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Planning is facing powerful challenges - professionally, intellectually, practically - in ways arguably not seen before. In this editorial we examine whether we have witnessed the withering away of regional planning. Our argument ...
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Planning is facing powerful challenges - professionally, intellectually, practically - in ways arguably not seen before. In this editorial we examine whether we have witnessed the withering away of regional planning. Our argument is that planning remains integral to the future of regional studies, but not in the form it once took. We argue for new approaches to planning regional futures. More broadly, this editorial and the Planning Regional Futures issue is an intellectual call-to-arms to engage planners (and those who engage with planning) to critically explore what planning is, and should be, for in how we plan cities and regions.
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This paper proposes a control architecture of autonomous underwater vehicle (AUV) for coverage mission in irregular region (CMIR) with an improved task planner. The CMIR control architecture is structured in four layers: perceptio...
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This paper proposes a control architecture of autonomous underwater vehicle (AUV) for coverage mission in irregular region (CMIR) with an improved task planner. The CMIR control architecture is structured in four layers: perception layer, reactive layer, decision making layer and execution layer. To improve the task planner in decision making layer of control architecture, we adopted convex partitioning method and Success-History Based Adaptive Differential Evolution Algorithm (SHADE) including linear population size reduction (L-SHADE) as the computing engine, which make CMIR control architecture more suitable to coverage problems. Through statistical analysis, we obtained a set of optimized control parameters. Simulation experiments were carried out, three task planners were compared in terms of convergence speed, optimized path length and computing time consumption. The results show that the coverage efficiency of the task planner based on L-SHADE is higher than that of task planner based on particle swarm optimization (PSO) and differential evolution (DE). Sea trial was performed with Sailfish-AUV, which proved that the CMIR control architecture is feasible in actual marine environment.
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Abstract This paper focuses on assessing a policy for reallocation of Colorado River water for major stakeholders in the state of California, to set a standard for sustainable long-term public and environmental use. We address the...
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Abstract This paper focuses on assessing a policy for reallocation of Colorado River water for major stakeholders in the state of California, to set a standard for sustainable long-term public and environmental use. We address the policy of allocating scarce water resources to competing stakeholders of different sectors in the Salton Sea region under over-committed water rights agreement. We determine the value of water applied to the agricultural, urban and tourist sectors to estimate the regional welfare under different allocation frameworks. We use two models for allocation: one involving a social planner approach that maximizes regional welfare, the second focusing on the bankruptcy rules of proportional deficit (cutback), and constrained equal award. We find the proportional cutback framework to be less conducive to regional welfare, although it presents a more politically feasible and robust option.
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The authors present a probabilistically complete planning approach for handling the lift path planning problem without prior picking/placing configurations. Firstly, this research introduces the concept of crane location regions (...
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The authors present a probabilistically complete planning approach for handling the lift path planning problem without prior picking/placing configurations. Firstly, this research introduces the concept of crane location regions (CLRs) to represent the constraints that the pose of the lifted object imposes on the crane's pose at the picking or placing moment. And then the authors develop a rapidly-exploring random trees (RRT)-based planner called the bidirectional multiple RRTs (BiMRRTs), which simultaneously gradually grows multiple trees from the picking pose-constrained space and the placing pose-constrained space instead of just growing a single tree from the picking configuration and the placing configuration. Finally, three simulation experiments are conducted to demonstrate the effectiveness of the proposed approach. The results show that the proposed approach can efficiently generate a collision-free lift path when the picking configuration and the placing configuration are unknown. (C) 2014 American Society of Civil Engineers.
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Planners make judgements in their daily work - they define a problem, they formulate objectives or implement certain instruments to develop, with and for others, good or desirable places, neighbourhoods, cities or regions. These j...
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Planners make judgements in their daily work - they define a problem, they formulate objectives or implement certain instruments to develop, with and for others, good or desirable places, neighbourhoods, cities or regions. These judgements are affected by both individual and collectively shared cognitive frames, representing the 'cultural DNA' through which planners perceive the world. To understand and compare how planning practices and judgements are constructed by the interplay of individual and collective frames from various actors and spheres (values of individual planners, norms of planning institutions, general societal values, etc.) in a specific culturised context, a conceptual framework is developed by adopting analytical categories from the fields of organisational sciences or cultural studies. The conceptual framework - consisting of the dimensions: cognitive frames of individual planners and planning institutions; actors and their interactions; the institutional context and the planning system; as well as the underlying societal beliefs, perceptions and values affecting planning and planners' judgements - provides scientists with a new theoretical approach that allows analysing and comparing the situated particularities of planning practices on basis of a consistent system of criteria.
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Recently, new regional innovation policy paradigms emerged that transcend a long-lived dispute on whether either regional specialization, diversification, or rather related variety is most conducive to regional innovativeness. Thi...
