Coordination of last train transfers using automated fare collection (AFC) system data

This paper studies last train coordination problem for metro networks, aiming to maximize the total number of passengers who can reach their destinations by metro prior to the end of operation. The concept of last boarding time is defined as the latest time that passengers can board the last trains and reach final destinations. The corresponding method for calculating last boarding time is also put forward. With automatic fare collection system data, an optimization model for coordinating last trains is proposed. The objective function optimizes the number of passengers who can reach their final destinations during the train period using departure times and headways of last trains for each line as decision variables. Afterwards, an adaptive genetic algorithm is put forward to solve this model and is applied to a case study of the Shanghai metro system. Copyright © 2017 John Wiley & Sons, Ltd.     

An equilibrium-based network model for international container flows

The liner shipping industry is a highly complex system and is extremely sensitive to rapid changes in the environment. To facilitate decision-making in response to endogenous and exogenous shocks, this research develops a strategic network model based on equilibrium principles to analyze the international marine liner shipping network according to port charge, congestion level at the port, and load factor of the ship and estimates the possible container flows under different scenarios in the long run. The distribution model of container flows is extended from Beckmann's transformation. To calibrate the parameters employed in the model so that it offers greater fidelity in predicting container flows, we devise a descent direction-based heuristic. The proposed framework is empirically applied to various scenarios to validate the model and predict the flow pattern after significant events. By identifying these events’ potential impact on the maritime network, the presented model can help relevant stakeholders reduce uncertainty when shaping maritime policies so that they can seize opportunities to increase their competitiveness and maintain their advantage in the maritime market.     

Field implementation feasibility study of cumulative travel‐time responsive (CTR) traffic signal control algorithm

The cumulative travel‐time responsive (CTR) algorithm determines optimal green split for the next time interval by identifying the maximum cumulative travel time (CTT) estimated under the connected vehicle environment. This paper enhanced the CTR algorithm and evaluated its performance to verify a feasibility of field implementation in a near future. Standard Kalman filter (SKF) and adaptive Kalman filter (AKF) were applied to estimate CTT for each phase in the CTR algorithm. In addition, traffic demand, market penetration rate (MPR), and data availability were considered to evaluate the CTR algorithm's performance. An intersection in the Northern Virginia connected vehicle test bed is selected for a case study and evaluated within vissim and hardware in the loop simulations. As expected, the CTR algorithm's performance depends on MPR because the information collected from connected vehicle is a key enabling factor of the CTR algorithm. However, this paper found that the MPR requirement of the CTR algorithm could be addressed (i) when the data are collected from both connected vehicle and the infrastructure sensors and (ii) when the AKF is adopted. The minimum required MPRs to outperform the actuated traffic signal control were empirically found for each prediction technique (i.e., 30% for the SKF and 20% for the AKF) and data availability. Even without the infrastructure sensors, the CTR algorithm could be implemented at an intersection with high traffic demand and 50–60% MPR. The findings of this study are expected to contribute to the field implementation of the CTR algorithm to improve the traffic network performance. Copyright © 2017 John Wiley & Sons, Ltd.     

Dynamic change of aircraft seat condition for fast boarding

Aircraft boarding is a process mainly impacted by the boarding sequence, individual passenger behavior and the amount of hand luggage. Whereas these aspects are widely addressed in scientific research and considered in operational improvements, the influence of infrastructural changes is only focused upon in the context of future aircraft design. The paper provides a comprehensive analysis of the innovative approach of a Side-Slip Seat, which allows passengers to pass each other during boarding. The seat holds the potential to reduce the boarding time by approx. 20%, even considering operational constraints, such as passenger conformance to the proposed boarding strategy. A validated stochastic boarding model is extended to analyze the impact of the Side-Slip Seat. The implementation of such fundamental change inside the aircraft cabin demands for adapted boarding strategies, in order to cover all the benefits that accompany this new dynamic seating approach. To reasonably identify efficient strategies, an evolutionary algorithm is used to systematically optimize boarding sequences. As a result, the evolutionary algorithm depicts that operationally relevant boarding strategies implementing the Side-Slip Seat should differentiate between the left and the right side of the aisle, instead of the current operationally preferred boarding from the back to the front.     

