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A Convex Trajectory Planning Method for Autonomous Vehicles Considering Kinematic Feasibility and Bi-State Obstacles Avoidance Effectiveness

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2024年第7期73卷 9575-9590页

作者： Wang, Ying Wei, Chong Li, Shurong Sun, Junkai Cao, Jianfei Beijing Jiaotong Univ Sch Traff & Transportat MOT Key Lab Transport Ind Big Data Applicat Techno Beijing 100044 Peoples R China Jilin Univ Sch Mech & Aerosp Engn Changchun 130000 Peoples R China Beijing Inst Spacecraft Syst Engn Beijing 100044 Peoples R China

The Trajectory Planning Module is a key component of the Autonomous Driving System which is central to the realization and widespread use of Autonomous Vehicles. However, in the models adopted by mainstream trajectory planners, only crude representations of the geometrical sizes of vehicles are usually made, a limitation that cannot guarantee the kinematic feasibility of the driving process. But accounting for kinematic constraints will present a further challenge as the model itself will be non-convex due to the inherent angularity of vehicles. To cope with this challenge, a trajectory planning method considering kinematic feasibility based on the convex optimization framework is proposed. Instead of employing solving techniques that loosen non-convex effects, our method directly addresses the problem of convex kinematic feasibility by constructing a collision-free constraint regarding a vehicle's precise size and a variable boundary constraint regarding the vehicle's inherent limitation. Moreover, we present a "Bi-state Obstacles Avoidance" strategy designed to overcome the disadvantages in typical trajectory planners that only consider a static obstacle avoidance constraint in the path generation phase of trajectory planning. By introducing an external parameter "time", the staticization representation of dynamic obstacles can effectively be implemented, which greatly improves the ability to regulate velocity. The feasibility and effectiveness of the proposed new planner were tested using both simulated and real-world driving data, the results of which show that the proposed method can plan safe and efficient trajectories in real-time, an essential requirement for implementation in real-world autonomous vehicles.

关键词： Trajectory planning Kinematics Planning Trajectory Vehicle dynamics Safety Roads Autonomous vehicles trajectory planning kinematic feasibility Bi-State Obstacles Avoidance nonlinear program

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Leveraging Lazy Theta* Path Planning for UAV Pseudospectral Trajectory Optimization Initialization 18

Leveraging Lazy Theta* Path Planning for UAV Pseudospectral ...

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18th International Conference on Control Automation Robotics and Vision

作者： Boucek, Zdenek Flidr, Miroslav Straka, Ondrej Univ West Bohemia Pilsen Fac Appl Sci New Technol Informat Soc Res Ctr Plzen Czech Republic Univ West Bohemia Pilsen Fac Appl Sci Dept Cybernet Plzen Czech Republic

ISBN: (纸本)9798331518509;9798331518493

This paper examines the influence of initial guesses on trajectory planning for unmanned aerial vehicles (UAVs) formulated in terms of the optimal control problem (OCP). The OCP is solved numerically using the pseudospectral collocation method. Our approach leverages a path identified through Lazy Theta* and incorporates known constraints and a model of the UAV's behavior for the initial guess. Our findings indicate that a suitable initial guess has a beneficial influence on the planned trajectory and suggests promising directions for future research.

关键词： aerial robotics trajectory planning collocation method nonlinear program UAVs

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Autonomous Driving on Curvy Roads Without Reliance on Frenet Frame: A Cartesian-Based Trajectory Planning Method

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2022年第9期23卷 15729-15741页

作者： Li, Bai Ouyang, Yakun Li, Li Zhang, Youmin Hunan Univ Coll Mech & Vehicle Engn Changsha 410082 Hunan Peoples R China Tsinghua Univ Dept Automat BNRist Beijing 100084 Peoples R China Concordia Univ Dept Mech Ind & Aerosp Engn Montreal PQ H3G 1M8 Canada

