船舶气象导航最省燃料航线研究

船舶气象导航是保证船舶航行安全和节能的重要手段。本文应用最佳控制理论研究和建立船舶最省燃料航线数学模型。在分析比较船舶最短时间航线和最省燃料航线数学模型的基础上，讨论了最省燃料航线算法实现。并针对冬季北太平洋进行了最省燃料航线模拟试验。     

智能水箱风扇电动机控制系统

介绍商用车水箱风扇电动机控制系统的一种优化方式,精确控制水箱风扇电动机工作的温度范围,从而提升整车性能。     

考虑不确定性因素的路径优化(英文)

A route optimization methodology in the frame of an onboard decision support/guidance system for the ship’s master has been developed and is presented in this paper.The method aims at the minimization of the fuel voyage cost and the risks related to the ship’s seakeeping performance expected to be within acceptable limits of voyage duration.Parts of this methodology were implemented by interfacing alternative probability assessment methods,such as Monte Carlo,first order reliability method(FORM) and second order reliability method(SORM),and a 3-D seakeeping code,including a software tool for the calculation of the added resistance in waves of NTUA-SDL.The entire system was integrated within the probabilistic analysis software PROBAN.Two of the main modules for the calculation of added resistance and the probabilistic assessment for the considered seakeeping hazards with respect to exceedance levels of predefined threshold values are herein elaborated and validation studies proved their efficiency in view of their implementation into an on-board optimization system.     

基于遗传算法的道路车辆自组织网络源路由机制

在当前基于交叉路口的城市车辆自组织网络(VANETs)路由协议中，道路上数据包传输大多采用基于地理位置的贪婪转发策略，当数据量较大时，个别节点负载较重，极易引起传输延迟增大乃至丢包的情况.本文提出了一种基于遗传算法的源路由机制，通过记录单体车辆的驾驶信息而非传统方法中的车流均值数据，来预测道路上车辆网络的连通情况，并借助遗传算法，首次基于道路连通性、节点负载和连接跳数这3 点综合考虑，计算得出道路上最佳的源路由节点序列.仿真实验结果表明，在传输率与延迟时间上，性能均优于传统的贪婪路由机制，尤其在车流量为250 veh· lane-1· h-1时，传输率提升约13%.该研究可为智能交通信息通讯提供可靠助力.     

考虑均衡性的城市轨道交通线路负荷水平评估研究

线路负荷水平的评价工作是优化运输组织方案的重要前提。首先，本文分析了采用单一均值性指标表征负荷水平不能体现线路内负荷分布偏差的问题。为此，从城市轨道交通线路客流与运输能力匹配的角度出发，以列车负荷为评价单元，建立包括负荷均值和标准差率二维指标的线路负荷水平评估模型。负荷均值指标考虑了各评价单元加权计算，以反映每个评价单元对线路负荷水平的贡献程度，标准差率指标表征负荷均衡性。模型分析得出，线路所有区间的运力同等规模变化不影响标准差率指标，相对提高大客流区间或大客流方向上的输送能力能够改善线路负荷的均衡性。算例分析表明：客流方向不均衡系数超过 1.4 时，应考虑运力优化措施以提高运输能力利用的均衡；组织列车大小交路方案和不成对行车模式，能够提高线路负荷的均衡程度。     

On the fundamental diagram for freeway traffic: A novel calibration approach for single-regime models

The speed-density or flow-density relationship has been considered as the foundation of traffic flow theory. Existing single-regime models calibrated by the least square method (LSM) could not fit the empirical data consistently well both in light-traffic/free-flow conditions and congested/jam conditions. In this paper, first, we point out that the inaccuracy of single-regime models is not caused solely by their functional forms, but also by the sample selection bias. Second, we apply a weighted least square method (WLSM) that addresses the sample selection bias problem. The calibration results for six well-known single-regime models using the WLSM fit the empirical data reasonably well both in light-traffic/free-flow conditions and congested/jam conditions. Third, we conduct a theoretical investigation that reveals the deficiency associated with the LSM is because the expected value of speed (or a function of it) is nonlinear with regard to the density (or a function of it).     

Stability of transportation networks under adaptive routing policies

Growing concerns regarding urban congestion, and the recent explosion of mobile devices able to provide real-time information to traffic users have motivated increasing reliance on real-time route guidance for the online management of traffic networks. However, while the theory of traffic equilibria is very well-known, fewer results exist on the stability of such equilibria, especially in the context of adaptive routing policy. In this work, we consider the problem of characterizing the stability properties of traffic equilibria in the context of online adaptive route choice induced by GPS-based decision making. We first extend the recent framework of “Markovian Traffic Equilibria” (MTE), in which users update their route choice at each intersection of the road network based on traffic conditions, to the case of non-equilibrium conditions, while preserving consistency with known existence and uniqueness results on MTE. We then exhibit sufficient conditions on the network topology and the latency functions for those MTEs to be stable in the sense of Lyapunov for a single destination problem. For various more restricted classes of network topologies motivated by the observed properties of travel patterns in the Singapore network, under certain assumptions we prove local exponential stability of the MTE, and derive analytical results on the sensitivity of the characteristic time of convergence to network and traffic parameters. The results proposed in this work are illustrated and validated on synthetic toy problems as well as on the Singapore road network with real demand and traffic data.     

Equilibrium analysis and route guidance in large-scale networks with MFD dynamics

Recent studies have demonstrated that Macroscopic Fundamental Diagram (MFD), which provides an aggregated model of urban traffic dynamics linking network production and density, offers a new generation of real-time traffic management strategies to improve the network performance. However, the effect of route choice behavior on MFD modeling in case of heterogeneous urban networks is still unexplored. The paper advances in this direction by firstly extending two MFD-based traffic models with different granularity of vehicle accumulation state and route choice behavior aggregation. This configuration enables us to address limited traffic state observability and to scrutinize implications of drivers’ route choice in MFD modeling. We consider a city that is partitioned in a small number of large-size regions (aggregated model) where each region consists of medium-size sub-regions (more detailed model) exhibiting a well-defined MFD. This paper proposes a route guidance advisory control system based on the aggregated model as a large-scale traffic management strategy that utilizes aggregated traffic states while sub-regional information is partially known. In addition, we investigate the effect of equilibrium conditions (i.e. user equilibrium and system optimum) on the overall network performance, in particular MFD functions.