基于二维联合修正算法的RS乘积码软判决研究

在分析了传统RS码译码算法的基础上,提出了基于二维联合修正的RS乘积码软判决算法。如何修正软信息,一直是乘积码迭代算法的关键问题。文章详细地分析了二维联合修正算法中软信息的修正及其依据,给出了具体的仿真结果,具有很好的应用前景。     

排放控制区下集装箱班轮航线路径规划与航速调度集成决策

针对排放控制区和“限硫令”实施下，控制区内外燃油价格的巨大差异，对船舶进出港射角 选择、航段航速优化，挂港顺序确定的影响，综合考虑船舶进出港射角与控制区内外航距组合的 关联关系，控制区内外航距、航速在燃油价格差异下的悖反关系，船舶耗油费用和耗时费用的平 衡关系，港口间船舶运行费用组合与航线挂港次序的作用关系，以及这些关系相互影响，相互作 用，相互耦合对船舶运营成本的影响，提出集装箱班轮航线路径规划与航速调度集成决策问题。 以航次运营成本最小为目标，运用斜边非限定变异三角函数几何方法和混合整数非线性规划建 模方法，构建该问题的两阶段集成决策模型，并利用遗传算法对结果进行优化。最后，通过案例 对比与趋势分析，验证了模型的实用性和优越性。     

面向动静态混合环境的智能车运动规划方法

针对存在动态和静态障碍物环境中的智能车运动规划问题，本文提出一种基于三维搜索的方法。该方法首先在笛卡尔坐标系中增加时间维度以建立时间-空间栅格，构建不同车速下的车辆运动基元；将智能车转化为多个圆心组成的线段，采用膨胀静态障碍物的方法进行不规则障碍物碰撞检测，运用时间间隔法将动态障碍物碰撞检测简化为线段交叉性检测；构建包含最大速度和加速度约束的速度启发式函数，用于引导搜索树在时空空间中快速到达目标位置和速度；最后基于启发式方法和局部运动规划方法在时空栅格中进行搜索，获取融合时间信息和“停止-等待”等决策信息的运动轨迹。实验结果表明：本文运动规划方法在动静态混合环境中能够引导智能车安全行驶，相比速度障碍方法，安全行驶的平均成功率提升23%；相比混合A*方法，平均成功率提升19%，行驶耗时缩短21%。     

指引路径规划模型的建模与仿真验证

道路上某个位置存在多个指路标志时可能引发信息过载问题，对驾驶员产生干扰. 为解决这一问题，本文基于A* (A-star)算法，提出一种指引路径规划模型.考虑特定节点信息过载问题对指引路径实际成本的影响，在模型的估价函数中增设惩罚系数，可以有效避开引发信息过载现象的指引路径选择 . 基于 VISSIM 展开案例研究，借助其二次开发功能提取 VISSIM路网中的相关数据.利用所建指引路径规划模型求解路网中一对OD间的指引路径. 最后，对比分析有无惩罚系数两种模型得到的指引路径规划和指路标志布设方案，证明本文模型在指引路径规划时可有效避免信息过载问题.     

基于关系代数的结构模式识别系统句法分析单元设计

介绍了一种基于关系代数的句法分析单元设计.尝试通过与关系代数模型紧密集成,利用关系数据库系统能够组织和快速检索海量数据的特点,提高句法分析单元的处理复杂文法样本的能力,同时减轻用户的编码负担.在此框架中,部分推导树集合被表示为关系；推理规则集被表示为扩展的关系代数运算.给出了算法实现所需的数据结构和控制结构.从而将句法分析算法完全表示为数据库系统中的一个关系运算过程.最后通过原型系统验证了该方法的可行性.