The allocation problem of electric car-sharing system: A data-driven approach

Car-sharing is an emerging transportation mode with increasing applications of electric vehicles (EVs). One of the important issues for one-way electric car-sharing systems (ECS) is unbalanced vehicle distributions and high relocation costs. To improve its efficiency and overall profit, this research proposes a data-driven optimization model with the consideration of demand uncertainty. Firstly, a large amount of historical order data from an ECS company are analyzed to characterize the dynamics of the vehicles and the behavioral features of the users. An important observation is that the daily demand by users, i.e., pick-ups, follows Poisson distribution; and the arrival rates vary across time exhibiting four major temporal stages. Based on this observation, this research constructs the ECS reallocation problem as a data-driven optimization model which is a combination of a probability expectation model and a linear programming problem with real-time data as input. More importantly, different from existing research, this research formulates the profit as the mathematical expectation of a discrete random variable with uncertain consumer demands. This allows for a comprehensive consideration of all possible future demands. Furthermore, driving range constraint has been considered in the proposed model as EV is the focus of this paper. A linear solution method is proposed to obtain the global optimal. At the end, the model is validated using real data from 30 ECS stations. The results indicate the daily improvement of profit could be as high as 19.05% with an average of 10.16%.     

网络配置管理的研究及设计

作者首先介绍了网络管理中配置管理的概念和几种配置管理的方式,讨论了本地与远程配置的实现机制、研究了Web配置中Web服务器的功能和作用,最后给出了设计思路和方法.     

船用柴油机故障在线智能仿真诊断技术的应用研究

本文提出了一种船用柴油机性能故障在线自动诊断的新方法,把仿真以及神经网络技术直接应用于柴油机故障在线诊断系统,建立船用柴油机症状与故障样本集,作为神经网络故障诊断的专家知识库,以和柴油机故障在线诊断。尤其是对网络容错能力进行评估分析,并确定较有代表性的径向基函数ＲＢＦ网络分布常数Ｓｃ,从而提高故障诊断的及时性和准确率,减少误诊。     

大凌河特大桥试桩极限承载力的试验及评价

本文通过在大凌河特大桥工程中探索性应用"扁担梁"式锚桩法试桩静载试验,采用小直径径试桩,实测试桩竖向抗压极限承载力以及桩周各土层的分段摩阻力与端阻力,为设计单位对桩参数进行优化提供了有利的试验数据。同时,也为本地区试桩的试验、评价提出了一种准确、可靠、经济可行、工期短的检测方法。     

基于遗传算法的膜片弹簧优化研究

膜片弹簧离合器是现今手动挡汽车的主要离合器形式,针对膜片弹簧在轴向受压过程中,弹簧大端压紧力与变形量的关系,新膜片弹簧工作点的压紧力与摩擦片最大磨损点所对应的膜片弹簧压紧力之间变化平缓以及驾驶员平均操纵力最小这两个矛盾问题的优化。利用权重系数法对其权重进行分配,并采用遗传算法对压紧力变化的平均值最小与驾驶员操纵力最小进行优化[1]。优化表明,在保证足够的工作压紧力下,摩擦片工作过程中磨损导致的膜片弹簧特性曲线部分变化平缓且驾驶员操纵力最小。通过这一算法,可以快速地得到膜片弹簧的各结构参数,为实际设计提供依据。     

汽车以太网技术发展现状与趋势探究

智能网联化已经成为当代汽车发展的重要主题,传统汽车网络通讯技术CAN,LIN等很难支撑汽车智能网联化的进一步发展,汽车以太网技术将在新一代汽车网络架构中承担重要角色。文章对汽车网络技术的发展进行了总结,对汽车以太网技术特点和现状进行了分析,阐明了汽车以太网技术的优势,研究了汽车以太网技术的发展趋势与主要挑战,并探讨了汽车以太网对新一代汽车网络架构的影响。     

Modeling the day-to-day traffic evolution process after an unexpected network disruption

Although various approaches have been proposed for modeling day-to-day traffic flow evolution, none of them, to the best of our knowledge, have been validated for disrupted networks due to the lack of empirical observations. By carefully studying the driving behavioral changes after the collapse of I-35W Mississippi River Bridge in Minneapolis, Minnesota, we found that most of the existing day-to-day traffic assignment models would not be suitable for modeling the traffic evolution under network disruption, because they assume that drivers’ travel cost perception depends solely on their experiences from previous days. When a significant network change occurs unexpectedly, travelers’ past experience on a traffic network may not be entirely useful because the unexpected network change could disturb the traffic greatly. To remedy this, in this paper, we propose a prediction-correction model to describe the traffic equilibration process. A “predicted” flow pattern is constructed inside the model to accommodate the imperfect perception of congestion that is gradually corrected by actual travel experiences. We also prove rigorously that, under mild assumptions, the proposed prediction-correction process has the user equilibrium flow as a globally attractive point. The proposed model is calibrated and validated with the field data collected after the collapse of I-35W Bridge. This study bridges the gap between theoretical modeling and practical applications of day-to-day traffic equilibration approaches and furthers the understanding of traffic equilibration process after network disruption.     

考虑动态稳定性的船舶电网重构技术研究

在进行供电网络重构策略的寻优过程中,一般只考虑最大负载恢复量、节点电压、电流约束等目标网络的稳态信息,系统动态稳定性则因为判断策略复杂等因素,常常忽视重构方案在实施过程中动态稳定性问题。因此,在进行重构方案的寻优过程中,除了考虑重构后网络中的潮流分布因素外,还应对预想性重构方案执行过程的稳定性进行分析,以确保决策全面可实现性。如果不进行重构策略的动态稳定性校验,仅凭“最大负载恢复量”和“潮流分布”选择的重构方案可能会导致故障影响进一步扩大,产生更严重的事故。本文将从船舶供电系统的特点和船舶供电网络重构的需求出发,建立一种准确、快速的分析方法。     

Pre-timed control for an under-saturated and over-saturated isolated intersection: a Bee Colony Optimization approach

In this paper we study the problem of determining the optimum cycle and phase lengths for isolated signalized intersections. Calculation of the optimal cycle and green phase lengths is based on the minimization of the average control delay experienced by all vehicles that arrive at the intersection within a given time period. We consider under-saturated as well as over-saturated conditions at isolated intersections. The defined traffic signal timing problem, that belongs to the class of combinatorial optimization problems, is solved using the Bee Colony Optimization (BCO) metaheuristic approach. The BCO is a biologically inspired method that explores collective intelligence applied by honey bees during the nectar collecting process. The numerical experiments performed on some examples show that the proposed approach is competitive with other methods. The obtained results show that the proposed approach is capable of generating high-quality solutions within negligible processing times.     

A family of macroscopic node models

The family of macroscopic node models which comply to a set of basic requirements is presented and analysed. Such models are required in macro-, mesoscopic traffic flow models, including dynamic network loading models for dynamic traffic assignment. Based on the behaviour of drivers approaching and passing through intersections, the model family is presented. The headway and the turn delay of vehicles are key variables. Having demand and supply as input creates a natural connection to macroscopic link models. Properties like the invariance principle and the conservation of turning fractions are satisfied. The inherent non-uniqueness is analysed by providing the complete set of feasible solutions. The node models proposed by Tampère et al. (2011), Flötteröd and Rohde (2011) and Gibb (2011) are members of the family. Furthermore, two new models are added to the family. Solution methods for all family members are presented, as well as a qualitative and quantitative comparison. Finally, an outlook for the future development of empirically verified models is given.