing data.

Energy-Optimal Braking Control Using a Double-Layer Scheme for Trajectory Planning and Tracking of Connected Electric Vehicles

Most researches focus on the regenerative braking system design in vehicle components control and braking torque distribution,few combine the connected vehicle technologies into braking velocity planning.If the braking intention is accessed by the vehicle-to-everything communication,the electric vehicles(EVs)could plan the braking velocity for recovering more vehicle kinetic energy.Therefore,this paper presents an energy-optimal braking strategy(EOBS)to improve the energy efficiency of EVs with the consideration of shared braking intention.First,a double-layer control scheme is formulated.In the upper-layer,an energy-optimal braking problem with accessed braking intention is formulated and solved by the distance-based dynamic programming algorithm,which could derive the energy-optimal braking trajectory.In the lower-layer,the nonlinear time-varying vehicle longitudinal dynamics is transformed to the linear time-varying system,then an efficient model predictive controller is designed and solved by quadratic programming algorithm to track the original energy-optimal braking trajectory while ensuring braking comfort and safety.Several simulations are conducted by jointing MATLAB and CarSim,the results demonstrated the proposed EOBS achieves prominent regeneration energy improvement than the regular constant deceleration braking strategy.Finally,the energy-optimal braking mechanism of EVs is investigated based on the analysis of braking deceleration,battery charging power,and motor efficiency,which could be a guide to real-time control.

Optimal control based coordinated taxiing path planning and tracking for multiple carrier aircraft on flight deck

Coordinated taxiing planning for multiple aircraft on flight deck is of vital importance which can dramatically improve the dispatching efficiency.In this paper,first,the coordinated taxiing path planning problem is transformed into a centralized optimal control problem where collision-free conditions and mechanical limits are considered.Since the formulated optimal control problem is of large state space and highly nonlinear,an efficient hierarchical initialization technique based on the Dubins-curve method is proposed.Then,a model predictive controller is designed to track the obtained reference trajectory in the presence of initial state error and external disturbances.Numerical experiments demonstrate that the proposed“offline planningþonline tracking”framework can achieve efficient and robust coordinated taxiing planning and tracking even in the presence of initial state error and continuous external disturbances.

Cognitive Granular-Based Path Planning and Tracking for Intelligent Vehicle with Multi-Segment Bezier Curve Stitching

Unmanned vehicles are currently facing many difficulties and challenges in improving safety performance when running in complex urban road traffic environments,such as low intelligence and poor comfort perfor-mance in the driving process.The real-time performance of vehicles and the comfort requirements of passengers in path planning and tracking control of unmanned vehicles have attracted more and more attentions.In this paper,in order to improve the real-time performance of the autonomous vehicle planning module and the comfort requirements of passengers that a local granular-based path planning method and tracking control based on multi-segment Bezier curve splicing and model predictive control theory are pro-posed.Especially,the maximum trajectory curvature satisfying ride comfort is regarded as an important constraint condition,and the corresponding curvature threshold is utilized to calculate the control points of Bezier curve.By using low-order interpolation curve splicing,the planning computation is reduced,and the real-time performance of planning is improved,com-pared with one-segment curve fitting method.Furthermore,the comfort performance of the planned path is reflected intuitively by the curvature information of the path.Finally,the effectiveness of the proposed control method is verified by the co-simulation platform built by MATLAB/Simulink and Carsim.The simulation results show that the path tracking effect of multi-segment Bezier curve fitting is better than that of high-order curve planning in terms of real-time performance and comfort.

Trajectory Planning and Optimal Lateral Stability Control under Multiple Barriers for Intelligent Vehicle

Based on analysis and evaluation on the circular, cosine type, constant-speed offset type and ladder type lane change trajectory, this paper proposes an intelligent vehicle lane change trajectory model under multiple barriers, proposes its dynamic constraints in the light of the cellular automata theory, obtains the desired lane change trajectory using this method, and finally changes into a simple coefficient selection problem. Secondly, based on the quadratic optimal control theory, this paper proposes a state space analysis method of intelligent vehicle lateral control, and designs an optimal controller for lateral stability of H2 vehicles. The computer simulation results show that compared with other vehicle trajectory methods, the method in this paper is able to simply and rapidly describe the trajectory, and can describe the intelligent vehicle lane change trajectory under a variety of situations, wherein the controller is reliable and capable of fast convergence.

MODELING AND IMPLEMENTATION OF A DISTRIBUTED SHOP FLOOR MANAGEMENT AND CONTROL SYSTEM

Adopting distributed control architecture is the important developmentdirection for shop floor management and control system, is also the requirement of making it agile,intelligent and concurrent. Some key problems in achieving distributed control architecture areresearched. An activity model of shop floor is presented as the requirement definition of theprototype system. The multi-agent based software architecture is constructed. How the core part inshop floor management and control system, production plan and scheduling is achieved. Thecooperation of different agents is illustrated. Finally, the implementation of the prototype systemis narrated.

Testing of Decision Making Tools for Village Land Use Planning and Natural Resources Management in Kilimanjaro Region

This paper focuses on participatory testing of decision making tools (DMTs) at village level to assist in development of land use plans (LUPs) for sustainable land management (SLM) in Kilimanjaro Region, Tanzania. Data were collected using conditional surveys through key informant interviews with the project’s district stakeholders in each district, focused group discussions with selected villagers and participatory mapping of natural resources. Soil health, land degradation, carbon stock, and hydrological conditions were assessed in the seven pilot villages in all seven districts using DMTs as part of testing and validation. Results indicated soils of poor to medium health, and land degradation as portrayed by gullies and wind erosion in lowlands and better in uplands. Carbon and forest disturbance status could not be assessed using one-year data but hydrological analysis revealed that water resources were relatively good in uplands and poor in the lowlands. Challenges with regard to land use include increased gully erosion, decreased stream flow, reduced vegetation cover due to shifting from coffee with tree sheds to annual crops farming, cultivation near water sources, and overgrazing. Empowering the community with decision making tools at village level is essential to ensure that village land uses are planned in a participatory manner for sustainable land and natural resources management in Kilimanjaro and other regions in Tanzania.

Development of an Integrated System to Enhance Spatial Data Processing & Management for Planning Authorities

In a world where there is constant data generation and processing, the need for an integrated system cannot be overemphasized. The systems that enable storage of large amounts of spatial data and must be made available to multiple users in real time. Studies have shown that standalone desktop spatial systems are often rigid and inflexible to support multiple data processing or demands from multiple users. The integrated spatial management system was designed to address the above highlighted challenges by bringing enhanced possibilities of utilization of spatial data though improving accessibility, visualization, and processing spatial information. The present work employed a mixed approach of qualitative and quantitative techniques to obtain the desired result. Qualitative data collection tools were used to collect field data required to design the prototype. The research sought to establish whether the integrated systems are in use by the targeted institutions, the findings highlighted that 71.4% have no integrated spatial data systems while 28.6% have partial-integrated systems. An overview of the architecture of integrated spatial systems consists of a well distributed database linked to multiple tools and platforms to query both the spatial and non-spatial data. The WEB-GIS and Mobile GIS interfaces were developed to allow multiple users to access information through the web in real time and data collection, respectively.

Ecological and environmental characteristics and management planning of Mawei Economic Development District

The natural and social background of the district was described, and the major ecological and environmental problems were analysed. The measures and planning for the ecological and environmental protection were recommended. Systematic analysis method and environmental mathematical models were suggested to be used for the ecological and environmental general planning in this paper.