港口与城市环境及资源的协调发展度研究

随着我国港口和城市建设的不断发展,在生态环境和资源利用方面港城间的矛盾日益明显,如何协调两者之间的发展已成为目前迫切需要解决的课题。为此,以大连市为例,从建立港城协调发展度模型入手,对港口与环境及资源之间协调的程度进行评判,从而为指导港口和城市的可持续发展提供了决策依据。     

LED道路交通信号灯测试平台研究

通过研究LED道路交通信号灯测试平台的结构和功能,分析用户层测试模块、系统层测试模块、基础层测试模块和传输层测试模块的结构和内容,探讨LED道路交通信号灯的安装测试、功能特性测试、兼容性测试、电气安全性测试、信号传输测试、环境适应性测试、可靠性测试等方面的测试项目、测试内容和测试方法,旨在建立一套科学的、完整的、适用的测试系统,为LED道路交通信号灯以及相关控制设备的检测项目、检测方法、检测设备提供技术支持。     

城市可持续交通系统的研究

通过对国内外可研成果的分析和研究,结合沈阳市的实际情况,分析了沈阳市交通系统现状和存在问题,明确了沈阳城市可持续交通系统的影响因素和指标体系,制定了沈阳市可持续交通系统的实现方法。     

Application of genetic algorithms for joint optimization of signal setting parameters and dynamic traffic assignment for the real network data

This paper presents the joint optimization of signal setting parameters and dynamic user equilibrium (DUE) traffic assignment for the congested urban road network. The simulation-based approach is employed to obtain the DUE condition for the case of multiple-origin multiple-destination traffic flows. The dynamic traffic assignment simulation program (DTASP), developed in C language is used to assign the traffic dynamically on the road network, whereas method of successive averages (MSA) is modified and used to arrive at the DUE condition. The artificial intelligence technique of genetic algorithms (GAs) is applied to obtain the optimal signal setting parameters and path flow distribution factor for DUE condition. The methodology developed in such a way that joint optimization of signal setting parameters with DUE is obtained. The proposed method is applied to the real network data of Fort Area of Mumbai city comprising of 17 nodes and 56 unidirectional links with 72 Origin–Destination pairs, where all the 17 nodes are signalized intersections. The traffic flow condition for the optimized signal setting parameters is considerably improved compared to the existing signal settings. The results prove that the GA is an effective technique to solve the joint optimization problem for the real network data.     

基于工况分布的重型环卫货车 NOx排放模型

为提高城市重型环卫货车的NOx排放测算精度，本文提出一个基于工况分布的重型环卫货车NOx排放模型.首先，根据基于实测逐秒速度数据分析的环卫重型货车工况特征和 NO_x排放特性对不同负载货车的 VSP区间进行划分；其次，结合货车瞬时速度建立不同负载的环卫重型货车运行模式区间划分方法，并对不同负载货车NO_x排放因子进行测算.结果显示，空载货车在速度区间[0, 20) km/h 上，NOx排放因子大于满载，其他速度区间上相反.与基于 MOVES模型测算结果对比，在不同速度区间上，基于 MOVES的测算结果均比本文提出模型的测算结果偏低，如在低速区间[0，20) km/h，中速区间[20，50) km/h，高速区间[50，+∞) km/h：空载行驶时，分别低24.67%、6.82%和23.81%；满载行驶时，分别低12.38%、18.81%和26.43%.     

