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A nonlinear programing model for collision-free lane-change trajectory planning based on vehicle-to-vehicle communication

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JOURNAL OF TRANSPORTATION SAFETY & SECURITY 2021年第9期13卷 936-956页

作者： Wei, Chong Wang, Ying Asakura, Yasuo Ma, Lu Beijing Jiaotong Univ Sch Traff & Transportat MOT Key Lab Transport Ind Big Data Applicat Techn Beijing 100044 Peoples R China Tokyo Inst Technol Dept Civil & Environm Engn Tokyo Japan

This study focuses on the trajectory planning problem for automatic lane-change maneuvers, for which we propose a nonlinear programing model to generate the collision-avoidance lane-change trajectory in a spatiotemporal space. In this model, we regard a lane-change trajectory as the combination of a lane-change path and its velocity profiles. Based on the polynomial curve, the lane-change path is planned first in 2-dimensional Cartesian coordinates to connect the initial position with final position, and then a nonlinear mathematical programing model is used to generate the velocity profiles for maintaining the driving safety and comfort. To solve the nonlinear model efficiently, we design an inverse strategy to set the initial guess that can coordinate with the discrete scheme of the trajectory planning problem. Moreover, as the vehicle shifts from a lane-change maneuver to a car-following maneuver at the end of the lane-change process, the planned final acceleration is constrained from the car-following model. Finally, a series of numerical examples are provided, and the results indicate that the automated vehicle can drive along the planned lane-changing trajectory safely and efficiently.

关键词： automated lane-change trajectory planning nonlinear programing car-following model constrained optimization

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A nonlinear programing model for optimized sortie allocation.

A nonlinear programing model for optimized sortie allocation...

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作者： Klaus Paul Wirths Naval Postgraduate School

学位级别：硕士

The United States Air Force uses a nonlinear programming model to assess the utilization of weapons and sorties needed to achieve a maximum value of destroyed targets in a multi-period, Theater-Level conflict. The current model is modified by con- straining the consumption of weapons. Alternate objective functions are introduced. Their meaning and influence on the optimization is compared. An increase in the worth of destroyed targets is gained if the model can more flexibly utilize weapons than is currently the case. The optimization can be further improved if all time periods are considered simultaneously while assigning sorties to targets, rather than the current myopic approach.

关键词： Heavy Attack nonlinear programing optimization global optimzation. sortie allocation

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Maximizing Social Welfare in Micro-grids to Provide an Smooth Daily Load Profile Using nonlinear programing at Scheduled Operation

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INTERNATIONAL JOURNAL OF RENEWABLE ENERGY RESEARCH 2016年第3期6卷 930-940页

作者： Momen, Shirin Nikoukar, Javad Islamic Azad Univ Saveh Branch Coll Elect Engn Dept Engn Saveh Iran

Micro-grids are consisted of some interconnected networks such as distributed energy systems (resources and Loads) which are able to operate in gird connected and islanding modes. According to different loads in terms of feeding priority, consumers can help Micro-grid control center (MGCC) to do their best optimized scheduled operations. Then it could provide power for critical loads by controlling interruptible loads or displacement of load at different prices. Demand response (DR) plays an important role at electricity market in order to balance power generation and demand level required. Overall consumer pricing can be very useful in reduction of the operating costs, especially when market prices are high. In addition, by using this method, consumers can reduce their payment for less important loads. In this paper, the optimal operation of micro-grid in presence of demand response will be investigated in order to increase social welfare and flattening the load curve at an acceptable level. Multi-objective optimization problem will be solved by Epsilon limitation method with nonlinear programming (NLP) using General Algebraic Model System (GAMS) software package. The proposed algorithm will be implemented on a 17 bus micro-grid. The results indicate that proposed algorithm has ability to improve of micro-grid performance in scheduled operations.

