基于HLA的智能交通信息试验平台研究

从智能交通信息平台的概念出发,研究利用已有的智能交通系统资源建立智能交通信息试验平台。首先对比分析了已有的平台体系结构开发方法,即面向过程的开发方法和面向对象的开发方法,两者都已不能适应复杂大系统的开发需求。通过引入计算机建模与仿真领域的HLA（高层体系结构）技术,创造性地提出了基于HLA的体系结构开发方法,结合信息试验平台需求分析,设计了智能交通信息试验平台的逻辑结构。平台分4层来组织,分别是基础数据层、数据库层、应用服务层和用户主体层,在若干接口程序的衔接下,各类联邦成员协同作用以实现信息平台的功能。结合现有的技术设备条件,实现了信息平台的物理连接。平台搭建后运营正常,已接入信息平台的ITS系统包括车载导航系统和城市商用车辆调度系统,并为其他子系统的接入预留了接口。     

智能车辆安全辅助驾驶技术研究近况

论述了安全辅助驾驶技术的研究现状、研究的必要性以及研究进展。安全辅助驾驶技术包括车道偏离预警与保持、前方车辆探测及安全车距保持、行人检测、驾驶员行为监测、车辆运动控制与通讯等。分析了各种传感器的优缺点及其在实际应用过程中存在的问题,基于单一传感器不能很好地解决安全辅助驾驶技术可靠性和环境适应能力的要求,应结合激光雷达技术解决图像模糊问题,利用红外传感器增强机器视觉识别的可靠性,未来的安全辅助驾驶技术应该采取多种传感器融合的技术,结合毫米波雷达和激光雷达系统具有深度测量精确的特点,将极大的推动汽车安全辅助驾驶系统的应用和推广。     

多尺度图像边缘检测技术在车辆识别中的应用

指出了图像边缘检测的定义及现有算法的不足,并对Canny边缘检测离散准则及该准则下的最优线性滤波器进行了论述。根据边缘检测离散准则,利用数值方法求出该准则下边缘检测的最优线性滤波器及对应的平滑算子,将其与Canny边缘检测技术相结合进行边缘检测,检测出不同尺度下多幅边缘图像,并根据小尺度下图像边缘细节信息丰富、边缘定位精度高,大尺度下图像边缘稳定、抗噪性好等特点,将检测到的多尺度边缘进行融合,得到抗噪性好的精确的单像素宽边缘;同时将该方法应用于汽车特征提取,检测到完整连续的汽车边缘图像,为车型识别提供条件。试验结果表明:该方法不仅能准确检测出图像边缘,而且能有效地抑制噪声,是边缘检测的实用方法。     

小型运输船船型经济性论证分析

文章根据大连湾老铁山水道的情况,考虑变吃水的运输方式,以船长、船宽、吃水及航速作为变量来进行船型方案的组合。选用净现值、内部收益率、投资回收期、必要运费率和综合经济指标作为衡量船型方案的标准,通过分析计算得出最佳的船型方案,为小型渔货船型选择提供参考。     

基于机器视觉的智能车辆前方道路边界及车道标识识别方法综述

为了全面了解国内外在基于机器视觉的智能车辆前方道路边界及车道标识识别领域的研究进展，文章介绍了近年来一些典型的基于机器视觉的道路边界及车道标识识别系统，对基于机器视觉的前方道路边界及车道标识识别方法进行了分类，对各大类方法中采用的不同技术进行了阐述，然后对基于机器视觉与其他传感器融合的识别方法进行了总结，最后就该领域的研究难点及发展趋势进行了简要论述。     

公路客运班车报停制度研究

公路客运峰谷现象明显,在运能、运力有限的情况下,如何才能更好地满足客运高峰期(如春运)的交通需求是政府和企业的一项重要课题。现有的政策并没有使有限的客运资源得到最合理的利用,给能源和环境都带来了一定的影响。文章较系统地从企业和政府两个角度论述了建立班车报停制度的必要性和可行性,通过对客运线路的调查,对公路客运班车报停制度的社会经济效益作了定性和定量分析。     

优化理论在沥青路面机械化施工中的应用

针对政道路改扩建工程中，多搅拌站供料和多工地同时施工的现象，在确保机械化施工连续性的条件下，利用优化算法确定在不同的施工阶段，各搅拌的最佳供给量，并以此为基础，合理安排生产，调度运输车辆,轴时以施工实例给出具体计算过程。     

智能交通系统及其车辆自动控制技术

本文简要介绍了智能交通系统的概念、发展状况、基本内容和研究开发过程，进一步阐述了智能交通系统中的先进车辆控制技术。综述了汽车纵向控制、横向控制、自动驾驶及车列控制。最后，对我国如何发展智能交通系统和先进车辆自动控制技术进行了探讨。     

A study of the environmental impacts of intelligent automated vehicle control at intersections via V2V and V2I communications

This article presents a novel intersection traffic management system for automated vehicles and quantifies its impact on fuel consumption and greenhouse gas emissions of CO₂ relative to traditional traffic signal and roundabout intersection control. The developed intelligent traffic management (ITM) techniques, which are based on a spatiotemporal reservation scheme, ensure that vehicles proceed through the intersection without colliding with other vehicles while at the same time reducing the intersection delay and environmental impacts. Specifically, the spatiotemporal reservation scheme provides each vehicle a collision-free path that is decomposed into a speed profile along with navigational instructions. The integration of the developed microscopic traffic simulator with instantaneous emission model, provides improved assessments of the environmental impact of traffic control strategies at intersections. The simulator architecture integrates several ITM algorithms, vehicle sensors, V2V/V2I communications, and emission and fuel consumption models. Each vehicle is modeled by an agent and each agent provides information depending on the specific vehicle sensors. The ITM system is supported by V2V and V2I communications, allowing the exchange of information among vehicles and infrastructure. The data include the estimated vehicle position and speed. Compared with traditional traffic management techniques, the simulation results prove that the proposed ITM system reduces CO₂ emissions significantly. The research also shows that these reductions are more significant when the traffic flow increases.     

Exchange rate and transport cost sensitivities of bilateral freight flows between the US and China

This paper explores the long-run impacts of gross domestic product, exchange rate, and transport costs on bilateral air and ocean freight flows between the US and China. The study employs a cointegration framework by using export and import data over the period of 2003:Q1-2014:Q2. Results show that gross domestic product is the key determinant of bilateral freight flows, indicating that real income of a trading partner is a driving force of the bilateral freight flows between the US and China. In examining the sensitivities of the bilateral trade flows, air freight flows are found to be more responsive to a real income change than ocean freight flows. The bilateral exchange rate is a significant factor affecting the freight flows from China to the US, suggesting that a US dollar appreciation against the Chinese yuan increases the inflows of Chinese commodities to the US. The impacts of the bilateral exchange rate and transport cost are found to vary at industry and commodity levels. These findings support the importance of employing disaggregate data in the bilateral freight flow analysis.