Electric vehicle charging station locations: Elastic demand,station congestion,and network equilibrium

Battery-only electric vehicles (BEVs) generally offer better air quality through lowered emissions, along with energy savings and security. The issue of long-duration battery charging makes charging-station placement and design key for BEV adoption rates. This work uses genetic algorithms to identify profit-maximizing station placement and design details, with applications that reflect the costs of installing, operating, and maintaining service equipment, including land acquisition. Fast electric vehicle charging stations (EVCSs) are placed across a congested city's network subject to stochastic demand for charging under a user-equilibrium traffic assignment. BEV users’ station choices consider endogenously determined travel times and on-site charging queues. The model allows for congested-travel and congested-station feedback into travelers’ route choices under elastic demand and BEV owners’ station choices, as well as charging price elasticity for BEV charging users.Boston-network results suggest that EVCSs should locate mostly along major highways, which may be a common finding for other metro settings. If 10% of current EV owners seek to charge en route, a user fee of $6 for a 30-min charging session is not enough for station profitability under a 5-year time horizon in this region. However, $10 per BEV charging delivers a 5-year profit of $0.82 million, and 11 cords across 3 stations are enough to accommodate a near-term charging demand in this Boston-area application. Shorter charging sessions, higher fees, and/or allowing for more cords per site also increase profits generally, everything else constant. Power-grid and station upgrades should keep pace with demand, to maximize profits over time, and avoid on-site congestion.     

Large-scale evacuation network optimization: a bi-level control method with uncertain arterial demand

To improve the efficiency of large-scale evacuations, a network aggregation method and a bi-level optimization control method are proposed in this paper. The network aggregation method indicates the uncertain evacuation demand on the arterial sub-network and balances accuracy and efficiency by refining local road sub-networks. The bi-level optimization control method is developed to reconfigure the aggregated network from both supply and demand sides with contraflow and conflict elimination. The main purpose of this control method is to make the arterial sub-network to be served without congestion and interruption. Then, a corresponding bi-objective network flow model is presented in a static manner for an oversaturated network, and a Genetic Algorithm-based solution method is used to solve the evacuation problem. The numerical results from optimizing a city-scale evacuation network for a super typhoon justify the validity and usefulness of the network aggregation and optimization control methods.     

Transit network design with allocation of green vehicles: A genetic algorithm approach

The use of fossil fuels in transportation generates harmful emissions that accounts for nearly half of the total pollutants in urban areas. Dealing with this issue, local authorities are dedicating specific efforts to seize the opportunity offered by new fuels and technological innovations in achieving a cleaner urban mobility. In fact, authorities are improving environmental performances of their public transport fleet by procuring cleaner vehicles, usually called low and zero emission vehicles (LEV and ZEV, respectively). Nevertheless there seems to be a lack of methodologies for supporting stakeholders in decisions related to the introduction of green vehicles, whose allocation should be performed since the network design process in order to optimize their available green capacity.In this paper, the problem of clean vehicle allocation in an existing public fleet is faced by introducing a method for solving the transit network design problem in a multimodal, demand elastic urban context dealing with the impacts deriving from transportation emissions.The solving procedure consists of a set of heuristics which includes a routine for route generation and a genetic algorithm for finding a sub-optimal set of routes with the associated frequencies.     

Workspace analysis to generate a collision-free torch path for a ship welding robot

We propose a method to determine the optimal initial location and to generate torch paths for a ship welding robot with 6 degrees of freedom (DOF). The optimal initial location is determined using an objective function, which is set up by combining constraints on the torch posture, manipulability, and the range of each joint angle to avoid collisions. A genetic algorithm (GA) is used to optimize the objective function because it does not require additional derivatives. After the initial location is determined, torch paths are generated by interpolating the starting point, endpoints and torch postures using inverse kinematics. Our method can be applied to automate the welding job for each block during ship building, irrespective of the shape of the robots, by changing the objective function.     

基于多代理机制的列车运行调整模型及算法动态集成研究

分析列车运行调整问题研究的现状与进展,主要集中在模型研究和算法研究两个方面。分析传统求解模型及算法研究的局限性,提出对现有模型及算法进行动态集成的研究思路。采用基于多代理机制的动态集成方法,将模型对象和算法对象转化成多个代理,定义多代理之间的交互策略,实现调整方法的动态集成。提出基于多代理机制的列车运行调整问题模型及算法的动态集成系统。     

铁路行车调度系统数据结构分析与设计

分析铁路行车调度系统基本结构和功能。利用面向对象分析技术和数据结构理论,对铁路行车调度系统中的信息进行抽象,提出一种以列车为中心的十字链表数据存储结构,提出调整计划的数据帧结构形成算法Ajustment()和在屏幕上画运行线的算法DrawCurve()。并对算法的复杂性进行分析,所有算法的复杂度与问题的规模呈线性关系。系统具有较高的执行效率。     

高速铁路无砟轨道精调算法软件探讨

目前高铁无砟轨道的调轨方案是借助轨道几何状态测量仪随机调轨软件,通过人工操作得出。这样费工费时,给工程实际应用带来诸多不便。为了能够快速计算出符合工程实际需要的调整结果,依据人工调轨的思路,编程实现自动化调轨算法。对比某专业长轨精调软件与新研发的无砟轨道精调软件,对同一段无砟轨道实测数据进行轨道精调,分别统计两种方法获得的调轨方案各项平顺性指标合格率、调整量和计算时间,结果表明:(1)两种方案均能满足工程实际要求,且新研发的精调软件得到的调整量要小于某专业长轨精调软件得到的调整量;(2)对于不同方法得到的调轨方案的效率,某专业长轨精调软件调整需要几个小时,而新研发的软件调整只需要几分钟,新算法显著地缩短了精调方案的获取时间,提高了工效。     

基于GA优化模糊PID控制的ATO算法研究

针对城市轨道列车的自动驾驶系统(ATO)传统PID控制方法适应性差和智能化不足的问题,基于该领域专家知识和驾驶司机的操作经验,将遗传算法优化的模糊PID控制算法运用在ATO的控制系统中,并运用MTALAB进行仿真。仿真结果表明,该控制算法优于传统的PID控制,能够满足ATO系统对不同工况下的适应性和智能性要求,可以达到精确停车和准点到站的目的,能够有效提高列车舒适性和降低列车能耗。     

进路搜索数据结构与算法研究

在深入研究站场信号平面图的基础上,对站场信号平面图建立有向无环图的模型,阐述一种在有向无环图中动态生成二叉树的进路搜索算法。验证算法的有效性和实用性。     

自动事件检测算法的比较及评估

对现有的几种典型的高速公路事件自动检测算法的性能进行了评价,并给出各种算法的优缺点及比较评估标准,采用检测率(DR)和误报率(FAR)特征曲线及模拟退火算法进行了评价和优化,在比较、分析结果的基础上提出了智能检测算法的概念,并指出其今后的发展趋势。