关键词： Daily Load Profile Maximizing Social Welfare nonlinear programing Scheduled Operation

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A feasible SQP method for nonlinear programming

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APPLIED MATHEMATICS AND COMPUTATION 2010年第11期215卷 3956-3969页

作者： Zhu, Zhibin Zhang, Weidong Geng, Zhenjie Guilin Univ Elect Technol Sch Math & Comp Sci Guilin 541004 Peoples R China

In this paper, a new SQP algorithm is presented to solve the general nonlinear programs with mixed equality and inequality constraints. Quoted from P. Spellucci (see [9]), this method maybe be named sequential equality constrained quadratic programming (SECQP) algorithm. Per single iteration, based on an active set strategy (see [9]), this SECQP algorithm requires only to solve equality constrained quadratic programming subproblems or system of linear equations. The theoretical analysis shows that global and superlinear convergence can be induced under some suitable conditions. (C) 2009 Elsevier Inc. All rights reserved.

关键词： nonlinear programing SQP method Active set strategies Global convergence Superlinear convergence

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Trajectory planning for autonomous vehicle based on window-constrained Pearl model

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2024年第7期238卷 2055-2065页

作者： Lu, Xiao Liu, Guang Liu, Haiqing Rai, Laxmisha Wang, Haixia Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao Peoples R China Shandong Univ Sci & Technol Coll Elect & Informat Engn Qingdao Peoples R China Shandong Univ Sci & Technol Coll Elect Engn & Automat 579 Qianwangang Rd Qingdao 266590 Peoples R China

Speed guidance is a significant application in driver assistance system or driverless automated system. Considering the traditional Pearl model-based trajectory planning, this paper proposes an improved method based on window constraints to enhance the rationality at intersection positions. To solve the problem, where the slopes of traditional time-distance Pearl curve at the two boundaries generate relatively low values and which is not in accordance with the actual situation, a new window constraint is used to guide the vehicle passing through the intersection at a high speed. Regarding the new window constraints, together with the maximum speed, tolerating accelerated speed constraints, and traffic signal length constraints, a multi-variable and single objective optimization improved nonlinear programing scheme is applied to obtain the most comfort trajectory of passengers for speed guidance. Simulation results show that, the proposed method presents better performance in traveling time and trajectory smoothness compared with the traditional method under different initial vehicle speeds at upstream intersections and signal offset cases.

关键词： Speed guidance trajectory planning Pearl model nonlinear programing

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An optimization neural network model with time-dependent and lossy dynamics

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NEUROCOMPUTING 2002年第1-4期48卷 53-62页

作者： Heszberger, Z Bíró, J Budapest Univ Technol & Econ High Speed Networks Lab Dept Telecommun & Telemat H-1117 Budapest Hungary

The paper is concerned with continuously operating optimization neural networks with lossy dynamics. As the main feature of the neural model, the time-varying nature of neuron activation functions is introduced. The model presented is general in the sense that it covers the cases of neural networks for combinatorial optimization (Hopfield-like networks) and neural models for optimization problems with continuous decision variables (i.e., the Kennedy and Chua neural network). Besides the rigorous stability analysis of the proposed neural network, we also show how to derive lossy versions of improved Hopfield neural models from it and explore the relations to other optimization neural systems. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： optimization neural networks continuously operating neural networks Hopfield-like neural networks nonlinear programing

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A Coordinate Optimization Approach or Concurrent Design

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2019年第7期64卷 2913-2920页

作者： Peng, Yijie Huang, Edward Xu, Jie Shi, Zhongshun Chen, Chun-Hung Peking Univ Coll Engn Dept Ind Engn & Management Beijing 100080 Peoples R China George Mason Univ Dept Syst Engn & Operat Res Fairfax VA 22030 USA Univ Wisconsin Dept Ind & Syst Engn Madison WI 53706 USA

In concurrent design (CCD), multiple design teams execute their tasks simultaneously and then exchange information to update their designs. The process then iterates until the termination criterion is met. When properly controlled and executed, CCD can be an effective method to shorten the time in product development for complex and large-scale projects thanks to its parallel nature. In this note, we propose a coordinate optimization framework to model and control team coordination through information sharing in CCD. It can be shown that under a certain convexity assumption, CCD converges to a globally optimal design if the information sharing intensity is smaller than a certain threshold. Numerical experiments substantiate the theoretical results.