Curvy roads are a particular type of urban road scenario, wherein the curvature of the road centerline changes drastically. This paper is focused on the trajectory planning task for autonomous driving on a curvy road. The prevalent on-road trajectory planners in the Frenet frame cannot impose accurate restrictions on the trajectory curvature, thus easily making the resultant trajectories beyond the ego vehicle's kinematic capability. Regarding planning in the Cartesian frame, selection-based methods suffer from the curse of dimensionality. By contrast, optimization-based methods in the Cartesian frame are more flexible to find optima in the continuous solution space, but the new challenges are how to tackle the intractable collision-avoidance constraints and nonconvex kinematic constraints. An iterative computation framework is proposed to accumulatively handle the complex constraints. Concretely, an intermediate problem is solved in each iteration, which contains linear and tractably scaled collision-avoidance constraints and softened kinematic constraints. Compared with the existing optimization-based planners, our proposal is less sensitive to the initial guess especially when it is not kinematically feasible. The efficiency of the proposed planner is validated by both simulations and real-world experiments. Source codes of this work are available at https://***/libai1943/CartesianPlanner.

关键词： Trajectory Roads Kinematics Trajectory planning Planning Autonomous vehicles Task analysis Trajectory planning computational optimal control nonlinear program Frenet frame autonomous vehicle

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A Drone Routing Problem for Ship Emission Detection Considering Simultaneous Movements

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ATMOSPHERE 2023年第2期14卷 373-373页

作者： Hu, Zhi-Hua Liu, Tian-Ci Tian, Xi-Dan Shanghai Maritime Univ Logist Res Ctr Shanghai 201306 Peoples R China

Offshore ships' emission has a tremendous environmental and healthy impact on the port cities and citizens, even though the Emission Control Area (ECA) policy imposes legislative constraints on the ships. It is challenging to detect ships with illegal emissions using traditional administrative and enforcement methods. In addition to a system of ships' emission detection, a drone-based detection system is investigated, and a drone routing problem is formulated considering the distinct feature: the drone flying while ships move simultaneously. A nonlinear program is devised, and heuristics algorithms are developed to solve the test instances. The numerical experiments demonstrate the feasibility and advantages of using drone routing solutions. The solution algorithm can solve large samples with 50 ships within 2 s, and the computing time is almost linear to the number of ships. The proposed model and algorithms should contribute to drone-based ship emission detection and a featured routing problem.

关键词： drone routing problem ship emissions emission control area evolutionary algorithm nonlinear program

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Road Boundary Modeling for Autonomous Bus Docking Subject to Rectangular Geometry Constraints

Road Boundary Modeling for Autonomous Bus Docking Subject to...

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European Control Conference (ECC)

作者： Elawad, Amal Murgovski, Nikolce Jonasson, Mats Sjoberg, Jonas Chalmers Univ Technol Dept Elect Engn SE-41296 Gothenburg Sweden Chalmers Univ Technol Dept Mech & Maritime Sci SE-41296 Gothenburg Sweden

ISBN: (纸本)9789463842365

This paper studies the optimization problem of autonomous bus parallel parking subjected to rectangular geometry constraints. The parking space is a non-smooth and non-convex irregular polygon. We propose a novel method for modeling geometry constraints, which allows using the exact non-smooth parking space, while still being able to formulate the problem as a smooth nonlinear program. The focus of this paper is to compare our method to two other approaches of modeling rectangular geometry constraints, where one uses mixed-integers while the other approximates the rectangle as a smooth function. We show that our novel method prevents collisions and requires shorter computation time, where collision constraints are imposed on a limited number of points on the vehicle contour.

关键词： autonomous bus parking path planning rectangle polygon geometry constraints OCP nonlinear program direct multiple-shooting CASADI

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Research on Sampling Inspection Procedures for Bank Service Time Based on Bayes Method

Research on Sampling Inspection Procedures for Bank Service ...

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10th International Conference on Applied Human Factors and Ergonomics (AHFE) / AHFE International Conference on Human Aspects of Advanced Manufacturing / AHFE International Conference on Advanced Production Management and Process Control (APMPC)

作者： Wang, Jingjing Wang, Haitao Zhang, Fan Zhao, Chao Wu, Gang Zhao, Jing China Natl Inst Standardizat Beijing Peoples R China Capital Normal Univ Sch Math Sci Beijing Peoples R China

ISBN: (纸本)9783030204945;9783030204938

Using the previous data and experience of the service time provided by bank tellers to customers, this paper constructs a bank service time sampling inspection program based on Bayes method, and re-formulate the sampling plan on;kTHORN for the mean value. In this paper, we use nonlinear programming theory to determine (n, k) in the "k"-type sampling plan. Then, compared with the conventional sampling inspection program, it is found that the sampling inspection plan for banking service time based on Bayes method requires fewer samples, which is valuable for reducing the sampling cost and strength.

