A pre-appraisal model for rail transit in developing cities

A major research study funded by the UK Overseas Development Administration (ODA) and designed to establish the necessary considerations for viability of mass rapid transit railways in developing cities was recently completed. The analytical core of the study was a pre-appraisal model, which combines an innovative strategic land use/transport model utilizing relationships from developing cities and an economic evaluation model. This model — MRTAP — has now been developed into a user-friendly package which the ODA intend should be made widely available in the developing world. The paper describes the basis of this model.     

An Analysis of Weekend Work Activity Patterns in the San Francisco Bay Area

The purpose of this study is to examine the spatial and temporal characteristics of weekend work episodes. Specifically, we examine whether individuals work over the weekend and, if they work, whether they work at home or outside the home. We also model the time of day of weekend work. The empirical analysis in the paper is based on the 2000 San Francisco Bay Area Travel Survey. The results indicate the important effects of day of week/seasonal effects, individual demographics, work-related variables, household characteristics, and location variables on weekend work participation characteristics. The models estimated in the paper may be embedded within a larger weekend activity-travel pattern forecasting model system.     

Spatial variation of roadside C2–C6 hydrocarbon concentrations during low wind speeds: A note

This Note describes an investigation of spatial variations in the ambient concentrations of hydrocarbons in the vicinity of a suburban motorway during five consecutive weekday morning peak periods of unusually warm and calm conditions. Background-corrected downwind concentrations representing the influence of the motorway source were found to be strongly dependant on wind speed and direction. The ambient ethene-to-acetylene concentration ratio was greatest close to the roadside and the effect of wind speed on the ratio had different average profiles for main wind directions due to different rates of dispersal. Higher values were obtained using background-corrected concentrations.     

Partial-profilogram reconstruction method to measure the geometric parameters of wheels in dynamic condition

The present work poses a method for the measurement of geometric parameters of rail wheels in a dynamic condition, by reconstructing the profilogram from a portion of the wheel surface wear with artificial vision. The suggested procedure can work with a two-dimensional laser displacement transducer or by processing a sole image from a single camera with a structured light source. These two procedures require fewer devices and simpler implementation processes and allow the use of mathematical algorithms that demand less information processing, thus generating more accurate results. Railway operators may implement this method to perform predictive maintenance to their rolling stock at a fraction of the regular cost; thus achieving better precision, availability, maintenance performance and improving safety. Results were compared to those given by commercial equipment, showing similar precision but a better cost–benefit relation.     

Using demand elasticities from disaggregate mode choice models

Three of the most highly regarded disaggregate mode split models incorporate very different estimates of the responsiveness, or elasticity, of mode choice to changes in auto travel times and costs. These differences appear to be due in part to the varying specifications used by the model, and particularly whether certain variables (such as a dummy variable for CBD destinations or automobile ownership) are included in addition to the more traditional variables (such as travel time, cost, and household income). More research is needed on the implications of the theory of traveler choices for model specification and the effect of alternative, but theoretically justifiable, specifications on elasticity estimates. Until this research reduces our uncertainty about the elasticity of demand, analysts evaluating transportation policies should assess the sensitivity of their results to the range of plausible elasticities or models.     

New appraisal values of travel time saving and reliability in Great Britain

Transportation - This paper provides an overview of the study ‘Provision of market research for value of time savings and reliability’ undertaken by the Arup/ITS Leeds/Accent consortium...     

Estimation of the determinants of bicycle mode share for the journey to work using census data

A model is presented that relates the proportion of bicycle journeys to work for English and Welsh electoral wards to relevant socio-economic, transport and physical variables. A number of previous studies have exploited existing disaggregate data sets. This study uses UK 2001 census data, is based on a logistic regression model and provides complementary evidence based on aggregate data for the determinants of cycle choice. It suggests a saturation level for bicycle use of 43%. Smaller proportions cycle in wards with more females and higher car ownership. The physical condition of the highway, rainfall and temperature each have an effect on the proportion that cycles to work, but the most significant physical variable is hilliness. The proportion of bicycle route that is off-road is shown to be significant, although it displays a low elasticity (+0.049) and this contrasts with more significant changes usually forecast by models constructed from stated preference based data. Forecasting shows the trend in car ownership has a significant effect on cycle use and offsets the positive effect of the provision of off-road routes for cycle traffic but only in districts that are moderately hilly or hilly. The provision of infrastructure alone appears insufficient to engender higher levels of cycling.

Review of fishing safety policies in Canada with respect to extreme environmental conditions and climate change effects

Fishing is one of the most dangerous occupations in the world. Numerous research studies have been carried out to improve fishing safety from many different perspectives. Several of these studies focused on the relationship between environmental factors, climate change effects, and fishing safety. This paper aims to suggest a knowledge mobilization structure that translates findings of this type of research into input of evidence-based decision making and consequently improve and update fishing policies with respect to fishing safety and environmental conditions. Significant safety factors extracted from related literature are stability of vessels, fisheries management, safety equipment, communication, insurance, training, safety information and culture, weather forecasts, fatigue, and search and rescue planning. The paper then reviews policies related to these factors to examine if they address extreme environmental conditions and climate change effects. The paper presents recommendations to improve general fishing safety with respect to short- and long-term environmental considerations.