Dynamics of heterogeneity in urban networks: aggregated traffic modeling and hierarchical control

Real traffic data and simulation analysis reveal that for some urban networks a well-defined Macroscopic Fundamental Diagram (MFD) exists, which provides a unimodal and low-scatter relationship between the network vehicle density and outflow. Recent studies demonstrate that link density heterogeneity plays a significant role in the shape and scatter level of MFD and can cause hysteresis loops that influence the network performance. Evidently, a more homogeneous network in terms of link density can result in higher network outflow, which implies a network performance improvement. In this article, we introduce two aggregated models, region- and subregion-based MFDs, to study the dynamics of heterogeneity and how they can affect the accuracy scatter and hysteresis of a multi-subregion MFD model. We also introduce a hierarchical perimeter flow control problem by integrating the MFD heterogeneous modeling. The perimeter flow controllers operate on the border between urban regions, and manipulate the percentages of flows that transfer between the regions such that the network delay is minimized and the distribution of congestion is more homogeneous. The first level of the hierarchical control problem can be solved by a model predictive control approach, where the prediction model is the aggregated parsimonious region-based MFD and the plant (reality) is formulated by the subregion-based MFDs, which is a more detailed model. At the lower level, a feedback controller of the hierarchical structure, tries to maximize the outflow of critical regions, by increasing their homogeneity. With inputs that can be observed with existing monitoring techniques and without the need for detailed traffic state information, the proposed framework succeeds to increase network flows and decrease the hysteresis loop of the MFD. Comparison with existing perimeter controllers without considering the more advanced heterogeneity modeling of MFD highlights the importance of such approach for traffic modeling and control.     

Probe vehicle-based traffic state estimation method with spacing information and conservation law

This paper proposes a method of estimating a traffic state based on probe vehicle data that contain spacing and position of probe vehicles. The probe vehicles were assumed to observe spacing by utilizing an advanced driver assistance system, that has been implemented in practice and is expected to spread in the near future. The proposed method relies on the conservation law of the traffic flow but is independent of a fundamental diagram. The conservation law is utilized for reasonable aggregation of the spacing data to acquire the traffic state, i.e., a flow, density and speed. Its independence from a fundamental diagram means that the proposed method does not require predetermined nor exogenous assumptions with regard to the traffic flow model parameters. The proposed method was validated through a simulation experiment under ideal conditions and a field experiment conducted under actual traffic conditions; and empirical characteristics of the proposed method were investigated.     

交通运输综合执法提升水运企业监管效能的思考

文章以南通市交通综合行政执法为例,通过分析原执法模式存在的不足和问题,解析综合执法的意义,并对如何提升综合执法效能进行探讨。     

Competing risk mixture model and text analysis for sequential incident duration prediction

Predicting the duration of traffic incidents sequentially during the incident clearance period is helpful in deploying efficient measures and minimizing traffic congestion related to such incidents. This study proposes a competing risk mixture hazard-based model to analyze the effect of various factors on traffic incident duration and predict the duration sequentially. First, topic modeling, a text analysis technique, is used to process the textual features of the traffic incident to extract time-dependent topics. Given four specific clearance methods and the uncertainty of these methods when used during traffic incidents, the proposed mixture model uses the multinomial logistic model and parametric hazard-based model to assess the influence of covariates on the probability of clearance methods and on the duration of the incident. Subsequently, the performance of estimated mixture model in sequentially predicting the incident duration is compared with that of the non-mixture model. The prediction results show that the presented mixture model outperforms the non-mixture model.     

Predicting travel time reliability using mobile phone GPS data

Estimates of road speeds have become commonplace and central to route planning, but few systems in production provide information about the reliability of the prediction. Probabilistic forecasts of travel time capture reliability and can be used for risk-averse routing, for reporting travel time reliability to a user, or as a component of fleet vehicle decision-support systems. Many of these uses (such as those for mapping services like Bing or Google Maps) require predictions for routes in the road network, at arbitrary times; the highest-volume source of data for this purpose is GPS data from mobile phones. We introduce a method (TRIP) to predict the probability distribution of travel time on an arbitrary route in a road network at an arbitrary time, using GPS data from mobile phones or other probe vehicles. TRIP captures weekly cycles in congestion levels, gives informed predictions for parts of the road network with little data, and is computationally efficient, even for very large road networks and datasets. We apply TRIP to predict travel time on the road network of the Seattle metropolitan region, based on large volumes of GPS data from Windows phones. TRIP provides improved interval predictions (forecast ranges for travel time) relative to Microsoft’s engine for travel time prediction as used in Bing Maps. It also provides deterministic predictions that are as accurate as Bing Maps predictions, despite using fewer explanatory variables, and differing from the observed travel times by only 10.1% on average over 35,190 test trips. To our knowledge TRIP is the first method to provide accurate predictions of travel time reliability for complete, large-scale road networks.     

基于代理的城市交通信息网格服务系统

城市交通信息服务作为智能交通系统的重要组成部分，其发展大多处于分散重复的建设阶段。本文在分析了网格技术与代理技术各自的优势基础上，提出了基于代理的城市交通信息网格服务系统，并给出了结构模型。通过代理技术和网格技术的结合，整合现有资源提高城市交通信息的服务效率。     

关于建立宁波液化品自由港的探讨

宁波港是世界著名的深水良港,自然条件得天独厚。宁波液化品自由港位于中国的炼化产业带,区位优势明显,硬件设施先进,管理规范,是国内吞吐能力最大的液化品专业港。由于缺乏良好的关税环境,宁波液化品港在与韩、日港口的竞争中处于劣势。鉴此,就建立宁波液化品自由港的意义、条件和发展进行了探讨,以期为建立宁波液化品自由港,为我国液化品运输的发展和我国炼化行业的降本增效提供参考。     

氟对培养的软骨细胞生长的影响

本文报道了氟对培养的软骨细胞生长的影响。传代兔关节软骨细胞在不同氟浓度培养液中培养192 h,结果显示:细胞生长和基质产生量均与氟浓度呈负相关。光镜形态观察各组间未见明显差异。     

浅谈企业文化与企业经营管理

企业文化是企业的灵魂,是企业成熟和成熟企业走向成功的标志。在知识经济时代,竞争已经从产品、人才扩展到了文化领域,成功的企业必然得力于成功的文化,中国的企业特别需要建立起独特的、优秀的企业文化。然而,企业文化的建设需要通过长期艰苦的努力;需要各级领导干部身体力行,常抓不懈;需要及时调整企业的人力资源管理系统,对员工施加影响,潜移默化,逐步实现对旧文化的扬弃和新文化的推广。     

铁路行车调度系统数据结构分析与设计

分析铁路行车调度系统基本结构和功能。利用面向对象分析技术和数据结构理论,对铁路行车调度系统中的信息进行抽象,提出一种以列车为中心的十字链表数据存储结构,提出调整计划的数据帧结构形成算法Ajustment()和在屏幕上画运行线的算法DrawCurve()。并对算法的复杂性进行分析,所有算法的复杂度与问题的规模呈线性关系。系统具有较高的执行效率。