A programmable calculation procedure for number of traffic conflict points at highway intersections

Traffic movement conflict points at intersections are the points at which traffic movements intersect (including crossing, merging, and diverging). Numbers and distribution of different types of conflict points are used to evaluate intersection access management designs and safety performance. Traditionally, the determination of the numbers of conflict points for different traffic movements is based on manual methods, which causes the difficulty for computerized procedures to evaluate safety performance of different access management designs. Sometimes, a programmable calculation procedure may provide more effective solutions as compared with manual methods. This paper presents a programmable calculation procedure for the determination of the numbers of conflict points, which could be used as a basis for a computerized procedure. Concepts of virtual movement lanes and intersection quadrants are introduced to specify types of intersections, traffic lane configurations, and traffic movement regulations. Calculation models, based on such concepts, for traffic movement conflict points at signalized and unsignalized intersections can be obtained. In support of the procedure, case studies are presented in the paper. The procedure presented in the paper can be programmed into a computer program for the purpose of a computerized evaluation of intersection safety and design performance of different access management or control approaches. Copyright © 2012 John Wiley & Sons, Ltd.     

重庆市两江新区疏唐互通立交方案设计浅析

重庆市两江新区基础设施快速建设,港口、码头、铁路、公路、城市道路之间相互交叉影响,以疏唐互通立交为例,浅述如何解决各项基础设施建设之间的矛盾,确保项目的顺利实施。     

高速公路左侧路肩设置必要性研究

尽管<公路工程技术标准>(JTG B01-2003)中规定八车道的高速公路应当设置2.5 m的左侧硬路肩,但国内几条刚刚改建完成的八车道高速公路中没有一条设置了左侧硬路肩,甚至没有宽于0.75 m的路缘带.研究运用可接受间隙理论计算了不同流量和车道数条件下车辆从最内侧车道穿插变道停驶到右侧路肩这一过程的概率和所需距离,并通过交通事故数据调研,分析了左侧路肩设置对提高交通安全的影响,从运行效率和交通安全两个方面定性和定量分析了左侧路肩设置的必要性.     

A preliminary proposal for urban and transportation planning in response to the Great East Japan Earthquake

The purpose of this paper is to propose information of use in the reconstruction of urban transport and infrastructure in response to the Great East Japan Earthquake. In particular, knowledge of urban planning and transportation planning is summarized to help in drawing up physical plans.     

Modeling the relationships among urban passenger travel carbon dioxide emissions,transportation demand and supply,population density,and proxy policy variables

To support the development of policies that reduce greenhouse gas (GHG) emissions by encouraging reduced travel and increased use of efficient transportation modes, it is necessary to better understand the explanatory effects that transportation, population density, and policy variables have on passenger travel related CO₂ emissions. This study presents the development of a model of CO₂ emissions per capita as a function of various explanatory variables using data on 146 urbanized areas in the United States. The model takes into account selectivity bias resulting from the fact that adopting policies aimed at reducing emissions in an urbanized area may be partly driven by the presence of environmental concerns in that area. The results indicate that population density, transit share, freeway lane-miles per capita, private vehicle occupancy, and average travel time have a statistically significant explanatory effect on passenger travel related CO₂ emissions. In addition, the presence of automobile emissions inspection programs, which serves as a proxy indicator of other policies addressing environmental concerns and which could influence travelers in making environmentally favorable travel choices, markedly changes the manner in which transportation variables explain CO₂ emission levels.     

