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Shared Steering Torque Control for Lane Change Assistance: A stochastic Game-Theoretic Approach

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2019年第4期66卷 3093-3105页

作者： Ji, Xuewu Yang, Kaiming Na, Xiaoxiang Lv, Chen Liu, Yahui Tsinghua Univ State Key Lab Automot Safety & Energy Beijing 100084 Peoples R China Univ Cambridge Dept Engn Cambridge CB2 1PZ England Nanyang Technol Univ Sch Mech & Aerosp Engn Singapore 639798 Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

The challenging issue of "human-machine copilot" opens up a new frontier to enhancing driving safety. However, driver-machine conflicts and uncertain driver/external disturbances are significant problems in cooperative steering systems, which degrade the system's path-tracking ability and reduce driving safety. This paper proposes a novel stochastic game-based shared control framework to model the steering torque interaction between the driver and the intelligent electric power steering (IEPS) system. A six-order driver-vehicle dynamic system, including driver/external uncertainty, is established for path-tracking. Then, the affine linear-quadratic-based path-tracking problem is proposed to model the maneuvers of the driver and IEPS. Particularly, the feedback Nash and Stackelberg frameworks to the affine-quadratic problem are derived by stochastic dynamic programming. Two cases of copilot lane change driving scenarios are studied via computer simulation. The intrinsic relation between the stochastic Nash and Stackelberg strategies is investigated based on the results. And the steering-in-the-loop experiment reveals the potential of the proposed shared control framework in handling driver-IEPS conflicts and uncertain driver/external turbulence. Finally, the copiloting experiments with a human driver further demonstrate the rationality of the game-based pattern between both the agents.

关键词： Affine-quadratic game driver-machine conflicting shared steering control stochastic dynamic programming

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Uncertainty Quantification in Water Resource Systems Modeling: Case Studies from India

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WATER 2020年第6期12卷 1793-1793页

作者： Rehana, Shaik Rajulapati, Chandra Rupa Ghosh, Subimal Karmakar, Subhankar Mujumdar, Pradeep Int Inst Informat Technol Hyderabad Lab Spatial Informat Hyderabad 500032 India Univ Saskatchewan Ctr Hydrol Saskatoon SK S7N 1K2 Canada Indian Inst Technol Dept Civil Engn Mumbai 400076 Maharashtra India Indian Inst Technol Environm Sci & Engn Dept Mumbai 400076 Maharashtra India Indian Inst Sci Interdisciplinary Ctr Water Res Dept Civil Engn Bangalore 520011 Karnataka India

Regional water resource modelling is important for evaluating system performance by analyzing the reliability, resilience and vulnerability criteria of the system. In water resource systems modelling, several uncertainties abound, including data inadequacy and errors, modeling inaccuracy, lack of knowledge, imprecision, inexactness, randomness of natural phenomena, and operational variability, in addition to challenges such as growing population, increasing water demands, diminishing water sources and climate change. Recent advances in modelling techniques along with high computational capabilities have facilitated rapid progress in this area. In India, several studies have been carried out to understand and quantify uncertainties in various basins, enumerate large temporal and regional mismatches between water availability and demands, and project likely changes due to warming. A comprehensive review of uncertainties in water resource modelling from an Indian perspective is yet to be done. In this work, we aim to appraise the quantification of uncertainties in systems modelling in India and discuss various water resource management and operation models. Basic formulation of models for probabilistic, fuzzy and grey/inexact simulation, optimization, and multi-objective analyses to water resource design, planning and operations are presented. We further discuss challenges in modelling uncertainties, missing links in integrated systems approach, along with directions for future.

关键词： reservoir operation stochastic dynamic programming fuzzy optimization reservoir-river system water quantity-quality management climate change

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Staff assignment policies for a mass casualty event queuing network

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ANNALS OF OPERATIONS RESEARCH 2019年第1-2期283卷 411-442页

作者： Lodree, Emmett J. Altay, Nezih Cook, Robert A. Univ Alabama Culverhouse Coll Commerce & Business Adm Tuscaloosa AL 35487 USA Depaul Univ Driehaus Coll Business Chicago IL 60604 USA

We study parallel queuing systems in which heterogeneous teams collaborate to serve queues with three different prioritization levels in the context of a mass casualty event. We assume that the health condition of casualties deteriorate as time passes and aim to minimize total deprivation cost in the system. Servers (i.e. doctors and nurses) have random arrival rates and they are assigned to a queue as soon as they arrive. While nurses and doctors serve their dedicated queues, collaborative teams of doctors and nurses serve a third type of customer, the patients in critical condition. We model this queueing network with flexible resources as a discrete-time finite horizon stochastic dynamic programming problem and develop heuristic policies for it. Our results indicate that the standard c mu rule is not an optimal policy, and that the most effective heuristic policy found in our simulation study is intuitive and has a simple structure: assign doctor/nurse teams to clear the critical patient queue with a buffer of extra teams to anticipate future critical patients, and allocate the remaining servers among the other two queues.

