KSUTraffic: A Microscopic Traffic Simulator for Traffic Planning in Smart Cities

Simulation is a powerful tool for improving, evaluating and analyzing the performance of new and existing systems. Traffic simulators provide tools for studying transportation systems in smart cities as they describe the evolution of traffic to the highest level of detail. There are many types of traffic simulators that allow simulating traffic in modern cities. The most popular traffic simulation approach is the microscopic traffic simulation because of its ability to model traffic in a realistic manner. In many cities of Saudi Arabia, traffic management represents a major challenge as a result of expansion in traffic demands and increasing number of incidents. Unfortunately, employing simulation to provide effective traffic management for local scenarios in Saudi Arabia is limited to a number of commercial products in both public and private sectors. Commercial simulators are usually expensive, closed source and inflexible as they allow limited functionalities. In this project, we developed a local traffic simulator “KSUtraffic” for traffic modeling, planning and analysis with respect to different traffic control strategies and considerations. We modeled information specified by GIS and real traffic data. Furthermore, we designed experiments that manipulate simulation parameters and the underlying area. KSUTraffic visualizes traffic and provides statistical results on the simulated traffic which would help to improve traffic management and efficiency.     

儿童友好视角下城市公园品质与可达性研究——以巴塞罗那学龄前儿童为例

具备可进入的绿色空间、游乐场地是儿童友好城市衡量中的核心指标，也是城市公园提供的必要服务之一。聚焦对城市公园需求度和使用率较高的学龄前儿童，尝试建构综合考虑城市公园品质和可达性的分析及评估方法。选取联合国儿童友好城市——西班牙巴塞罗那为案例，基于实地调研、开源地图、官方统计数据等，使用儿童友好的公园品质指数（QUINPY）和空间句法可达性模型开展综合评价，并结合学龄前儿童人口密度分布，提出有针对性的改善建议，基于不同的需求和现状，选取改善城市交通步行环境、合理增加结构性设施或者鼓励分时段及立体化拓展空间使用可能性等适宜性创新措施。以期为我国儿童友好导向的城市公园发展建设提供参考。     

A fast genetic algorithm for a critical protection problem in biomedical supply chain networks

In this paper, we present a new bilevel model for a biomedical supply chain network with capacity and budget constraint due to the protection and interdiction operations. The components considered in this model are biomedical devices, distribution centers (DCs), medical suppliers (MSs), and hospitals and patients as the demand points. On the other hand, two levels of decisions in the network planning is suggested: (1) the defender’s decision about protection operations of MSs and DCs, the assignment of clients to the DCs, and quantity of products shipped to DCs from MSs to minimize the demand-weighted traveling costs and transport costs and (2) the attacker’s decision about interdiction operations of MSs and DCs to maximize the capacity or service reduction and losses. Because of nondeterministic polynomial time (NP)-hardness of the problem under consideration, an efficient and fast approach based on a genetic algorithm and a fast branch and cut method (GA–FBC) was developed to solve the proposed model. Also, the efficiency via the comparison of results with the genetic algorithm based on CPLEX (GA-CPLEX) and decomposition method (DM) is investigated. In order to assess the performance of the presented GA–FBC, a set of 27 instances of the problem is used. Comprehensive analysis indicates that the proposed approach significantly solves the problem. In addition, the benefits and advantages of preference with running times and its accuracy is shown numerically. Simulation results clearly demonstrate that the defender’s objective effectively reduced and CPU time also within the large-sized instances of the problem in comparison with the GA-CPLEX and DM.     

The Art of Masonry

Brick masonry is not only a question of building physics, building construction and durability, i.e. sustainability, but has much to do with aesthetics and making sense, which may have been forgotten in modern architecture with its absolute lack of décor. Masonry as an art form has been scarce since the era of brick expressionism. Recently, there have been some exceptions – and thoroughly welcome. The ”Fjordenhus“ in Vejle, Denmark, is an astonishing example.     

