Activity-based model development to support transport planning in the Stockholm region

The environment in which transportation analysis and infrastructure planning take place has changed dramatically during the last years. The focus is now, to a considerable extent, on how to transform the transportation system in a direction that could be sustainable in the long run, rather than on planning for infrastructure investment to meet new demand. At the same time information technology penetrates all sectors of the society. This will change how the transportation system will be used by travellers and conveyers, both directly, through new products and services, and, indirectly, through a spatial reorganisation of many activities that govern the transport demand. In such a situation it must be questioned whether the analytical tools that may have functioned reasonably well in the past, also are appropriate, or possible to adapt, to be useful for the issues we will face in the future. A survey is made of ideas for model development for travel analysis with an emphasis on activity based models based on an international literature review. The study treats tools for the whole chain from location decisions to network effects. The main focus is on such development that is of interest for a medium-sized city like Stockholm. It stresses demands that might be raised on modelling tools with a background in the planning issues that can expected to be central within the next ten-year period. Different ideas for model development, and existing models that could be considered for implementation, are evaluated with respect to their usefulness for planning, need for resources, demand for competence and data, and obstacles of implementation. Finally, we are suggesting some specific model development that should be tested in Stockholm, including a pilot study concerning the implementation of an activity-based model.

Probabilistic Choice as a Result of Mistakes

We derive a family of probabilistic choice models including the multinomial logit model, from a microeconomic model in which the decision maker has to make some effort in order to avoid mistakes when implementing any desired outcome. The disutility of this effort enters the decision maker's goal function in an additively separable way. A particular disutility function, yielding the multinomial logit and GEV models as special cases, is characterized axiomatically. Unlike the usual random-utility approach, the present approach leads to a normalization of the achieved utility with respect to the number of alternatives. The present model also applies to continuum choice sets in Euclidean spaces, and provides a microeconomic foundation for quantal response models in game theory. Choice; Decision Theory; Mistakes

Invariance of the distribution of the maximum

Many models in economics involve probabilistic choices where each decision-maker selects the best alternative from a finite set. Viewing the value of each alternative as a random variable, the analyst is then interested in the choice probabilities, that is, the probability for an alternative to give the maximum value. Much analytical power can be gained, both for positive and normative analysis, if the maximum value is statistically independent of which alternative obtains the highest value. This note synthesizes and generalizes previous results on this invariance property. We provide characterizations of the property within a wide class of distributions that comprises the McFadden GEV class, show implications in several directions, and establish connections with copulas. We illustrate the usefulness of the invariance property by way of a few examples

Developing a methodology for road network vulnerability analysis

TSC import 635 2012-01-30. QC 20120219</p

The impact of network density, travel and location patterns on regional road network vulnerability

TSC import 153 2012-01-30. QC 20120208</p

Transportsystemets sårbarhet och resiliens

QC 20160304</p

The vulnerability of road networks under area-covering disruptions

QC 20111118</p

Developing a methodology for road network vulnerability analysis

TSC import 635 2012-01-30. QC 20120219</p