On the use of Lagrangian observations from public transport and probe vehicles to estimate car space-mean speeds in bi-modal urban networks

The Macroscopic Fundamental Diagram (MFD) has been recognized as a powerful framework to develop network-wide control strategies. Recently, the concept has been extended to the three-dimensional MFD, used to investigate traffic dynamics of multi-modal urban cities, where different transport modes compete for, and share the limited road infrastructure. In most cases, the macroscopic traffic variables are estimated using either loop detector data (LDD) or floating car data (FCD). Taking into account that none of these data sources might be available, in this study we propose novel estimation methods for the space-mean speed of cars based on: (i) the automatic vehicle location (AVL) data of public transport where no FCD is available; and (ii) the fused FCD and AVL data sources where both are available, but FCD is not complete. Both methods account for the network configuration layout and the configuration of the public transport system. The first method allows one to derive either uni-modal or bi-modal macroscopic fundamental relationships, even in the extreme cases where no LDD nor FCD exist. The second method does not require a priori knowledge about FCD penetration rates and can significantly improve the estimation accuracy of the macroscopic fundamental relationships. Using empirical data from the city of Zurich, we demonstrate the applicability and validate the accuracy of the proposed methods in real-life traffic scenarios, providing a cross-comparison with the existing estimation methods. Such empirical comparison is, to the best of our knowledge, the first of its kind. The findings show that the proposed AVL-based estimation method can provide a good approximation of the average speed of cars at the network level. On the other hand, by fusing the FCD and AVL data, especially in case of sparse FCD, it is possible to obtain a more representative outcome regarding the performance of multi-modal traffic.     

An online speed profile generation approach for efficient airport ground movement

The precise guidance and control of taxiing aircraft based on four-dimensional trajectories (4DTs) has been recognised as a promising means to ensure safe and efficient airport ground movement in the context of ever growing air traffic demand. In this paper, a systematic approach for online speed profile generation is proposed. The aim is to generate fuel-efficient speed profiles respecting the timing constraints imposed by routing and scheduling, which ensures conflict-free movement of aircraft in the planning stage. The problem is first formulated as a nonlinear optimisation model, which uses a more flexible edge-based speed profile definition. A decomposed solution approach (following the framework of matheuristic) is then proposed to generate feasible speed profiles in real time. The decomposed solution approach reduces the nonlinear optimisation model into three tractable constituent problems. The control point arrival time allocation problem is solved using linear programming. The control point speed allocation problem is solved using particle swarm optimisation. And the complete speed profile between control points is determined using enumeration. Finally, improved speed profiles are generated through further optimisation upon the feasible speed profiles. The effectiveness and advantages of the proposed approach are validated using datasets of real-world airports.     

Maximizing airborne delay at no extra fuel cost by means of linear holding

This paper introduces a linear holding strategy based on prior works on cruise speed reduction, aimed at performing airborne delay at no extra fuel cost, as a complementary strategy to current ground and airborne holding strategies. Firstly, the equivalent speed concept is extended to climb and descent phases through an analysis of fuel consumption and speed from aircraft performance data. This gives an insight of the feasibility to implement the concept, differentiating the case where the cruise flight level initially requested is kept and the case where it can be changed before departure in order to maximize the linear holding time. Illustrative examples are given, where typical flights are simulated using an optimal trajectory generation tool where linear holding is maximized while keeping constant the initially planned fuel. Finally, the effects of linear holding are thoroughly assessed in terms of the vertical trajectory profiles, range of feasible speed intervals and trade-offs between fuel and time. Results show that the airborne delay increases significantly with nearly 3-fold time for short-haul flights and 2-fold for mid-hauls to the cases in prior works.     

Adaptive traffic parameter prediction: Effect of number of states and transferability of models

Traffic parameters can show shifts due to factors such as weather, accidents, and driving characteristics. This study develops a model for predicting traffic speeds under these abrupt changes within regime switching framework. The proposed approach utilizes Hidden Markov, Expectation Maximization, Recursive Least Squares Filtering, and ARIMA methods for an adaptive forecasting method. The method is compared with naive and mean updating linear and nonlinear time series models. The model is fitted and tested extensively using 1993 I-880 loop data from California and January 2014 INRIX data from Virginia. Analysis for number of states, impact of number of states on forecasting, prediction scope, and transferability of the model to different locations are investigated. A 5-state model is found to be providing best results. Developed model is tested for 1-step to 45-step forecasts. The accuracy of predictions are improved until 15-step over nonadaptive and mean adaptive models. Except 1-step predictions, the model is found to be transferable to different locations. Even if the developed model is not retrained on different datasets, it is able to provide better or close results with nonadaptive and adaptive models that are retrained on the corresponding dataset.     