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Recently, new regional innovation policy paradigms emerged that transcend a long-lived dispute on whether either regional specialization, diversification, or rather related variety is most conducive to regional innovativeness. This includes ‘smart specialization’ in which regions are deliberately specialized and connected following technological relatedness, ‘gatekeepers’ in which there are pipelines between dense regional networks, and a ‘regional mix’ of knowledge that allows sustained ‘branching’. We develop and use an agent-based model to study the conjecture that, to stimulate (supra)regional innovativeness, social planners need to consider both, in conjunction, the mix of technological knowledge in regions and the (inter)regional innovation network topology. We use this agent-based model to evaluate the performance of and study the internal mechanisms of these new policy paradigms in a variety of scenarios. To increase the external validity of our findings, we calibrate the knowledge graph searched by the agents in our model to the OECD patent database. We confirm that access to related variety is important, yet that, on top of that, access to incidentally related knowledge is crucial to prevent high-level lock-in and ensure long term technological progress. Moreover, we find that networks with regional gatekeepers are particularly innovative, because these gatekeepers form ‘knowledge hubs’, create short paths to potential partners, and enlarge the total pool of knowledge. In case agents have few relationships, we find exceptionally high performance for the gatekeeper network in combination with regional diversification. The smart specialization network is a solid second option, although it lacks access to incidentally related knowledge and thus will ultimately fall behind whenever agents have relatively few relationships. The study elaborates on specific scenarios to reveal intricacies in the relationship between knowledge distribution, network topology, and the structure of interrelationships between knowledge fields.
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This paper reports a semi-decentralized framework for joint expansion planning of privately owned multi regional energy systems (MRGES) and sub-transmission grids. Multi-agent systems are employed for decentralization purpose and ...
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This paper reports a semi-decentralized framework for joint expansion planning of privately owned multi regional energy systems (MRGES) and sub-transmission grids. Multi-agent systems are employed for decentralization purpose and facilitated participation of private ownerships in planning model by preventing agents to disclose their private properties. Regional energy system's agents and the sub-transmission expansion planner's agent are the active players of the proposed method, where exchange of information among them is fully decentralized and an independent coordinating agent (ICA) is responsible for conducting market operation and evolutionary stability state (ESS) extraction. By applying the fuzzy satisfying and Max-Min method, the ESS point of the agents' payoff is determined by ICA. Simulations are carried out on a ten-bus network to validate the efficacy of the suggested framework. The obtained simulation results are compared to those of traditional expansion planning, indicating the superiority of the proposed model.
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This study presents a distributed collaborative transmission expansion planning (TEP) algorithm for interconnected multi-regional power systems. The proposed algorithm is a multi-agent-based TEP. A local TEP is formulated for each...
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This study presents a distributed collaborative transmission expansion planning (TEP) algorithm for interconnected multi-regional power systems. The proposed algorithm is a multi-agent-based TEP. A local TEP is formulated for each region (agent) with respect to the region's local characteristic and interactions (i.e. tie-line flows) with its neighbours. Nodal power balances at border buses are modified to model the interactions. Realistic planning constraints and objectives such as budget constraints, operational costs, N - 1 security criterion, and uncertainties are modelled in the local TEPs. The information privacy is respected as each local planner needs to share limited information related to cross-border tie lines with other planners. To coordinate the local planners, a two-level distributed optimisation algorithm is proposed based on the concept of analytical target cascading (ATC) for multidisciplinary design optimisation. While the upper level solves the local TEPs in parallel, the lower level seeks to coordinate neighbouring regions. The lower-level problem is further replaced in the upper-level optimisation by Karush-Kuhn-Tucker conditions to relax the need for any form of central coordinator. This makes the proposed ATC-based TEP a fully parallelised distributed optimisation algorithm. An initialisation strategy is suggested to enhance the performance of the distributed TEP.
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This study presents an adaptive motion planning strategy for automated vehicle collision avoidance systems to be associated with the variation of collision speed region based on the position of the obstacle. This is done by design...
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This study presents an adaptive motion planning strategy for automated vehicle collision avoidance systems to be associated with the variation of collision speed region based on the position of the obstacle. This is done by designing the motion planner using an artificial potential field (APF) with the incorporation of an adaptive multi-speed scheduler using fuzzy system in the motion planning structure. The knowledge database information is developed based on the risk perception of the driver that consists of APF parameters and was optimised by using particle swarm optimisation algorithm. This study contributes to the improvement of a feasible reference motion generated by the motion planner that can be converted into desired control signals. The reference motion resulted to provide the control command that managed to avoid collision successfully by evasive manoeuvre without lane departure when adapting to variation in the vehicle speeds with different obstacle positions. The results indicated the reduction of the lateral error with respect to the reference avoidance trajectory data of up to 87% compared to base-type APF with maximum reference lateral motion is reduced of up to 26%. Then, a hardware-in-loop test is conducted to verify the proposed strategy using a steering wheel system.
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