Recent Development in Active Steering of Railway Vehicles

Summary This paper presents the recent development on active steering for railway vehicles, and carries out a technical appraisal of different actuation schemes and control approaches. It brings together the latest research activities and findings for the full active steering techniques for rail vehicles with the solid-axle wheelsets, independently-rotating wheelsets and wheel-pairs without axles, but relevant work on passive and semi-active solutions is also briefly described. Potential benefits of the use of a combination of modern control technology and mechatronic approach are evaluated, and in particular solutions for the difficult design trade-off between the stability and the curving performance are presented. Various actuation configurations are discussed, and advantages and drawbacks of those schemes are investigated. The outline design using a number of control methods is analysed, and measurement requirement and state estimation techniques essential for implementation of the active steering schemes are also explored. In addition the issue of safety criticality is highlighted and a possible approach for developing fault-tolerant systems is proposed. Overall the paper provides an authoritative assessment of the major advances in actively-steered wheels and addresses outstanding critical issues.     

Maritime education factors and presenteeism: a comparative quantitative study

Presenteeism research has only recently extended from a construct capturing lost productivity due to attending work despite health issues to a construct representing students’ perceived academic performance. Aligning with presenteeism’s prevalent research paradigm, the pioneering studies used health-related issues to measure presenteeism. In contrast, this study used the Presenteeism and Perceived Academic Performance (PPAP) Scale, which the researcher developed for this study. The PPAP Scale comprises aspects of student behavior that support academic performance. This study filled gaps in the literature by investigating presenteeism as a concept associated with students’ perceived academic performance, measured with the PPAP Scale, and factors specific to maritime education. The factors investigated were self-identified by the study respondents, in sufficient numbers to support statistical analysis, as favorably (i.e., cruise and license/maritime instruction) or negatively (i.e., mandatory regimental activity, taps, morning or afternoon formations, and watch) impacting their academic performance. This study found no statistical evidence to suggest the level of presenteeism, measured with the PPAP Scale, among the study’s sample of license students is associated with factors perceived to favorably or negatively impact academic performance. Additional insight can be gained from license student participants’ responses to the study’s open-ended questions (e.g., a perceived imbalance between time available to allocate to their academics and time needed to fulfill regimental responsibilities).     

A latent variable representation of count data models to accommodate spatial and temporal dependence: Application to predicting crash frequency at intersections

This paper proposes a reformulation of count models as a special case of generalized ordered-response models in which a single latent continuous variable is partitioned into mutually exclusive intervals. Using this equivalent latent variable-based generalized ordered response framework for count data models, we are then able to gainfully and efficiently introduce temporal and spatial dependencies through the latent continuous variables. Our formulation also allows handling excess zeros in correlated count data, a phenomenon that is commonly found in practice. A composite marginal likelihood inference approach is used to estimate model parameters. The modeling framework is applied to predict crash frequency at urban intersections in Arlington, Texas. The sample is drawn from the Texas Department of Transportation (TxDOT) crash incident files between 2003 and 2009, resulting in 1190 intersection-year observations. The results reveal the presence of intersection-specific time-invariant unobserved components influencing crash propensity and a spatial lag structure to characterize spatial dependence. Roadway configuration, approach roadway functional types, traffic control type, total daily entering traffic volumes and the split of volumes between approaches are all important variables in determining crash frequency at intersections.     

An analysis of bicycle route choice preferences in Texas,US

In the US, the rise in motorized vehicle travel has contributed to serious societal, environmental, economic, and public health problems. These problems have increased the interest in encouraging non-motorized modes of travel (walking and bicycling). The current study contributes toward this objective by identifying and evaluating the importance of attributes influencing bicyclists’ route choice preferences. Specifically, the paper examines a comprehensive set of attributes that influence bicycle route choice, including: (1) bicyclists’ characteristics, (2) on-street parking, (3) bicycle facility type and amenities, (4) roadway physical characteristics, (5) roadway functional characteristics, and (6) roadway operational characteristics. The data used in the analysis is drawn from a web-based stated preference survey of Texas bicyclists. The results of the study emphasize the importance of a comprehensive evaluation of both route-related attributes and bicyclists’ demographics in bicycle route choice decisions. The empirical results indicate that travel time (for commuters) and motorized traffic volume are the most important attributes in bicycle route choice. Other route attributes with a high impact include number of stop signs, red light, and cross-streets, speed limits, on-street parking characteristics, and whether there exists a continuous bicycle facility on the route.