关键词： Banking service time Hypothesis testing Bayes theory nonlinear program

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NEW ADAPTIVE BARZILAI-BORWEIN STEP SIZE AND ITS APPLICATION IN SOLVING LARGE-SCALE OPTIMIZATION PROBLEMS

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ANZIAM JOURNAL 2019年第1期61卷 76-98页

作者： Li, Ting Wan, Zhong Cent S Univ Sch Math & Stat Changsha Hunan Peoples R China

We propose a new adaptive and composite Barzilai-Borwein (BB) step size by integrating the advantages of such existing step sizes. Particularly, the proposed step size is an optimal weighted mean of two classical BB step sizes and the weights are updated at each iteration in accordance with the quality of the classical BB step sizes. Combined with the steepest descent direction, the adaptive and composite BB step size is incorporated into the development of an algorithm such that it is efficient to solve large-scale optimization problems. We prove that the developed algorithm is globally convergent and it R-linearly converges when applied to solve strictly convex quadratic minimization problems. Compared with the state-of-the-art algorithms available in the literature, the proposed step size is more efficient in solving ill-posed or large-scale benchmark test problems.

关键词： nonlinear program step size algorithm convergence large-scale optimization

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LEAST SPARSITY OF p-NORM BASED OPTIMIZATION PROBLEMS WITH p>1

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SIAM JOURNAL ON OPTIMIZATION 2018年第3期28卷 2721-2751页

作者： Shen, Jinglai Mousavi, Seyedahmad Univ Maryland Baltimore Cty Dept Math & Stat Baltimore MD 21250 USA

Motivated by l(p)-optimization arising from sparse optimization, high-dimensional data analytics and statistics, this paper studies sparse properties of a wide range of p-norm based optimization problems with p>1, including generalized basis pursuit, basis pursuit denoising, ridge regression, and elastic net. It is well known that when p>1, these optimization problems lead to less sparse solutions. However, the quantitative characterization of the adverse sparse properties is not available. This paper shows how to exploit optimization and matrix analysis techniques to develop a systematic treatment of a broad class of p-norm based optimization problems for a general p>1 and show that their optimal solutions attain full support, and thus have the least sparsity, for almost all measurement matrices and measurement vectors. Comparison to l(p)-optimization with 0

关键词： sparse optimization lp-optimization convex optimization nonlinear program

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Exact two steps SOCP/SDP formulation for a modified conic trust region subproblem

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OPTIMIZATION LETTERS 2017年第8期11卷 1691-1697页

作者： Salahi, Maziar Univ Guilan Fac Math Sci Rasht Iran

In this paper, we study a modified version of the conic trust region subproblem which arises within a class of nonlinear programming algorithms. First using a variant of S-Lemma, we give an SOCP/SDP formulation which gives its optimal objective value. Then using the parametrization approach of Dinkelbach and the known exact SOCP/SDP relaxation of the extended trust region subproblem, we find its optimal solution. Finally, some preliminary numerical results are given.

关键词： Conic trust region subproblem nonlinear program S-lemma Semidefinite program Second order cone program

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Outer Approximation Algorithm for One Class of Convex Mixed-Integer nonlinear programming Problems with Partial Differentiability

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JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2015年第2期167卷 644-652页

作者： Wei, Zhou Ali, M. Montaz Yunnan Univ Dept Math Kunming 650091 Peoples R China Univ Witwatersrand Sch Computat & Appl Math ZA-2050 Johannesburg South Africa

In this paper, we mainly study one convex mixed-integer nonlinear programming problem with partial differentiability and establish one outer approximation algorithm for solving this problem. With the help of subgradients, we use the outer approximation method to reformulate this convex problem as one equivalent mixed-integer linear program and construct an algorithm for finding optimal solutions. The result on finite steps convergence of the algorithm is also presented.

关键词： MINLP Outer approximation Subgradient nonlinear program

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