The social context of informal commuting: Slugs, strangers and structuration

Despite considerable interest in the role of social interactions and social context on transportation, there have been very few attempts to explore specific cases of social interaction influencing transportation systems. This paper explores the social practice of slugging, an informal system of carpooling in the Washington, DC area. Slugging emerged in response to the establishment of Virginia’s High Occupancy Vehicle (HOV) lanes in the early 1970s, as single drivers picked up riders alongside the road (slugs) in order to meet the requirements for driving in the less congested HOV lanes. Drawing on the work of sociologist Anthony Giddens, as well as the sociological insights of Georg Simmel and Stanley Milgram, we suggest that the practice of slugging highlights the processes of institutionalization and structuration. This paper details how the region’s mass transportation policies and urban culture have combined to result in an institutionalized practice with particular norms and logics of behavior. We conclude that looking at specific cases where social context has affected transportation, like slugging, could provide useful insights on the impact of social context on transportation policies and systems.     

Strategic considerations behind the network–regional airline tie ups – A theoretical and empirical study

The paper examines the strategic vertical relationship between network and regional airlines. We develop a model to illustrate how network airlines can use the contractual relationship with regional airlines as an efficient tool to simultaneously drive out inefficient network airlines and also accommodate other cost efficient network airlines in any specific market. The model is tested on U.S. data using simultaneous and sequential choice models. We find that market size, cost differences between network airlines, as well as cost differences between network and regional airlines, are the chief determinants of the network airlines’ decisions on whether or not to serve a market with their own fleet, as well as how many regional airlines to contract with.     

Multi-step prediction of experienced travel times using agent-based modeling

This paper develops an agent-based modeling approach to predict multi-step ahead experienced travel times using real-time and historical spatiotemporal traffic data. At the microscopic level, each agent represents an expert in a decision-making system. Each expert predicts the travel time for each time interval according to experiences from a historical dataset. A set of agent interactions is developed to preserve agents that correspond to traffic patterns similar to the real-time measurements and replace invalid agents or agents associated with negligible weights with new agents. Consequently, the aggregation of each agent’s recommendation (predicted travel time with associated weight) provides a macroscopic level of output, namely the predicted travel time distribution. Probe vehicle data from a 95-mile freeway stretch along I-64 and I-264 are used to test different predictors. The results show that the agent-based modeling approach produces the least prediction error compared to other state-of-the-practice and state-of-the-art methods (instantaneous travel time, historical average and k-nearest neighbor), and maintains less than a 9% prediction error for trip departures up to 60 min into the future for a two-hour trip. Moreover, the confidence boundaries of the predicted travel times demonstrate that the proposed approach also provides high accuracy in predicting travel time confidence intervals. Finally, the proposed approach does not require offline training thus making it easily transferable to other locations and the fast algorithm computation allows the proposed approach to be implemented in real-time applications in Traffic Management Centers.     

Understanding the impacts of mobile phone distraction on driving performance: A systematic review

The use of mobile phones while driving—one of the most common driver distractions—has been a significant research interest during the most recent decade. While there has been a considerable amount research and excellent reviews on how mobile phone distractions influence various aspects of driving performance, the mechanisms by which the interactions with mobile phone affect driver performance is relatively unexamined. As such, the aim of this study is to examine the mechanisms involved with mobile phone distractions such as conversing, texting, and reading and the driving task, and subsequent outcomes. A novel human-machine framework is proposed to isolate the components and various interactions associated with mobile phone distracted driving. The proposed framework specifies the impacts of mobile phone distraction as an inter-related system of outcomes such as speed selection, lane deviations and crashes; human-car controls such as steering control and brake pedal use and human-environment interactions such as visual scanning and navigation. Eleven literature-review/meta-analyses papers and 62 recent research articles from 2005 to 2015 are critically reviewed and synthesised following a systematic classification scheme derived from the human-machine system framework. The analysis shows that while many studies have attempted to measure system outcomes or driving performance, research on how drivers interactively manage in-vehicle secondary tasks and adapt their driving behaviour while distracted is scant. A systematic approach may bolster efforts to examine comprehensively the performance of distracted drivers and their impact over the transportation system by considering all system components and interactions of drivers with mobile phones and vehicles. The proposed human-machine framework not only contributes to the literature on mobile phone distraction and safety, but also assists in identifying the research needs and promising strategies for mitigating mobile phone-related safety issues. Technology based countermeasures that can provide real-time feedback or alerts to drivers based on eye/head movements in conjunction with vehicle dynamics should be an important research direction.     