关键词： Concurrent design (CCD) nonlinear programing

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Optimal management of naturally regenerating uneven-aged forests

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第3期256卷 886-900页

作者： Sinha, Ankur Ramo, Janne Malo, Pekka Kallio, Markku Tahvonen, Olli Indian Inst Management Ahmedabad Prod & Quantitat Methods Ahmadabad 380015 Gujarat India Aalto Univ Sch Business Dept Informat & Serv Econ POB 21220 Helsinki 00076 Finland Univ Helsinki Dept Forest Sci POB 27 FI-00014 Helsinki Finland

A shift from even-aged forest management to uneven-aged management practices leads to a problem rather different from the existing straightforward practice that follows a rotation cycle of artificial regeneration, thinning of inferior trees and a clearcut. A lack of realistic models and methods suggesting how to manage uneven-aged stands in a way that is economically viable and ecologically sustainable creates difficulties in adopting this new management practice. To tackle this problem, we make a two-fold contribution in this paper. The first contribution is the proposal of an algorithm that is able to handle a realistic uneven-aged stand management model that is otherwise computationally tedious and intractable. The model considered in this paper is an empirically estimated size-structured ecological model for uneven-aged spruce forests. The second contribution is on the sensitivity analysis of the forest model with respect to a number of important parameters. The analysis provides us an insight into the behavior of the uneven-aged forest model. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Natural resources Forest management nonlinear programing Evolutionary algorithms

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Dual Dynamic programing with cut selection: Convergence proof and numerical experiments

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第1期258卷 47-57页

作者： Guigues, Vincent Fundacao Getulio Vargas Sch Appl Math 190 Praia Botafogo BR-22250900 Rio De Janeiro Brazil

We consider convex optimization problems formulated using dynamic programing equations. Such problems can be solved using the Dual Dynamic programing algorithm combined with the Level 1 cut selection strategy or the Territory algorithm to select the most relevant Benders cuts. We propose a limited memory variant of Level 1 and show the convergence of DDP combined with the Territory algorithm, Level 1 or its variant for nonlinear optimization problems. In the special case of linear programs, we show convergence in a finite number of iterations. Numerical simulations illustrate the interest of our variant and show that it can be much quicker than a simplex algorithm on some large instances of portfolio selection and inventory problems. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Dynamic programing nonlinear programing Decomposition algorithms Dual Dynamic programing Pruning methods

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Automatic ship berthing using artificial neural network trained by consistent teaching data using nonlinear programming method

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2013年第10期26卷 2287-2304页

作者： Ahmed, Yaseen Adnan Hasegawa, Kazuhiko Osaka Univ Grad Sch Engn 2-1 Yamadaoka Suita Osaka Japan Dept Naval Architecture & Ocean Engn Div Global Architecture Suita Osaka Japan

Ship handling during berthing is considered as one of the most sophisticated tasks that a ship master has to face. The presence of current and wind make it even more complicated to execute, especially when ship approaches to a pier in low speed. To deal with such phenomenon, only experienced human brain decides the necessary action taken depending on situation demand. So automation in berthing is still far beyond imagination. But, if the human brain can be replicated by any suitable artificial intelligence technique to perform the same action that human brain does during berthing, then automatic ship berthing is possible. In this research artificial neural network is used for that purpose. To enhance its learnability, consistent teaching data based on the virtual window concept are created to ensure optimal steering with the help of nonlinear programming language (NPL) method. Then instead of centralized controller, two separate feed forward neural networks are trained using Lavenberg-Marquardt algorithm in backpropagation technique for command rudder angle and propeller revolution output respectively. The trained ANNs are then verified for their workability in no wind condition. On the other hand, separate ANNs are trained with reconstructed teaching data considering gust wind disturbances. To deal with any abrupt condition, ANN followed by PD controller is also introduced in case of command rudder angle output whose effectiveness is well verified not only for teaching data but also in case of non-teaching data and different gust wind distributions. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Artificial neural network PD controller Gust wind nonlinear programing

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