浅谈当前交调工作意义与存在的问题

交调工作是公路规划、建设的重要基础工作,详细地分析了交调工作的意义及河北省开展现状及存在的问题,并提出相应建议。     

高速公路意外事件影响下的车辆跟驰模型

应用智能主体技术,针对双向四车道高速公路意外事件影响下的车辆跟驰行为,建立了基于智能主体的车辆跟驰模型,利用西部高速公路交通调查统计的数据,对车辆主体的间距愿望进行了定量分析,利用比例微分控制确定车辆主体的加速度响应,建立了不同加速度队列的逻辑意图,使模型的加速度响应符合车辆的动力特性。利用开发的EAD-Simulation系统,在特定和随机两种不同过程下对模型进行的测试表明:利用智能主体技术描述高速公路意外事件影响下的跟驰行为,可充分发挥其个性、自治性和自适应性的特点,在主体的属性描述中利用比例微分控制“类阻尼”的特性,可有效地对车辆主体的稳定性进行控制。     

高速公路动态交通流Elman神经网络模型

为了提高高速公路交通流建模的精度,分析了离散的高速公路动态交通流数学模型,基于Elman网络原理,建立了回归神经网络交通流模型。回归神经网络的输入层、上下文层、隐含层和输出层的节点数目分别选为8、30、30和2,采用Levenberg-Marquardt算法对回归神经网络进行训练,并对一条5路段的高速公路进行仿真。结果表明:回归神经网络平均相对误差为8.683 7×10-5,最大相对误差为4.237 1×10-4,与BP神经网络和RBF神经网络相比较,Elman回归神经网络能更好地逼近交通流数学模型,真实地描述交通流基本特性,能准确地建立动态交通流模型,适应交通状况的变化。     

基于串联排队网络的三峡-葛洲坝水利枢纽联合调度模型

为了提高三峡-葛洲坝水利枢纽的整体通过能力,分析了三峡-葛洲坝水利枢纽联合调度的实际需求,建立了三峡-葛洲坝水利枢纽联合调度数学模型,考虑了闸室面积利用率最大、整体待闸时间最小两个目标函数和船舶编排过程中的八个约束,应用串联排队网络理论求解模型。算法将申报船舶按照航向分成四个船舶序列,动态计算每艘船舶的权重,兼顾船舶长度与宽度优先,待闸时间约束、葛洲坝船闸通航条件限制和任务均衡的要求,循环排船,逐步优化。应用结果表明应用该数学模型和编排算法编制一个计划期的两坝五闸计划仅需2 min,编排时间短,葛洲坝2#船闸的闸室面积利用率高于70%,并且客船和旅游观光船均排在前面的闸次中,说明客船的待闸时间约束是满足的,并且在航向上是上下航向交替运行,没有出现倒闸情况,编制的计划满足实际调度需要。     

基于服务质量招投标的出租车市场准入与退出机制

对中国现行出租车市场行政审批、拍卖、定额招标等主要准入模式存在的弊端进行了分析,指出出租车市场准入与退出机制应促进服务质量竞争,促进企业自身建设,促进运营模式改革,并维护行业稳定,建立一个以服务质量招投标为主要手段的出租车市场准入与退出机制,对实施服务质量招投标制度需解决的政策法规配套、服务质量评价体系构建、经营权有偿使用制度改革以及新老政策衔接等关键问题提出了建议。实际应用表明该机制可以较好地化解政府、出租车公司、出租车驾驶员之间的利益矛盾,促进行业自身建设,加强行业服务竞争,提高行业服务水平。     

客滚码头前沿功能区布置及交通组织仿真优化

以安全事故频发的客滚码头前沿区域作为研究对象,提出通过将该区域进行精细化布置以及合理交通组织的方式,提高码头前沿作业的安全性与便捷性。为获得区域行人密度、在港时间、行走距离及卸船作业时间等评价指标,建立客滚码头前沿作业系统微观仿真模型。并以某客滚码头泊位为例,分析码头前沿功能区布置及交通组织方案对客滚码头前沿作业评价指标的影响,并给出推荐方案。实例证明,客滚码头前沿功能区精细化布置及合理交通组织有利于减少安全事故,并提升前沿作业便捷性。     

Spatiotemporal traffic forecasting: review and proposed directions

This paper systematically reviews studies that forecast short-term traffic conditions using spatial dependence between links. We extract and synthesise 130 research papers, considering two perspectives: (1) methodological framework and (2) methods for capturing spatial information. Spatial information boosts the accuracy of prediction, particularly in congested traffic regimes and for longer horizons. Machine learning methods, which have attracted more attention in recent years, outperform the naïve statistical methods such as historical average and exponential smoothing. However, there is no guarantee of superiority when machine learning methods are compared with advanced statistical methods such as spatiotemporal autoregressive integrated moving average. As for the spatial dependency detection, a large gulf exists between the realistic spatial dependence of traffic links on a real network and the studied networks as follows: (1) studies capture spatial dependency of either adjacent or distant upstream and downstream links with the study link, (2) the spatially relevant links are selected either by prejudgment or by correlation-coefficient analysis, and (3) studies develop forecasting methods in a corridor test sample, where all links are connected sequentially together, assume a similarity between the behaviour of both parallel and adjacent links, and overlook the competitive nature of traffic links.     

In search of surrogate safety indicators for vulnerable road users: a review of surrogate safety indicators

Surrogate indicators are meant to be alternatives or complements of safety analyses based on accident records. These indicators are used to study critical traffic events that occur more frequently, making such incidents easier to analyse. This article provides an overview of existing surrogate indicators and specifically focuses on their merit for the analyses of vulnerable road users and the extent to which they have been validated by previous research. Each indicator is evaluated based on its ability to consider the collision risk, which can be further divided into the initial conditions of an event, the magnitude of any evasive action and the injury risk in any traffic event. The results show that various indicators and their combinations can reflect different aspects of any traffic event. However, no existing indicator seems to capture all aspects. Various studies have also focused on the validity of different indicators. However, due to the use of diverse approaches to validation, the large difference in how many locations were investigated and variations in the duration of observation at each location, it is difficult to compare and discuss the validity of the different surrogate safety indicators. Since no current indicator can properly reflect all the important aspects underlined in this article, the authors suggest that the choice of a suitable indicator in future surrogate safety studies should be made with considerations of the context-dependent suitability of the respective indicator.     

多智能体仿真在LNG码头选址及港口规划中的应用

液化天然气(LNG)船舶进出港进行的严格交通管制会影响港口的运营,因此在港口规划阶段须审慎决策LNG码头选址及布局问题。应用自主开发的《基于多智能体信息交互的港口运营系统仿真软件(简称:APSS)V1.0》,建立可模拟涵盖LNG船舶通航影响机制的港口运营系统仿真模型;以实际工程为例,系统探讨LNG船舶通航对近、远期港口运营影响问题的思路和方法;结合水域通航环境特点提出远期优化措施。研究结果可辅助港口规划制定。