基于stackelberg多步博弈的无人机协同搜索路径规划

考虑到现有无人机搜索问题研究中无人机、移动目标仅有一方具有远距离探测能力的设定，已经无法体现出战场环境下双方的博弈关系。针对这一不足，基于stackelberg均衡策略，结合多步预测的思想，提出了stackelberg多步博弈策略，实现了无人机、目标都具有远距离探测能力的博弈搜索。通过建立无人机、目标各自的路径收益函数，使双方能够根据不同时刻的博弈状态选择相对应的函数，实现无人机的动态路径规划。仿真结果表明所提出策略完全适用于该博弈模型，比贪婪策略具有更高的搜索效率，大大提高了目标捕获率。     

Generation-expansion planning with linearized primary frequency response constraints

As renewable energy resources increasingly penetrate the electric grid, the inertia capability of power systems has become a developmental bottleneck. Nevertheless, the importance of primary frequency response (PFR) when making generation-expansion plans has been largely ignored. In this paper, we propose an optimal generation-expansion planning framework for wind and thermal power plants that takes PFR into account. The model is based on the frequency equivalent model. It includes investment, startup/shutdown, and typical operating costs for both thermal and renewable generators. The linearization constraints of PFR are derived theoretically. Case studies based on the modified IEEE 39-bus system demonstrate the efficiency and effectiveness of the proposed method. Compared with methods that ignore PFR, the method proposed in this paper can effectively reduce the cost of the entire planning and operation cycle, improving the accommodation rate of renewable energy.     

扬子江城市群工业能源碳排放与经济增长脱钩水平及驱动因素

扬子江城市群地处长江经济带的下游重要门户地区，是江苏省“1+3”重点功能区发展的龙头引擎，打造扬子江城市群的绿色生态走廊对建设“强富美高”新江苏和落实长江大保护均具有重要战略意义。论文聚焦扬子江城市群工业能源碳排放脱钩及其驱动因素分析，研究得出：1）扬子江城市群整体工业碳排放量呈现波动上升的变化趋势，其中南京市和苏州市的碳排放增量明显大于其他城市；2）扬子江城市群工业能源碳排放脱钩大致经历了扩张连接、强脱钩以及弱脱钩3个阶段，整体上脱钩水平逐渐提高，但稳定性不高，各城市工业能源碳排放脱钩水平差异较大，但在逐步优化中；3）从驱动因素看，碳排放强度效应和能源强度效应对脱钩水平有促进作用，工业经济规模效应、区域经济比重和能源结构则相反。基于此，论文提出加强低碳城市试点建设、探索构建全域碳权交易市场、调整优化能源结构、推动科技创新等建议，以促进扬子江城市群工业建设高质量发展。     

城市排水管网混合流数值模拟研究进展

全球气候变化背景下,城市洪涝灾害事件频发,城市雨洪模型将扮演愈发重要的角色。精细化的城市雨洪模型离不开对排水管网水流的准确模拟。混合流在排水管网系统中普遍存在,研究其机理和精确模拟技术对城市排水模型和雨洪模拟精度的提升意义重大。因此,从混合流数值模拟方法、混合流物理模型及城市排水管网模型等三个方面综合分析了国内外在混合流模拟和计算方面的研究进展,并分析了当前研究存在的不足,在此基础上对未来排水管网混合流方面的研究工作进行了展望。     

An analysis of adaptive planning capacity: The case of chilean water utilities

New long-term planning approaches capable of coping with uncertainties such as climate change, rapid urbanization, and changing societal values, have been put forward as a way of producing more robust and sustainable plans for the future. But is the planning practice ready for their adoption? This paper takes four key propositions from the adaptive planning literature and tests the existing capacity for adopting those propositions in the context of Chilean water utilities. We will then propose how existing capacities could be enhanced, and propose alternatives for current planning practices, highlighting the importance of implementation through experimentation.     

Team O2AS at the world robot summit 2018: an approach to robotic kitting and assembly tasks using general purpose grippers and tools

ABSTRACT

In this article, we propose a versatile robotic system for kitting and assembly tasks which uses no jigs or commercial tool changers. Instead of specialized end effectors, it uses its two-finger grippers to grasp and hold tools to perform subtasks such as screwing and suctioning. A third gripper is used as a precision picking and centering tool, and uses in-built passive compliance to compensate for small position errors and uncertainty. A novel grasp point detection for bin picking is described for the kitting task, using a single depth map. Using the proposed system we competed in the Assembly Challenge of the Industrial Robotics Category of the World Robot Challenge at the World Robot Summit 2018, obtaining 4th place and the SICE award for lean design and versatile tool use. We show the effectiveness of our approach through experiments performed during the competition.