Modelling passenger demand for parkway rail stations

Interest in Parkway stations emerged in the 1980s. These act as convenient out-of-town stations for inter-urban rail journeys. There were 13 so-called Parkway stations in Great Britain in 1999 and two have subsequently been opened. This paper reports the development and application of a new Parkway forecasting model which was conducted for the Association of Train Operating Companies (ATOC), undertaken as part of an extensive update to the Passenger Demand Forecasting Handbook, which recommends demand forecasting frameworks and associated parameters that are widely used in the railway industry in Great Britain. The objective was to develop a model that had more desirable properties and was more straightforward to apply than the previously recommended procedure. The focus is entirely upon inter-urban journeys of over 80 km.The model forecasts the demand for Parkway stations based solely on rail ticket sales data and its properties are illustrated with two case study applications. The nature of Parkway stations forces consideration of competition, and it is demonstrated that the inclusion of a station choice component leads to a somewhat improved explanatory power and a more plausible generalised cost elasticity.In addition to the methodological developments, the model has provided generally reasonable elasticities and forecasts and shown that Parkway users have different preferences to rail travellers in general. In a test based around a newly opened Parkway station, its forecasts are more accurate than the procedure it replaces.     

Wave data assimilation with the Kalman filter

A new data assimilation method for ocean waves is presented, based on an efficient low-rank approximation to the Kalman filter. Both the extended Kalman filter and a truncated second-order filter are implemented. In order to explicitly estimate past wind corrections based on current wave measurements, the filter is extended to a fixed-lag Kalman smoother for the wind fields. The filter is tested in a number of synthetic experiments with simple geometries. Propagation experiments with errors in the boundary condition showed that the KF was able to accurately propagate forecast errors, resulting in spatially varying error correlations, which would be impossible to model with time-independent assimilation methods like OI. An explicit comparison with an OI assimilation scheme showed that the KF also is superior in estimating the sea state at some distance from the observations. In experiments with errors in the driving wind, the modeled error estimates were also in agreement with the actual forecast errors. The bias in the state estimate, which is introduced through the nonlinear dependence of the waves on the driving wind field, was largely removed by the second-order filter, even without actually assimilating data. Assimilation of wave observations resulted in an improved wave analysis and in correction of past wind fields. The accuracy of this wind correction depends strongly on the actual place and time of wave generation, which is correctly modeled by the error estimate supplied by the Kalman filter. In summary, the KF approach is shown to be a reliable assimilation scheme in these simple experiments, and has the advantage over other assimilation methods that it supplies explicit dynamical error estimates.     

Coupling Model of Vertical and Lateral Vehicle/Track Interactions

A new dynamic model of vehicle/track interaction is presented. The model considers the vehicle and the track as a whole system and couples the vertical interaction with the lateral interaction. The vehicle subsystem is modeled as a multi-body system with 37 degrees of freedom, which runs on the track with a constant velocity. The track substructure is modeled as a discretely supported system of elastic beams representing the rails, sleepers and ballasts. The normal contact forces between wheels and rails are described by Hertzian nonlinear elastic contact theory and the tangential wheel/ rail forces are decided by the creep theory. Numerical results are compared with those of conventional dynamic models of railway vehicles. Applications of the coupling model to the investigation of safety limits against derailment due to the track twist and the combined alignment and cross-level irregularities are reported at the end of the paper.     

Fatigue life reliability prediction of a stub axle using Monte Carlo simulation

A stub axle is a part of a vehicle constant-velocity system that transfers engine power from the transaxle to the wheels. The stub axle is subjected to fatigue failures due to cyclic loads arising from various driving conditions. The aim of this paper was to introduce a probabilistic framework for fatigue life reliability analysis that addresses uncertainties that appear in the mechanical properties. Service loads in terms of response-time history signal of a Belgian pave were replicated on a multi-axial spindle-coupled road simulator. The stress-life method was used to estimate the fatigue life of the component. A fatigue life probabilistic model of a stub axle was developed using Monte Carlo simulation where the stress range intercept and slope of the fatigue life curve were selected as random variables. Applying the goodness-of-fit analysis, lognormal was found to be the most suitable distribution for the fatigue life estimates. The fatigue life of the stub axle was found to have the highest reliability between 8000–9000 cycles. Because of uncertainties associated with the size effect and machining and manufacturing conditions, the method described in this paper can be effectively applied to determine the probability of failure for mass-produced parts.     

Population ageing,gender and the transportation system

Across the globe population structures are ageing and how older men and women interact with the transport system is increasingly important in maintaining a good quality of life and inclusion in society. The paper reviews three issues: the nature of older people’s interaction with the transport system by gender; older people’s attitude to travel; and the involvement of older people as road traffic casualties. Patterns of travel in the UK show that older people are heavily dependent on car use, but in the form of more frequent but shorter journeys than younger people. This is especially so for women over 70 years old who, as passengers, are very reliant on males to drive them. Attitudes suggest that there are few obstacles to public transport use, and most agree that bus travel is good, but convenience means many prefer cars. Involvement of older men and women in serious road traffic accidents show that they have lower killed and seriously injured (KSI) rates than 17–24 year old drivers. However, those aged over 70 years exhibit a trend of increasing KSI rates. Analysis of casualty rates of drivers by type of junction, manoeuvre and environmental conditions found that some gender-age groups are overrepresented in certain accident types, including higher serious accidents rates for men, and over representation of older women when driving in poor conditions and turning right and negotiating roundabouts, crossroads and T, Y and staggered junctions. Improvement in engineering design and driver training are suggested together with the need for a greater understanding of the transportation system needs of old and very old people.     

A redefinition of water masses in the Vietnamese upwelling area

A redefinition of characteristic water masses in the Vietnamese upwelling area is presented based on five interdisciplinary cruises during different seasons and 331 CTD casts. In contrast to the previous definition of Rojana-anawat et al. (2001), we clearly can define water masses which serve as end members of mixing. This new definition is useful for an improved understanding of geographical positions of different water masses with respect to climate variability, the phytoplankton distribution and complex nutrient cycle in this area.     

Spatial heterogeneity and temporal dynamics of particles, bacteria, and pEPS in Arctic winter sea ice

Abundances of particles, total bacteria, and particulate extracellular polymeric substances (pEPS) in Arctic sea ice were tracked through a winter season to examine the impact of combined extremes of low temperature and high salinity on the prokaryotic microbial community. Three horizons, centered at depths of 25, 45, and 65 cm from the ice surface, with mean seasonal temperatures of − 20, − 17, and − 13 °C, respectively, were sampled 16 times over the course of 12 weeks. Microscopic counts of bacteria (stained with DAPI) and particles (stained with acridine orange) reflected the dynamic conditions of the growing ice sheet, with greater abundances and variability in the upper ice horizons compared to the lower. The trend of higher particle and bacterial abundances in the upper ice was corroborated by several full-depth profiles taken during the expedition, which also displayed significantly decreasing cell abundance with depth. Bacterial abundance declined slowly and significantly with time in the upper and middle ice horizons, but not in the lowest, suggesting that much of the prokaryotic microbial community is resilient to extreme environmental conditions. We found that pEPS concentrations increased significantly with time and with decreasing temperatures in all depth horizons, which may lend support to the argument that sea ice bacteria produce EPS in situ as a cryoprotectant.