Vibration control in train–bridge–track systems

To study the problems associated with vibration control of train–bridge–track systems a mathematical model with the capability of representing supplementary vibrational control devices is proposed. The train system is assumed as rigid bodies supported on double-deck suspension mechanism with semi-active features. The bridge system is modeled using the modal approach. Vibration control for bridge responses is provided by tuned mass dampers. A non-classical incremental Eigen analysis is proposed to trace the system characteristics across the time. In an example, the capability of the proposed model in investigating the vibration control prospects of a bridge–train system is shown. The results indicate the effectiveness of active suspension mechanism in reducing train's body movements, particularly the pitching angle and the vertical accelerations. Accordingly, the results also verify the potential of TMD devices in reducing the bridge responses at resonance motions.     

Rolling horizon control framework for driver assistance systems. Part II: Cooperative sensing and cooperative control

This contribution furthers the control framework for driver assistance systems in Part I to cooperative systems, where equipped vehicles can exchange relevant information via vehicle-to-vehicle communication to improve the awareness of the ambient situation (cooperative sensing) and to manoeuvre together under a common goal (cooperative control). To operationalize the cooperative sensing strategy, the framework is applied to the development of a multi-anticipative controller, where an equipped vehicle uses information from its direct predecessor to predict the behaviour of its pre-predecessor. To operationalize the cooperative control strategy, we design cooperative controllers for sequential equipped vehicles in a platoon, where they collaborate to optimise a joint objective. The cooperative control strategy is not restricted to cooperation between equipped vehicles. When followed by a human-driven vehicle, equipped vehicles can still exhibit cooperative behaviour by predicting the behaviour of the human-driven follower, even if the prediction is not perfect.The performance of the proposed controllers are assessed by simulating a platoon of 11 vehicles with reference to the non-cooperative controller proposed in Part I. Evaluations show that the multi-anticipative controller generates smoother behaviour in accelerating phase. By a careful choice of the running cost specification, cooperative controllers lead to smoother decelerating behaviour and more responsive and agile accelerating behaviour compared to the non-cooperative controller. The dynamic characteristics of the proposed controllers provide new insights into the potential impact of cooperative systems on traffic flow operations, particularly at the congestion head and tail.     

Dynamic demand estimation and microscopic traffic simulation of a university campus transportation network

Abstract

This article documents the authors' experience with the modeling, simulation, and analysis of a university transportation system, using the TRansportation ANalysis and SIMulation System (TRANSIMS). The processes of data preparation and network coding are described, followed by the algorithm developed to estimate the dynamic 24-hour demand, which includes a procedure for estimating the ‘desirability’ of the different parking lots from readily available data. The dynamic demand estimation algorithm is validated by comparing estimated and observed parking lot occupancies, where it is shown that the algorithm is capable of replicating observed results. Finally, an example is included to demonstrate how the developed model can be used in campus transportation planning. Besides serving as a first case study for using TRANSIMS to model a university campus, the study's contributions include the development of a procedure for parking lot desirability ranking and a practical procedure for estimating dynamic demand on university campuses.     

俄罗斯船用及工业燃气轮机的发展和应用现状

综述并分析俄罗斯船用及工业燃气轮机设计、研制、生产和应用的现状及发展状况。指出,俄罗斯小功率发电用燃气轮机的发展现状良好,拥有一些性能优良的机组,但是中等功率和大功率发电用机组却是弱项,距离世界先进水平还有很大差距。机械驱动用燃气轮机始终是俄罗斯工业燃气轮机中的强项,设计、研制和应用均处于世界领先水平。曾经是其强项的船用燃气轮机,由于苏联的解体,却成了俄罗斯燃气轮机工业中的缺项。     

Weight threshold estimation of falling UAVs (Unmanned Aerial Vehicles) based on impact energy

Different weight thresholds for drone operations have been specified by regulatory agencies in different countries, without detailed backgrounds of guidelines. Therefore, this paper aims to study weight thresholds by focusing different levels of injuries caused by the impact of the drones on human head of different weights dropped at various heights. The work covers drone free drop modelling, FEM (finite element method) based impact modeling, and comparable drop impact experiments. The analyses and experiments were conducted accordingly to two individual commercially-available groups: small and large drones in weights. Two well-established indicators defining head injuries due to impact, which are known as Head Injury Criterion (HIC) and Abbreviated Injury Scale (AIS), are used in the present weight threshold study. The proposed AIS level for the weight threshold estimation has been set at AIS level 3, which indicates major skull fracture, in the further analysis through the probability of fatality. The main focus of the present work is to perform a parametric study and to present a reliable model to estimate the weight thresholds of the drone operations based on HIC and AIS. In conclusion, the results obtained and presented in this paper have demonstrated and provided a comprehensive analysis of possible direct injuries of a falling drone impacting a human head, with relevant data of impact or injury levels associated with HIC and AIS obtained for a drone with different weights falling from various heights.     