Fuel economy of hybrid-electric versus conventional gasoline vehicles in real-world conditions: A case study of cold cities in Quebec,Canada

This paper investigates the fuel efficiency of commercial hybrid electric vehicles (HEVs) and compares their performance with respect to standard gasoline vehicles in the context of cold Canadian urban environments. The effect of different factors on fuel efficiency is studied including road driving conditions (link type, city size), temperature, speed, cold-starts and eco-driving training. For this study, fuel consumption data at the link level in real-world conditions was used from a sample of 74 instrumented vehicles. From the study fleet, 21 vehicles were HEVs. Among other results, the beneficial fuel efficiency merits of hybrid vehicles were demonstrated with respect to gasoline cars, in particular at low speeds and in urban (city) environments. After controlling for other factors, sedan HEVs were 28% more efficient than sedan gasoline vehicles. However, the low temperatures (below 0 °C) observed regularly during winter season in the study cities were identified as a detrimental factor to fuel economy. In winter, the fuel efficiency of HEVs decrease about 20% with respect to summer. Other factors such as eco-driving training, city size, cold start and vehicle type were also found to be statistically significant.     

The inherent precision of regression estimated route probabilities

From basic assumptions about independent and consistent driver behaviour, and with data from traffic counts, we derive statistical properties of regression or correlation estimates of route selection probabilities, turning probabilities and travelling times. Our modelling is conditional in a way that avoids most traffic generation problems and permits an asymptotic analysis of the precision under mild assumptions allowing non-stationarity. This allows us to put together non-stationary data from the corresponding time intervals during several days when we aim at high precision estimates.     

混凝土桥梁使用寿命评估和最佳养护方法

介绍了一种方法，可以对结构使用寿命进行概率评估及选择最佳养护计划。这种方法基于一种新的方法，以评估侵蚀环境扩散侵蚀下混凝土结构的时变性能。概率分析的结果可以用来帮助选择不同养护类型下的修复方案，以使结构使用寿命达到设计值。在一个空心墩上的应用显示了本方法的效果。     

综合评价在公路项目前期工作中的应用

目前在公路建设项目前期工作中，经济评价结论决定了项目的可行性。随着高速公路建设步伐的加快，由于项目造价高而交通量预测值低且车辆收费标准增长缓慢，经济评价特别是财务评价效果越来越差，部分项目经济评价无法通过。综合评价是在经济评价的基础上。综合项目在经济、政治、国防、社会效益等多领域因素的分析，得到项目的综合评价结论，为项目的可行性提供依据。     

铁道列车制动限速

阐明并确立铁道列车紧急制动限速与常用制动限速的涵义、影响因素、核定依据以及不同的确定方式。通过铁道列车紧急制动距离限值与紧急制动限速的数学关系,可以求解不同条件下的列车紧急制动限速值。建立铁道列车紧急制动限速的简化经验公式,并给出各种既有列车特定的相关经验系数。基于常用制动时列车总减速力等于零的极限约束条件,计算并绘制普通货物列车的常用制动限速图。利用图解方法得到我国普通货物列车总制动限速图以及其中的紧急制动限速与常用制动限速的分界转换线。利用相关的简化经验公式及制动限速图可以方便、准确地求出列车具体制动限速值或制订列车制动限速表。     

锚泊中船舶卧底链长的一种估算方法

为了从定量上掌握锚泊船卧底锚链的长度 ,保证锚泊安全 ,本文根据锚链悬链线特殊性质 ,提出了在出链长度一定的情况下估算卧底链长的一种简易方法 ,即根据锚链在锚链筒外孔处与铅垂线的夹角来估算卧底链长的方法 ,并对估算误差作了简要分析。分析表明 ,当锚链张角 <5 0°时 ,误差较小 ;当锚链张角 >6 0°时 ,误差偏大 ,但仍可满足航海实践需要