Competition and Ownership in Land Passenger Transport: The Sixth International Conference,Cape Town,South Africa,September 1999 - Part 1

The ability of conventional South African travel analysis practices to analyse adequately the travel needs of the poor is examined. The origins and nature of conventional practices are described, and it is observed that typically their scope has been limited to motorized modes, commutes and peaks. The paper reports on the findings of an activity diary survey administered in Cape Town that extended the conventional scope of analysis. An activity‐based survey method was selected because it typically yields higher rates of trip recall than other methods and is therefore relatively well suited to investigating travel behaviour in its fuller complexity. Selected findings of the survey are presented to demonstrate that travel occurring by non‐motorized modes, for non‐work purposes and during off‐peak periods, is considerable. It is argued that the conventional limitation in analytical scope can create serious misconceptions of the true nature of travel behaviour, particularly of low‐income households. By restricting the focus of analysis to motorized, work and peak period trip‐making, there is a risk of a routine bias being introduced in the way the urban passenger transport problem is understood, and in the nature of the interventions that are implemented as a result.     

Preventing death and injury on the world's roads

The problem of deaths and injury as a result of road crashes is now acknowledged to be a global phenomenon with authorities in virtually all countries concerned about the growth in the number of people killed and seriously injured on their roads. The World Health Organization has declared that its annual World Health Day in 2004 will have the theme 'Safe Roads', and several organizations, including the World Bank and the Global Road Safety Partnership, are supporting this initiative to raise the profile of road safety in the public and political minds.     

Making use of respondent reported processing information to understand attribute importance: a latent variable scaling approach

In recent years we have seen an explosion of research seeking to understand the role that rules and heuristics might play in improving the predictive capability of discrete choice models, as well as delivering willingness to pay estimates for specific attributes that may (and often do) differ significantly from estimates based on a model specification that assumes all attributes are relevant. This paper adds to that literature in one important way—it explicitly recognises the endogeneity issues raised by typical attribute non-attendance treatments and conditions attribute parameters on underlying unobserved attribute importance ratings. We develop a hybrid model system involving attribute processing and outcome choice models in which latent variables are introduced as explanatory variables in both parts of the model, explaining the answers to attribute processing questions and explaining heterogeneity in marginal sensitivities in the choice model. The resulting empirical model explains how lower latent attribute importance leads to a higher probability of indicating that an attribute was ignored or that it was ranked as less important, as well as increasing the probability of a reduced value for the associated marginal utility coefficient in the choice model. The model does so by treating the answers to information processing questions as dependent rather than explanatory variables, hence avoiding potential risk of endogeneity bias and measurement error.     

Energy Consumption Analysis of Different Bev Powertrain Topologies by Design Optimization

Flexible layout of electric motors in battery electric vehicles (BEVs) has enabled different powertrain topologies to be used. However, these different powertrain topologies also affect the overall efficiency of energy conversion from the electrochemical form stored in the battery to the mechanical form on the driving wheels for vehicle propulsion. In this study, a methodology combining an energy-based BEV simulation model with the genetic algorithm optimization approach is applied to evaluate the energy efficiency of three different BEV powertrain topologies. The analysis is carried out assuming two different urban driving conditions, as exemplified by the New European Drive Cycle (NEDC) and the Japanese JC08 drive cycle. Each of the three BEV powertrain topologies is then optimized – in terms of its electric motor size and, where applicable, gear reduction ratio – for minimum energy consumption. The results show that among the three powertrain topologies, the wheel-hub drive without gear reducers consumes the least energy. The energy consumption of BEVs under the more aggressive JC08 drive cycle is consistently 8 % above that under NEDC for all three powertrain topologies considered.     

中集集装箱半挂车进入日本市场

人们看惯了日本汽车在中国满地跑,谁见过中国人造的车在日本的国土上跑?可是现在,深圳中集专用车有限公司就让他们制造的集装箱半挂车成功进入了日本市场。 2006年4月5日,日本某专用车制造公司执行董事西川先生专程来到深圳,与中集专用车公司洽谈进一步扩大合作的事宜。     

Approximate procedures for planning public transit systems: A review and some examples

The approximate analytical models of public transit systems are reviewed. First, the derivation and formation of the standard model form is presented. Once the model is explained in general terms some practical planning applications are considered and evaluated. The model type presents an invaluable tool to the transit planner but a few operational problems need to be considered. Further benefits to the planning professionals would be realized if researchers were to devote more effort to sensitivity analysis as a means of determining which system parameters have the greatest impact upon the operation of the transit system.     

Noisy demand and mode choice

Mode choice under stochastically varying demand is studied via a dynamic mathematical model which describes the behavioural interactions between population groups. The model is developed by assuming competing attractivity functions for automobile and public transit which motivate their use subject to an overall demand for transportation. When this demand is allowed to vary stochastically, a set of stochastic differential equations describing the model are obtained. These are solved for their steady-state values. It is found that noisy demand can structure the system qualitatively differently than when the demand is fixed. The noise is found to generally reduce the level of public transit ridership, but it also changes the values of the threshold at which new regimes occur and, most interestingly, it induces new steady-state solutions for ridership at critical values of the variance of demand. In the latter case, noise becomes a source of new possibilities in the system by triggering a steady-state solution not present in the noise-free environment.