Speed variation during peak and off-peak hours on urban arterials in Shanghai

Increased speed variation on urban arterials is associated with reductions in both operational performance and safety. Traffic flow, mean speed, traffic control parameters and geometric design features are known to affect speed variation. An exploratory study of the relationships among these variables could provide a foundation for improving the operational and safety performance of urban arterials, however, such a study has been hampered by problems in measuring speeds. The measurement of speed has traditionally been accomplished using spot speed collection methods such as radar, laser and loop detectors. These methods can cover only limited locations, and consequently are not able to capture speed distributions along an entire network, or even throughout any single road segment. In Shanghai, it is possible to acquire the speed distribution of any roadway segment, over any period of interest, by capturing data from Shanghai’s 50,000+ taxis equipped with Global Positional Systems (GPS). These data, hereafter called Floating Car Data, were used to calculate mean speed and speed variation on 234 road segments from eight urban arterials in downtown Shanghai. Hierarchical models with random variables were developed to account for spatial correlations among segments within each arterial and heterogeneities among arterials. Considering that traffic demand changes throughout the day, AM peak, Noon off-peak, and PM peak hours were studied separately. Results showed that increases in number of lanes and number of access points, the presence of bus stops and increases in mean speed were all associated with increased speed variation, and that increases in traffic volume and traffic signal green times were associated with reduced speed variation. These findings can be used by engineers to minimize speed differences during the road network planning stage and continuing through the traffic management phase.     

Options for reducing noise from roads and railway lines

The fundamental noise generation mechanisms of road and rail vehicles are discussed with attention to noise abatement measures. Based on an evaluation of publicly available tire noise data and the European road traffic noise emission model CNOSSOS, it is shown that on the road side there is a significant noise reduction potential in the usage of low-noise tires. From a three months measurement campaign a noise model was derived to predict the maximal sound pressure level of heavy duty vehicles during a pass-by in 7.5 m distance with the parameters vehicle speed and number of axles. With help of recently published information about external costs caused by heavy duty vehicles and the noise prediction tool, a model was developed to derive a money equivalent that can be used as a bonus/malus in a heavy duty vehicle fee. As a measure at the infrastructure, the installation of low-noise pavements is an effective, durable and economically attractive measure. Recent experiences with different technologies from all over the world are compiled and evaluated. On the rail side, an overview of the possible noise reduction strategies is given, followed by a discussion of the current policy and legislation in the EU and on the national level of different European countries.     

Short-term speed predictions exploiting big data on large urban road networks

Big data from floating cars supply a frequent, ubiquitous sampling of traffic conditions on the road network and provide great opportunities for enhanced short-term traffic predictions based on real-time information on the whole network. Two network-based machine learning models, a Bayesian network and a neural network, are formulated with a double star framework that reflects time and space correlation among traffic variables and because of its modular structure is suitable for an automatic implementation on large road networks. Among different mono-dimensional time-series models, a seasonal autoregressive moving average model (SARMA) is selected for comparison. The time-series model is also used in a hybrid modeling framework to provide the Bayesian network with an a priori estimation of the predicted speed, which is then corrected exploiting the information collected on other links. A large floating car data set on a sub-area of the road network of Rome is used for validation. To account for the variable accuracy of the speed estimated from floating car data, a new error indicator is introduced that relates accuracy of prediction to accuracy of measure. Validation results highlighted that the spatial architecture of the Bayesian network is advantageous in standard conditions, where a priori knowledge is more significant, while mono-dimensional time series revealed to be more valuable in the few cases of non-recurrent congestion conditions observed in the data set. The results obtained suggested introducing a supervisor framework that selects the most suitable prediction depending on the detected traffic regimes.     

Real-time automatic rescheduling strategy for an urban rail line by integrating the information of fault handling

In the operation of urban rails, faults are inevitable, which leads to deviation between the actual timetable and the planned timetable. In nowadays, timetable rescheduling strategies rarely integrate the information of fault handling. In this paper, we develop a real-time automatic rescheduling strategy, which integrates the dynamic information of fault handling. The rescheduled timetable is obtained by a mathematical optimization model, the constraints set of which is automatically generated and adjusted as more information of fault handling is feedback. Compared with the experience-based rescheduling methods, the automatic rescheduling strategy reacts more quickly, and uses the information of fault handling more efficiently. A simulation system for testing the automatic rescheduling strategy is built, which uses the data of the Beijing Yizhuang metro line. Via testing on the simulation system, the effectiveness and efficiency of the automatic rescheduling strategy are validated.