Daily activity pattern recognition by using support vector machines with multiple classes

The focus of this paper is to learn the daily activity engagement patterns of travelers using Support Vector Machines (SVMs), a modeling approach that is widely used in Artificial intelligence and Machine Learning. It is postulated that an individual’s choice of activities depends not only on socio-demographic characteristics but also on previous activities of individual on the same day. In the paper, Markov Chain models are used to study the sequential choice of activities. The dependencies among activity type, activity sequence and socio-demographic data are captured by employing hidden Markov models. In order to learn model parameters, we use sequential multinomial logit models (MNL) and multiclass Support Vector Machines (K-SVM) with two different dependency structures. In the first dependency structure, it is assumed that type of activity at time ‘t’ depends on the last previous activity and socio-demographic data, whereas in the second structure we assume that activity selection at time ‘t’ depends on all of the individual’s previous activity types on the same day and socio-demographic characteristics. The models are applied to data drawn from a set of California households and a comparison of the accuracy of estimation of activity types and their sequence in the agenda, indicates the superiority of K-SVM models over MNL. Additionally, we show that accuracy in estimating activity patterns increases using different sets of explanatory variables or tuning parameters of the kernel function in K-SVM.     

Scheduling of Intelligent and Autonomous Vehicles under pairing/unpairing collaboration strategy in container terminals

A new class of Intelligent and Autonomous Vehicles (IAVs) has been designed in the framework of Intelligent Transportation for Dynamic Environment (InTraDE) project funded by European Union. This type of vehicles is technologically superior to the existing Automated Guided Vehicles (AGVs), in many respects. They offer more flexibility and intelligence in maneuvering within confined spaces where the logistic operations take place. This includes the ability of pairing/unpairing enabling a pair of 1-TEU (20-foot Equivalent Unit) IAVs dynamically to join, transport containers of any size between 1-TEU and 1-FFE (40-foot Equivalent) and disjoin again. Deploying IAVs helps port operators to remain efficient in coping with the ever increasing volume of container traffic at ports and eliminate the need for deploying more 40-ft transporters in the very confined area of ports. In order to accommodate this new feature of IAVs, we review and extend one of the existing mixed integer programming models of AGV scheduling in order to minimize the makespan of operations for transporting a set of containers of different sizes between quay cranes and yard cranes. In particular, we study the case of Dublin Ferryport Terminal. In order to deal with the complexity of the scheduling model, we develop a Lagrangian relaxation-based decomposition approach equipped with a variable fixing procedure and a primal heuristics to obtain high-quality solution of instances of the problem.     

Is the provision of park-and-ride facilities at light rail stations an effective approach to reducing vehicle kilometers traveled in a US context?

Park-and-Ride (PNR) facilities are a commonly used means of making a transit system more widely available. However, given that a PNR passenger must drive for part of the trip, this approach to transit provision has an ambiguous influence on vehicle kilometers traveled (VKT). The impact of PNR on VKT is highly dependent of how PNR users would choose to travel if the PNR facilities were not available. Given that this issue has received little attention in a US context, we use the light rail system in Charlotte, North Carolina as a case study to examine the potential impact of PNR removal on VKT. Using a travel survey of PNR passengers, we estimate the VKT currently generated while driving to and from the rail stations and then estimate how VKT would change under various PNR removal scenarios that assume different behavioral responses. We find that, under the most realistic scenarios, PNR removal would lead the average PNR passenger to increase her driving by 8–15 VKT per round trip.     

Virtual durability test rigs for automotive engineering

In recent years so-called ‘virtual test rigs’ have become more and more important in the development process of cars and trucks. Originally, the idea was to substitute expensive durability tests with computer simulation. Meanwhile, the focus has changed towards a more cooperative usage of numerical and laboratory rig simulation. For many safety critical issues laboratory tests remain indispensable. In early development stages, when no physical prototypes are available yet, numerical simulation is used to analyse and optimise the design. In this paper, we show how to build numerical simulation models of complex servo-hydraulic test systems and their test specimen using multi-body simulation for the mechanics in combination with simulation models for the hydraulics and controls. We illustrate this at two industrial application examples: a spindle-coupled passenger car suspension rig and a tyre-coupled full vehicle rig. We show how the simulation models are used to design and optimise better test rigs and to support the test rig operation by preparing the physical tests with new specimen, i.e. by performing numerical simulations including numerical drive file iteration before the physical tests start.     

基于分形插值方法的城市轨道交通车站客流拟合与仿真

城市轨道交通车站客流量的变化具有复杂的非线性特点,通过对某些车站一天的客流量时间序列的分析,发现其客流量的变化具有自相似性,并且满足某种拟周期性。本文采用迭代函数系统模型描述城市轨道交通车站客流量的变化特征,用计算机自动求解该迭代函数系统的相关参数,在此基础上采用分形插值的方法模拟产生动态的客流。通过与实际客流调查数据的对比分析可以看出,该方法模拟产生的客流不仅与实际客流较好地吻合,而且能更好地描述客流的非线性特征。