In this paper we analyze the prediction problem and focus on building a multinomial logit model (MNL) to predict accurately, the market shares of new cars in the Swedish car fleet in the short-term future. Also, we investigate whether or not different prediction questions lead to different...

GPS and nomad devices are increasingly used to provide data from individuals in urban traffic networks. In many different applications, it is important to predict the continuation of an observed path, and also, given sparse data, predict where the individual (or vehicle) has been. Estimating the...

This paper considers the path choice problem, formulating and discussing an econometric random utility model for the choice of path in a network with no restriction on the choice set. Starting from a dynamic specification of link choices we show that it is equivalent to a static model of the...

Rank dependent utility maximization is applied in maximizing a linear and a quadratic scheduling model considering a subjective weighting over uncertain outcomes. The optimal departure time and maximal utility are different from that under expect utility maximization in the transformed travel...

Data sources using new technology such as the Geographical Positioning System are increasingly available. In many different applications, it is important to predict the average speed on all the links in a network. The purpose of this study is to estimate the link speed in a network using sparse...

In this paper, we introduce a discrete penalty for excessive travel times into scheduling models whose maximal expected utilities have attractive theoretical features of linearity in standard deviation or variance. The extended models maintain the properties of linearity, and its maximal...