关键词： Humanitarian logistics Medical emergency stochastic dynamic programming Monte Carlo simulation

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Welfare Implications of Water Scarcity: Higher Prices of Desalination

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ENVIRONMENTAL & RESOURCE ECONOMICS 2019年第4期73卷 995-1022页

作者： Saglam, Yigit Victoria Univ Wellington Sch Econ & Finance POB 600 Wellington 6140 New Zealand

In this paper, we evaluate the welfare implications of shortages in renewable resources, and investigate the effects of cross-subsidization on these shortages. We set up a stochastic dynamic programming model in which a benevolent supplier allocates the resource for multiple user groups subject to revenue and resource constraints. The supplier also has access to an external source that can be utilized at a certain cost. The solution to the model gives the optimal sectoral prices, and demand for the external source. We find out that saving budget surplus during periods of scarcity allows the planner to charge prices below average costs when the resource is abundant. Using data from Turkey, we simulate our dynamic model to quantify the implications of cross-subsidization on water use across user groups.

关键词： Renewable resource Water shortages stochastic dynamic programming Desalination Cross-subsidization

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Risk, Risk Aversion, and Agricultural Technology Adoption A Novel Valuation Method Based on Real Options and Inverse stochastic Dominance

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Q Open 2021年第2期1卷

作者： Spiegel, Alisa Britz, Wolfgang Finger, Robert Institute for Food and Resource Economics University of Bonn Meckenheimer Allee 174 Bonn 53115 Germany Agricultural Economics and Policy Group ETH Zurich Sonneggstrasse 33 Zurich 8092 Switzerland

Risk and risk preferences belong to the key determinants of investment-based technology adoption in agriculture. We develop and apply a novel approach in which an inverse second order stochastic dominance approach is integrated into a stochastic dynamic farm-level model to quantify the effect of both risk and risk aversion on the timing and scale of agricultural technology adoption. Our illustrative example on short rotation coppice adoption shows that risk aversion leads to technology adoption that takes place earlier, but to a smaller extent. In contrast, higher levels of risk exposure lead to postponed but overall larger adoption. These effects would be obscured if technology adoption is not analyzed in a farm-scale context or considered as a now-or-never decision, the still dominant approach in the literature. © 2021 The Author(s). Published by Oxford University Press in association with European Agricultural and Applied Economics Publications Foundation.

关键词： farm-level investment decision inverse stochastic dominance perennial energy crop Risk preferences stochastic dynamic programming

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Modeling producer responses with dynamic programming: a case for adaptive crop management

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AGRICULTURAL ECONOMICS 2019年第1期50卷 101-111页

作者： Boussios, David Preckel, Paul V. Yigezu, Yigezu A. Dixit, Prakash N. Akroush, Samia M'hamed, Hatem Cheikh Annabi, Mohamed Aw-Hassan, Aden Shakatreh, Yahya Hadi, Omar Abdel Al-Abdallat, Ayed Abu El Enein, Jamal Ayad, Jamal ERS USDA Washington DC 20250 USA Purdue Univ Dept Agr Econ W Lafayette IN 47907 USA ICARDA Amman Jordan NARC Amman Jordan INRAT Tunis Tunisia Univ Jordan Fac Agr Amman Jordan

Past research found agricultural producers' conditional responses during the growing season are important adaptations to weather and other stochastic events. Failing to recognize these responses overstates the risks confronting producers and understates their ability to respond to adverse circumstances. dynamic programming (DP) provides a means for determining optimal long-term crop management plans. However, most applications in the literature base their analysis on annual time steps with fixed strategies within the year, effectively ignoring conditional responses during the year. We suggest an alternative approach that captures the strategic responses within a cropping season to random weather variables as they unfold, reflecting farmers' ability to adapt to weather realizations. We illustrate our approach by applying it to a typical cereal farm in Karak, Jordan. The results show that including conditional within-year responses to weather reduces the frequency of fallowing by 23% and increases expected income by 9%.

关键词： Crop rotation stochastic dynamic programming Systems analysis Risk Bioeconomic

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stochastic optimal switching model for migrating population dynamics

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JOURNAL OF BIOLOGICAL dynamicS 2019年第1期13卷 706-732页

作者： Yoshioka, Hidekazu Tanaka, Tomomi Aranishi, Futoshi Izumi, Tomoki Fujihara, Masayuki Shimane Univ Grad Sch Nat Sci & Technol Matsue Shimane Japan Shimane Univ Fisheries Ecosyst Project Ctr Matsue Shimane Japan Ehime Univ Grad Sch Agr Matsuyama Ehime Japan Kyoto Univ Grad Sch Agr Kyoto Japan

An optimal switching control formalism combined with the stochastic dynamic programming is, for the first time, applied to modelling life cycle of migrating population dynamics with non-overlapping generations. The migration behaviour between habitats is efficiently described as impulsive switching based on stochastic differential equations, which is a new standpoint for modelling the biological phenomenon. The population dynamics is assumed to occur so that the reproductive success is maximized under an expectation. Finding the optimal migration strategy ultimately reduces to solving an optimality equation of the quasi-variational type. We show an effective linkage between our optimality equation and the basic reproduction number. Our model is applied to numerical computation of optimal migration strategy and basic reproduction number of an amphidromous fish Plecoglossus altivelis altivelis in Japan as a target species.