优化广西铁路建设项目顺序研究

在综合分析国家及区域"十二五"经济社会发展规划、中长期铁路网规划等规划基础上,预测研究年度区域各铁路客货运量、构成及其未来发展趋势;分析各铁路项目的功能定位及其在区域路网中发挥的运输效益;综合考虑经济效益、社会效益及国家宏观经济政策,提出优化广西铁路建设项目顺序和提高运能的方案,达到提前发挥投资效益的目的。     

Ant Colony Routing algorithm for freeway networks

Dynamic traffic routing refers to the process of (re)directing vehicles at junctions in a traffic network according to the evolving traffic conditions. The traffic management center can determine desired routes for drivers in order to optimize the performance of the traffic network by dynamic traffic routing. However, a traffic network may have thousands of links and nodes, resulting in a large-scale and computationally complex non-linear, non-convex optimization problem. To solve this problem, Ant Colony Optimization (ACO) is chosen as the optimization method in this paper because of its powerful optimization heuristic for combinatorial optimization problems. ACO is implemented online to determine the control signal – i.e., the splitting rates at each node. However, using standard ACO for traffic routing is characterized by four main disadvantages: 1. traffic flows for different origins and destinations cannot be distinguished; 2. all ants may converge to one route, causing congestion; 3. constraints cannot be taken into account; and 4. neither can dynamic link costs. These problems are addressed by adopting a novel ACO algorithm with stench pheromone and with colored ants, called Ant Colony Routing (ACR). Using the stench pheromone, the ACR algorithm can distribute the vehicles over the traffic network with less or no traffic congestion, as well as reduce the number of vehicles near some sensitive zones, such as hospitals and schools. With colored ants, the traffic flows for multiple origins and destinations can be represented. The proposed approach is also implemented in a simulation-based case study in the Walcheren area, the Netherlands, illustrating the effectiveness of the approach.     

人机混驾环境下基于LSTM的无人驾驶车辆换道行为模型

道路系统中的人机混驾交通环境是指人工驾驶车辆与自动驾驶车辆混合运行的交通环境，其中换道行为建模是人机混驾环境下无人驾驶车辆行为研究的热点。基于深度学习理论，构建人机混驾环境下基于长短期记忆神经网络的无人驾驶车辆换道行为模型（Long-short-term-memory-based Autonomous Vehicles Lane Changing，LSTM-LC）。通过研究人工驾驶车辆在换道过程中与周边车辆的相互作用，对换道行为影响因素进行分析；同时，为了提升模型的迁移性，引入道路横向偏移量信息。结合LSTM神经网络的输入要求，使用美国公开交通数据集Next Generation SIMulation（NGSIM）构建换道行为样本库。针对LSTM-LC模型，以均方差MSE作为损失函数，使用RMSprop优化方法进行训练，对LSTM网络结构、历史序列长度N及训练样本量3个重要参数进行标定。最后，针对道路横向偏移量M对LSTM-LC模型性能的影响进行对比试验。研究结果表明：相比GRU-LC模型，LSTM-LC模型对换道行为的表征更准确，在模型的精度和迁移性上有着显著的提升；GRU-LC模型的均方差为4.64 m²，迁移性均方差为119.82 m²，而LSTM-LC模型的均方差为3.18 m²，迁移性均方差为79.58 m²，分别优化了31.5%和39.71%；通过引入道路横向偏移量M，可将LSTM-LC模型精度和迁移性提升约10%，且模型稳定性更强。     

公交专用道设置标准研究——以南昌市为例

对公交专用道设置的重要影响因素进行交通工程学分析,确定各因素基本阈值。以设置规模为约束条件.建立南昌市交通模型,对各影响因素进行组合分析,以此确定各类组合条件阈值.形成南昌市公交专用道设置标准。     

Spatial econometric analysis of automobile and motorcycle traffic on Indonesian national roads and its socio-economic determinants: Is it local or beyond city boundaries?

The purpose of this paper is to verify the justification provided for a centralized national road policyin Indonesia, namely, that trips on national roads are typically inter-urban, by measuring the spatialdimensions of automobile and motorcycle trips on national roads in Indonesia. The study finds thatmotorcycle trips are characteristically local; by contrast, automobile trips extend beyond city boundaries,although to a limited extent. The results suggest the decentralization of transportation policies for thedevelopment and maintenance of national roads by granting autonomy to local governments when nofiscal externality exists. The results also indicate that road capacity, gasoline prices, income, populationand worker density, city size, and the number of public buses are strong predictors of vehicle kilometerstraveled.