都市区轨道交通多层次各制式量化选择方法研究

为探讨多层次各制式选择方法的量化问题,更为精准、经济、因地制宜地选择轨道交通制式,在线网规划及相关前期工作时就能够基本确定制式,为后续进一步研究确立基础。汇总市域、大运量、中低运量各类轨道交通制式的技术参数,研究基于客流走廊特征、节点重要度、节点联系强度的轨道交通制式选择方法,并以大西安都市区为实例进行分析,考虑节点重要度、联系强度因素,将走廊客流量级与各制式量级进行匹配,进而确定各走廊适宜的制式。结果表明,通过该方法进行制式选择分析更为精确,能够体现城市结构特征,并满足不同层次的交通需求。     

物流园区规划建设规模确定方法

提出了一套确定合适物流园区建设规模的方法, 确定了区域物流园区建设总规模与各个物流园区的建设规模, 给出了经验计算公式及各系数具体的测算方法。比例汇总和类比分析表明, 该方法主观因素少, 易于量化, 操作性强。     

动态交通数据故障识别与修复方法

为提高交通模型输入信息的可靠性,通过对交通传感器采集到的动态交通数据的故障进行识别,并根据不同的故障种类采取补充、还原或修正等方法对数据进行修复。分析结果表明,动态交通数据的故障识别与修复方法是可行的,尤其是对数据的补充处理,可以很好地解决因为数据丢失而给后续处理带来的困难。     

多相位信号控制交叉口行人相位设置方法

运用相位组合技术,对行人相位与机动车相位的各种可能的组合进行了研究,提出了二次过街条件下行人相位的设计方法。与传统行人相位设计方法的对比分析表明这种行人相位设计方法缩短了行人过街最短绿灯时间,降低了过街人均延误。     

高速公路交通安全模糊评价与实例分析

结合交通安全管理实际,将模糊评价方法引入交通安全,并进行实例分析,对该方法进行了具体论证,为建立相应的专家系统奠定了基础。     

浅谈交通运输企业运用环境会计问题

要想实现环境和经济协调持续发展的奋斗目标,就很有必要将环境会计理论运用到交通运输业会计理论体系中。从环境会计兴起与发展谈起,对交通运输企业运用环境会计的必要性、内容及会计信息的披露方式进行了论述。     

多方式协调发展的运输通道布局规划体系

对中国运输通道内各种交通运输方式现状规划与实施方法进行了分析, 归纳了当前运输通道在规划建设理念、对象、功能、衔接等方面存在的不足之处, 立足于运输通道经济与运输特性, 采用系统分析方法建立了多方式协调发展的运输通道布局规划的理论体系、规划研究内容及实现方法。分析表明, 将区位理论、功能分析、方式优势分析等环节纳入通道布局研究, 可包容当前各方式规划的有效环节, 并可弥补不足, 增强运输通道线位确定、功能规划、衔接规划、技术评价方法的协调性, 将多种运输方式在规划布局阶段协调起来。     

单线区段列车运行图的自动化调整方法

介绍了在列车运行情况已知的条件下, 在(t₁, t₂]时间域内对列车运行图的自动化调整方法, 提出了用列车晚点加权总时分作为评价列车运行图调整优劣的指标, 并建立了指标优化的数学模型和简化模型。把简化模型构成网络图, 并使用分支定界法设计了列车运行图调整的算法。通过模拟编程验证, 该算法可行、有效, 能在较短的时间内得出较理想的3~4 h列车运行图。     

Conflict-free arrival and departure trajectory planning for parallel runway with advanced point-merge system

In this paper, an efficient trajectory planning system is proposed to solve the integration of arrivals and departures on parallel runways with a novel route network system. Our first effort is made in designing an advanced Point Merge (PM) route network named Multi-Level Point Merge (ML-PM) to meet the requirements of parallel runway operations. Then, more efforts are paid on finding a complete and efficient framework capable of dynamically modelling the integration of arrival and departure trajectories on parallel runways, modelling the conflict detection and resolution in presence of curved trajectory and radius-to-fix merging process. After that, a suitable mathematical optimization formulation is built up. Receding Horizon Control (RHC) and Simulated Annealing (SA) algorithms are proposed to search the near-optimal solution for the large scale trajectories in routine dense operations. Taking Beijing Capital International Airport (BCIA) as a study case, the experimental results show that our system shows good performances on the management of arrivals and departures. It can automatically solve all the potential conflicts in presence of dense traffic flows. With its unique ML-PM route network, it can realize a shorter flying time and a near-Continuous Descent Approach (CDA) descent for arrival aircraft, an economical climbing for departure aircraft, an easier runway allocation together with trajectory control solutions. It shows a good and dynamic sequencing efficiency in Terminal Manoeuvring Area (TMA). In mixed ML-PM mode, under tested conditions, our proposed system can increase throughput at BCIA around 26%, compared with baseline. The methodology defined here could be easily applied to airports worldwide.     

Field tests of a dynamic green driving strategy based on inter-vehicle communication

This paper presents the design and results for field tests regarding the environmental benefits in stop-and-go traffic of an algorithmic green driving strategy based on inter-vehicle communication (IVC), which was proposed in Yang and Jin (2014). The green driving strategy dynamically calculates advisory speed limits for vehicles equipped with IVC devices so as to smooth their speed profiles and reduce their emissions and fuel consumption. For the field tests, we develop a smartphone-based IVC system, in which vehicles’ speeds and locations are collected by GPS and accelerometer sensors embedded in smartphones, and communications among vehicles are enabled by specially designed smartphone applications, a central server, and 4G cellular networks. Six field tests are carried out on an uninterrupted ring road under slow or fast stop-and-go traffic conditions. We compare the performances of three alternatives: no green driving, heuristic green driving, and the IVC-based algorithmic green driving. Results show that heuristic green driving has better smoothing and environmental effects than no green driving, but the IVC-based algorithmic green driving outperforms both. In the future, we are interested in field tests under more realistic traffic conditions.