关键词： stochastic dynamic programming fish migration Hamilton-Jacobi-Bellman equation basic reproduction number Plecoglossus altivelis altivelis

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Medium-term scheduling of a hydropower plant participating as a price-maker in the automatic frequency restoration reserve market

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ELECTRIC POWER SYSTEMS RESEARCH 2020年 185卷 106399-106399页

作者： Perez-Diaz, Juan, I Guisandez, Ignacio Chazarra, Manuel Helseth, Arild Univ Politecn Madrid Dept Hydraul Energy & Environm Engn C Prof Aranguren 3 Madrid 28040 Spain SINTEF Energy Res Sem Saelands Vei 11 N-7465 Trondheim Norway

This paper presents a novel optimization model for the calculation of the water value of a hydropower plant. The model has a time horizon of 1 year with 1-day decision stages, considers sales of both energy and frequency restoration reserves (FRR) and is solved by stochastic dynamic programming. The novelty of the model is that it considers the producer's price-making ability in the FRR market. The proposed model is used to obtain the water values of an existing hydropower plant. The water values are then used to simulate the day-ahead scheduling of the hydropower plant in a 100-year scenario. The results are compared to those obtained without considering the producer's price-making ability in the FRR market. The profit increase is modest compared to the uncertainty existing in the day-ahead scheduling in all analysed cases. However, the water spillage is significantly lower if the producer's price-making ability in the FRR market is considered when computing the water value. This last result may have important implications for the plant's operation, especially when the reservoir is also used for the purpose of flood control, as the one used as case study in the paper, and many others all over the world.

关键词： Hydroelectric power generation Water value Frequency restoration reserve market Price-maker producer Mixed integer quadratic programming stochastic dynamic programming

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An Approach for Managing Operating Assets for Humanitarian Development Programs

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PRODUCTION AND OPERATIONS MANAGEMENT 2019年第8期28卷 2132-2151页

作者： Fard, Milad Keshvari Eftekhar, Mahyar Papier, Felix HEC Montreal Decis Sci Montreal PQ H3T 2A7 Canada Arizona State Univ Supply Chain Management Tempe AZ 85287 USA ESSEC Business Sch Operat Management F-95021 Cergy France

Every year, humanitarian organizations assign a sizable portion of their limited financial resources to procure, operate and maintain operating assets, without which service delivery would be nearly impossible. In this study, using vehicles to represent operating assets, we identify policies for sizing and allocating operational capacity to minimize the expected deprivation costs in a humanitarian development context. First, we develop a stochastic dynamic programming model, and then an efficient heuristic policy that considers the interaction of asset purchasing and operating decisions when the budget is uncertain. Based on a dataset provided by a large international organization, we estimate the parameters of our model to run numerical experiments. Results demonstrate the following: (i) Although budget uncertainty increases the expected deprivation costs and decreases capacity utilization, the negative impact of budget uncertainty is mitigated if budget savings between periods is allowed;(ii) a policy for minimizing the expected deprivation costs over time may avoid using all available assets in all periods;(iii) in situations in which the variation in the criticality of missions is large, both the expected deprivation costs and fleet utilization decrease;and (iv) in most conditions, a centralized asset procurement model outperforms a decentralized model, not only in terms of logistic costs but also in minimizing the expected deprivation costs.

关键词： asset procurement fleet management humanitarian development programs simultaneous allocation optimization stochastic dynamic programming

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Markov switching autoregressive modeling of wind power forecast errors

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ELECTRIC POWER SYSTEMS RESEARCH 2020年 189卷 106641-106641页

作者： Latimier, R. Le Goff Le Bouedec, E. Monbet, V ENS Rennes SATIE Lab Rennes France Univ Grenoble LEGI Grenoble France Univ Rennes 1 IRMAR Rennes France

Forecast errors constitute the main hurdle to integrating variable renewable energies into electrical power systems. Errors are inherent to forecasting, although their magnitude varies significantly with respect to both the method adopted and the time horizon. Their dynamic and stochastic modeling is mandatory for power systems to efficiently balance out these errors. A Markov Switching Autoregressive - MS-AR - approach is proposed herein for wind power forecast errors. This particular model is able to identify weather regimes according to the forecast reliability. Such regimes are controlled by a Markov chain whose state - not directly observable - determines the AR model parameters. The statistical features of the data artificially generated by this model are very similar to those of the actual forecast error. This model is used to solve the optimal management of a storage associated with a wind farm. The resolution is performed by means of stochastic dynamic programming while comparing the proposed MS-AR approach with several other models. In this illustrative problem, a 15% reduction in operating costs is derived from a fine model of forecast errors.

关键词： Forecast errors Markov switching autoregressive stochastic dynamic programming Wind power forecast

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