Turn taking behavior in dual earner households with children: a focus on escorting routines

Transportation - This article discusses results of a study on turn taking behavior in escorting children in dual-earner households. Using a multinomial logit model, the probability of different...     

Comparison of advanced imputation algorithms for detection of transportation mode and activity episode using GPS data

Global Positioning System (GPS) technologies have been increasingly considered as an alternative to traditional travel survey methods to collect activity-travel data. Algorithms applied to extract activity-travel patterns vary from informal ad-hoc decision rules to advanced machine learning methods and have different accuracy. This paper systematically compares the relative performance of different algorithms for the detection of transportation modes and activity episodes. In particular, naive Bayesian, Bayesian network, logistic regression, multilayer perceptron, support vector machine, decision table, and C4.5 algorithms are selected and compared for the same data according to their overall error rates and hit ratios. Results show that the Bayesian network has a better performance than the other algorithms in terms of the percentage correctly identified instances and Kappa values for both the training data and test data, in the sense that the Bayesian network is relatively efficient and generalizable in the context of GPS data imputation.     

The prevalence of context-dependent adjustment of activity-travel patterns in energy conservation strategies: results from a mixture-amount stated adaptation experiment

People’s adaptive behaviour to increasing energy prices has been studied at length in transportation research. Prior research however has not addressed research questions concerning the contribution of travel-related changes in more encompassing energy conservation strategies. Moreover, context-dependency and choice under constraints has not been studies at any length. In this paper, we therefore report the results of a context-dependent elaboration of a mixture amount choice experiment to measure context-dependent responses to accumulative energy charges under budget constraints. Accounting for consumer heterogeneity in adaptive response behaviour, mixed logit analysis is used to analyse the extent and nature of adaptations of activity-travel behaviour and resource allocation in response to increasing energy costs. The results indicate that individuals are inclined to compensate for increased expenditures on energy due to price increases. Moreover, results show the existence of significant heterogeneity among respondents in terms of their adaptation strategies to various energy-saving choices.     

Modeling co-dependent choice of workplace,residence and commuting mode using an error component mixed logit model

Transportation - This paper develops an error component mixed logit model to analyze the multi-dimensional residential, work and transportation mode choice. It expanse previous studies based on...     

The development of low-floor trams

The gradual development of trams, i.e., streetcars or trolley cars, from 1950 till 1980 was abruptly interrupted in the early eighties by the arrival of the low-floor car. Six factories in FRG and Austria, one in Switzerland and one in Belgium virtually covered the market based on what roughly could be defined as three designs. Today each of these makers has its own design(s) complemented by those of four italian, one swiss and one french builder. This article aims to give a synthesis of the development. Which designs have so far emerged as leading in volume, what are the technological tendencies that can be traced. What are the price consequences of the development.     

Measuring user benefits of changes in the transport system when traveler awareness is limited

This paper derives and illustrates measures for the ex ante evaluation of user benefits associated with improvements in the transport system. In contrast with conventional analyses, we assume that awareness among travelers of changes in the transport system is limited and grows over time. Specifically, we postulate that each day (trip) provides travelers with an opportunity to learn about changes that occurred recently in the transport system. This learning process may involve learning through direct experience and indirect learning through for example social networks or information provision. Our measure of user benefits incorporates the conventional logsum-measure as a special case (when full awareness is assumed) and has a closed form solution under reasonable error term assumptions. A numerical illustration provides a first sign of face validity. We derive and discuss a number of practical implications, and discuss possible model extensions.     

Transport Innovation: Coping with the Future

An efficient transport system is a crucial precondition for economic development and an asset in international mobility. Mobility of passengers and transport of goods are considered key elements for a modern society. The transport sector is also a sector of continuous technological innovation. However, there is considerable uncertainty surrounding future transport technology and policy, as well as a large variation in ways to deal with this uncertainty. With regard to the latter it may be helpful to use more than one foresight method, e.g. a combination of methods each with a different emphasis on expertise, creativity and interaction with actors. Such a multiple method approach allows for the identification of those futures or future developments that are robust. This paper provides an introduction to the topic of transport innovation as well as providing a context for the four papers which follow in this special issue, illustrating the importance of taking such a multiple method approach.     

Technological innovations in the transport sector: the need for cooperation to meet environmental interests

Environmental problems have become urgent in many countries. A large contribution to the solution of environmental problems is expected from technological change. This raises the issue of how technological change takes place, and more in particular how technological change can be promoted that is beneficial to long term sustainability objectives.

In the paper we discuss this topic in the context of the transport sector. This is relevant because transportation contributes significantly to various types of pollution, existing trends might lead to even more negative impacts and finally there are high expectations about the potential of future technological development to reduce the environmental impact of transportation.

We approach the issue of technological change towards more environmentally sound development from the perspective of technology dynamics and sustainable development. We argue that additional theoretical insights are needed especially when one wants to study technological change in the context of environmental problems. We therefore discuss a strategy of cooperation between government and firms in network. Special attention is paid to the role of the government in networks and the use of a new type of instruments.