A note on the use of correlation coefficients for assessing goodness-of-fit in spatial interaction models

The use of correlation coefficients to evaluate the accuracy of spatial interaction models is inappropriate unless such models have been fitted using least squares techniques. In other cases the correlation involves an implicit intercept value and a regression coefficient that may significantly modify the interaction model's estimates. Researchers have not acknowledged the role of these two parameters when the correlation is used. A generalized root mean square error is proposed as an alternative indicator of accuracy that may be used with any model.     

Interaction study of train-bridge-track systems using Maxwell model

The investigation of problems related to the interaction of train, bridge and track systems has been accelerated by the emergence of high-speed trains. Such studies are required, not only for the endurance issues regarding bridge and tracks, but to assure trains' functionality and performance. The suspension mechanism of train systems is of prime importance in defining the functionality of high-speed trains, and accurate mathematical models of the mechanism are imperative. This paper introduces a numerical technique for an interaction study of train-bridge-track systems based on Maxwell (three-element type) modeling of the suspension mechanisms of vehicles. Track irregularity in sinusoidal form is also integrated into the mathematical model. Although the proposed technique is simple in formulation, it offers phenomenal accuracy in representing the interaction of train, track and bridge systems. In a numerical example, the dynamic behavior of a train-bridge system has been studied. Results of this analysis provide a valuable insight into the contributing roles of different parameters in this subject.     

基于NURBS的船体与桥墩间水动干扰力及力矩的非定常计算

本文在一些假设下完成了船体与桥墩之间水动干扰力及力矩的数值计算工作，所采用的方法是基于非均匀有理B样条(NURBS)的三维Rankine源边界元法，即将船体、桥墩的几何形状以及流场中待求的物理量分布完全表达成NURBS的形式。给出了船体通过圆柱形桥墩时的水动干扰力及力矩的数值计算结果，并进行了一些分析。     

HBV Pre S1蛋白质在酵母细胞中具有转录激活功能

为探讨应用双杂交体系统克隆与HBVPreS1蛋白质结合的肝细胞受体的可行性，我们构建了HBVPreS1蛋白质与酵母GAL4DNAbindingdomain融合蛋白质酵母表达质粒。通过应用该质粒转化酵母菌株SFY526，检测报道基因产物五半乳糖苷酶活性，结果表明HBVPreS1蛋白质在酵母细胞中具有转录激活功能。能否去除PreS1蛋白质转录激活功能区域但却保留其与肝细胞受体的结合区域用于酵母双杂交体系统筛选肝细胞cDNA文库、克隆与PreS1蛋白质结合的肝细胞受体尚需进一步实验探讨。     

An efficient approach to the analysis of rail surface irregularities accounting for dynamic train–track interaction and inelastic deformations

A two-dimensional computational model for assessment of rolling contact fatigue induced by discrete rail surface irregularities, especially in the context of so-called squats, is presented. Dynamic excitation in a wide frequency range is considered in computationally efficient time-domain simulations of high-frequency dynamic vehicle–track interaction accounting for transient non-Hertzian wheel–rail contact. Results from dynamic simulations are mapped onto a finite element model to resolve the cyclic, elastoplastic stress response in the rail. Ratcheting under multiple wheel passages is quantified. In addition, low cycle fatigue impact is quantified using the Jiang–Sehitoglu fatigue parameter. The functionality of the model is demonstrated by numerical examples.