Going fast or going green? Evidence from environmental speed limits in Norway

This paper studies the impact of speed limits on local air pollution using a series of date-specific speed limit reductions in Oslo over the 2004–2011 period. We find that lowering the speed limit from 80 to 60 km/h reduces travel speed by 5.8 km/h. However, we find no evidence of reduced air pollution as measured next to the treated roads. Our estimates suggest an annual time loss of the speed limit reductions of 66 USD per affected vehicle. Our findings imply that policy makers need to consider other actions than speed limit reductions to improve local air quality.     

Forecasting journey time distribution with consideration to abnormal traffic conditions

Travel time is an important index for managers to evaluate the performance of transportation systems and an intuitive measure for travelers to choose routes and departure times. An important part of the literature focuses on predicting instantaneous travel time under recurrent traffic conditions to disseminate traffic information. However, accurate travel time prediction is important for assessing the effects of abnormal traffic conditions and helping travelers make reliable travel decisions under such conditions. This study proposes an online travel time prediction model with emphasis on capturing the effects of anomalies. The model divides a path into short links. A Functional Principal Component Analysis (FPCA) framework is adopted to forecast link travel times based on historical data and real-time measurements. Furthermore, a probabilistic nested delay operator is used to calculate path travel time distributions. To ensure that the algorithm is fast enough for online applications, parallel computation architecture is introduced to overcome the computational burden of the FPCA. Finally, a rolling horizon structure is applied to online travel time prediction. Empirical results for Guangzhou Airport Expressway indicate that the proposed method can capture an abrupt change in traffic state and provide a promising and reliable travel time prediction at both the link and path levels. In the case where the original FPCA is modified for parallelization, accuracy and computational effort are evaluated and compared with those of the sequential algorithm. The proposed algorithm is found to require only a piece rather than a large set of traffic incident records.     

Probe vehicle data sampled by time or space: Consistent travel time allocation and estimation

A characteristic of low frequency probe vehicle data is that vehicles traverse multiple network components (e.g., links) between consecutive position samplings, creating challenges for (i) the allocation of the measured travel time to the traversed components, and (ii) the consistent estimation of component travel time distribution parameters. This paper shows that the solution to these problems depends on whether sampling is based on time (e.g., one report every minute) or space (e.g., one every 500 m). For the special case of segments with uniform space-mean speeds, explicit formulae are derived under both sampling principles for the likelihood of the measurements and the allocation of travel time. It is shown that time-based sampling is biased towards measurements where a disproportionally long time is spent on the last segment. Numerical experiments show that an incorrect likelihood formulation can lead to significantly biased parameter estimates depending on the shapes of the travel time distributions. The analysis reveals that the sampling protocol needs to be considered in travel time estimation using probe vehicle data.     

An innovative model to estimate the accessibility of a destination by public transport

Accessibility is a valuable indicator for assessing the effectiveness of a transport network. Nevertheless, its analysis can lead to very heterogeneous results depending on the method adopted, thus still struggling to be considered by policy makers and in planning processes. This article contributes to the development of an accessibility analysis as a planning tool, by proposing an alternative model to estimate the relative accessibility of a destination by public transport (PT). Indeed, PT is a mobility paradigm that has been supported to reduce the negative externalities produced by private transport, especially in environmentally fragile contexts. The model includes a set of eleven factors affecting public transport operation which refer to four macro topics: connectivity, multimodality, tariff/ticketing, and info-mobility. They are integrated into a Public Transport Accessibility index which analyses a series of nodes along a route and detects the progressive variation of accessibility. Eventual shifts are highlighted, including information about the factors feeding them. The model is tested for the Lana-Zurich (IT-CH) connection, showing how the most relevant issues are caused by difficulties in the transnational and transregional integration of the services. Through this process, the model aims at backing policy makers in the detection and understanding of public transport barriers and related causes.     

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.     

路面平整度对标线逆反射测试的静态影响

为了明确路面平整度对道路交通标线逆反射亮度系数测试的静态影响机理，减小工程应用中的误差，针对手持式逆反射测量仪和车载式逆反射测量仪，在忽略仪器测量基准平面偏差的前提下，参考公路工程质量检验评定标准中路面平整度“最大间隙”的要求，分析路面平整度影响下的现场测试几何条件，提出逆反射标线板设计方案及其参考值赋值方法，开展手持式逆反射测量仪和车载式逆反射测量仪的测量偏差试验。在逆反射标线板参考值赋值过程中发现，反射照度随着入射角的增大而降低，同逆反射亮度系数随入射角变化产生的变化趋势呈非线性关系。手持式逆反射测量仪和车载式逆反射测量仪无法识别入射角产生的偏差，仅通过测得的反射信号强度计算得到逆反射亮度系数，因此其变化趋势和反射照度随入射角变化的趋势相近。入射角偏差对车载式逆反射测量仪测量结果引入的相对不确定度u_r22为4.8%，对开放光路的手持式逆反射测量仪测量结果引入的相对不确定度u_r12为7.4%。研究结果表明：入射角偏差对道路交通标线逆反射亮度系数的现场测量结果影响较大，在现场测量时应注意调整仪器的放置位置；车载式逆反射测量仪较手持式逆反射测量仪抗干扰的能力更强，在路面平整度较差的路段选用车载式逆反射测量仪并进行数据修正能够提高测量结果的可信度；建议车载式逆反射测量仪选取9 m内最大高程差不超过7 mm的路段进行现场自校准。     

A meta-analysis of Western European external costs estimates

This paper analyses the external transport cost estimates that have been found in various European studies. These estimates seem at first glance to be highly dispersed, a fact which raises questions about their reliability. The article offers a list of the possible reasons for discrepancies between the various studies; differences in the specific situations studied, in the type of cost calculated, in the physical laws relating to emissions, in the measurement of values of external costs. It assesses the relative magnitude of each of these causes through a meta-analysis. It turns out that the main differences come from the specificity of the situation under review and the type of cost calculated. In comparison, differences in the laws and in the values methods have a lower importance. The conclusion is that the estimates of external costs are reliable for decision-making policies.     

板桩码头的有限元解法及计算机处理

介绍采用竖向弹性地基梁法计算板桩码头的要点。     

城市轻轨车辆最佳运行控制方案的研究

本文给出一种利用微型机实现城市轨道车辆最佳运行的控制方案,即在变化的外界条件下确定断电和制动时刻,以指导司机驾驶车辆,实现能耗最小和准时运行.该控制方案的特点是不断地利用实测值并结合估算确定断电和制动时刻,简单易行.     

FAULT IDENTIFICATION IN HETEROGENEOUS NETWORKS USING TIME SERIES ANALYSIS

Fault management is crucial to provide quality of service grantees for the future networks, and fault identification is an essential part of it. A novel fault identification algorithm is proposed in this paper, which focuses on the anomaly detection of network traffic. Since the fault identification has been achieved using statistical information in management information base, the algorithm is compatible with the existing simple network management protocol framework. The network traffic time series is verified to be non-stationary. By fitting the adaptive autoregressive model, the series is transformed into a multidimensional vector. The training samples and identifiers are acquired from the network simulation. A k-nearest neighbor classifier identifies the system faults after being trained. The experiment results are consistent with the given fault scenarios, Which prove the accuracy of the algorithm. The identification errors are discussed to illustrate that the novel fault identification algorithm is adaptive in the fault scenarios with network traffic change.