Analysis of within-household effects and between-household differences in maintenance activity allocation

This paper investigates the allocation of household individuals to out-of-home maintenance activities using the rich activity-travel diary data from the San Francisco Bay Area. Two inter-related decisions are considered in this context: (i) whether the given activity episode is performed individually (solo) or jointly, and (ii) the person who participates in the activity, if it is a solo activity. To account for the conditional nature of the solo activity person selection, a nested mixed logit modeling framework is proposed and implemented to jointly analyze person allocation for all maintenance activities performed by a household on a given day. The model is used to investigate within-household effects and between-household differences. The proposed model relaxes some important restrictions in person allocation models by accounting for various sources of correlations and relaxing the assumption of constant variance across households. The proposed model is used to analyze the differences in person allocation between different types of households. The results indicate that life-cycle and household role, income, gender, employment status, and several types of constraints (activities including cost, time-availability, vehicle-availability, coordination constraints, and child-care obligations) affect person allocation decisions in the context of maintenance activities. The empirical results indicate the presence of various sources of correlations across persons, over activities, and within-household that are significant. In addition, the data also provides evidence that the unobserved variances in person selection utilities are not constant across households. A better understanding of these within-household interactions and between-household differences may be used in activity-based simulation models and to develop more effective and focused demand management measures.     

Transport Network Design Problem under Uncertainty: A Review and New Developments

This paper aims to provide a state-of-the-art review of the transport network design problem (NDP) under uncertainty and to present some new developments on a bi-objective-reliable NDP (BORNDP) model that explicitly optimizes the capacity reliability and travel time reliability under demand uncertainty. Both are useful performance measures that can describe the supply-side reliability and demand-side reliability of a road network. A simulation-based multi-objective genetic algorithm solution procedure, which consists of a traffic assignment algorithm, a genetic algorithm, a Pareto filter, and a Monte-Carlo simulation, is developed to solve the proposed BORNDP model. A numerical example based on the capacity enhancement problem is presented to demonstrate the tradeoff between capacity reliability and travel time reliability in the NDP.     

The role of VMT reduction in meeting climate change policy goals

This article evaluates the case for vehicle miles traveled (VMT) reduction as a core policy goal for reducing greenhouse gases (GHGs), concluding the economic impacts and social consequences would be too severe given the modest potential environmental benefits. Attempts to reduce VMT typically rely on very blunt policy instruments, such as increasing urban densities, and run the risk of reducing mobility, reducing access to jobs, and narrowing the range of housing choice. VMT reduction, in fact, is an inherently blunt policy instrument because it relies almost exclusively on changing human behavior and settlement patterns to increase transit use and reduce automobile travel rather than directly target GHGs. It also uses long-term strategies with highly uncertain effects on GHGs based on current research. Not surprisingly, VMT reduction strategies often rank among the most costly and least efficient options. In contrast, less intrusive policy approaches such as improved fuel efficiency and traffic signal optimization are more likely to directly reduce GHGs than behavioral approaches such as increasing urban densities to promote higher public transit usage. As a general principle, policymakers should begin addressing policy concerns using the least intrusive and costly approaches first. Climate change policy should focus on directly targeting greenhouse gas emissions (e.g., through a carbon tax) rather than using the blunt instrument of VMT reduction to preserve the economic and social benefits of mobility in modern, service-based economies. Targeted responses are also more cost effective, implying that the social welfare costs of climate change policy will be smaller than using broad-brushed approaches that directly attempt to influence living patterns and travel behavior.     

Integrating congestion pricing,transit subsidies and mode choice

We model and analyze optimal (welfare maximizing) prices and design of transport services in a bimodal context. Car congestion and transit design are simultaneously introduced and consumers choose based on the full price they perceive. The optimization variables are the congestion toll, the transit fare (and hence the level of subsidies) and transit frequency. We obtain six main results: (i) the optimal car-transit split is generally different from the total cost minimizing one; (ii) optimal congestion and transit price are interdependent and have an optimal frequency attached; (iii) the optimal money price difference together with the optimal frequency yield the optimal modal split; (iv) if this modal split is used in traditional stand-alone formulations – where each mode is priced independently–resulting congestion tolls and transit subsidies and fares are consistent with the optimal money price difference; (v) self-financing of the transport sector is feasible; and (vi) investment in car infrastructure induces an increase in generalized cost for all public transport users.     

Investigation into factors affecting the route choice in “Rijnstreek-West” with the aid of a disaggregate logit model

Transportation - Based on an analysis of observed automobile routes, an investigation is made into the factors affecting choice of routes. As in previous studies, the attempt to determine the...     

Grade measurement with an instrumented car

Grade information may be needed for route surveys and is important when fuel consumption is studied. An instrumented car was used to measure acceleration along the road surface by double differentiating accumulated pulses generated off the drive train. A second acceleration measure included the component due to gravity relative to the car body. The difference between these acceleration measures contains grade information but it also influenced by suspension dynamics and pitch of the car body. The effect of suspension dynamics was removed by filtering which limited the minimum wavelength to 160 m. The effect of pitch was removed by a correction based on acceleration, jerk and the square of vehicle speed. The correction was computed from data collected on a level airfield runaway. The method is verified for a high capacity arterial road. Grade is measured to within 0.001 rad (95% confidence limits). Elevation derived from the grade data was consistent with road construction drawings to the same limits.