André de Palma

The impact of adverse weather conditions on the propensity to change travel decisions: A survey of Brussels commuters

New developments in transportation systems and the increasing complexities of urban living are creating challenges and opportunities to comprehensively address transportation problems. The key to exploiting new opportunities lies in understanding how travelers would respond to changes in the transportation system. This study aims to understand traveler behavior under normal and unexpected travel conditions in real-life situations. The results of a comprehensive behavioral survey conducted in Brussels are reported. Commuters mode, departure time and route selection decisions, and the factors that influence them, including travel conditions, personal and household characteristics, and situational constraints, are explored. The paper develops a deeper understanding of automobile commuters response to adverse weather. Automobile commuters constitute more than 50% of the total sample (N = 1218). They were asked about adverse weather impacts on their mode, route and departure time changes. Among those who changed their travel decisions in adverse weather (about 50%), more than one-quarter reported that adverse weather was either very important or important in changing their mode; and 60% changed their departure time due to adverse weather whereas 35% diverted to alternate routes. Furthermore, close to 75% kept themselves informed about weather through secondary information sources such as radio and television. To analyze relationships empirically, ordered probit models of mode and departure time were estimated. The models show that commuters change their travel patterns in systematic ways when adverse weather occurs. Finally, the implications of the survey results for dealing with adverse weather problems are discussed.

Stationary dynamic solutions in congested transportation networks: summary and perspectives

The objective of this paper is to provide a systematic treatment of the stationary equilibrium dynamic solutions in large congested networks. We describe the Stable Dynamics approach that is based only on logical assumptions, and is amenable to a rigorous mathematical description. All parameters in use have a direct physical meaning and interpretation. We show existence of the stationary solutions under fairly weak assumptions. For completeness, we present (and criticize) the standard static traffic assignment models and discuss the key differences.

Risk Aversion, Road Choice, and the One-Armed Bandit Problem

This paper provides a theoretical analysis of advanced traveler information systems for road choice with risk-averse drivers who rationally learn over time, in a simple setting. For this purpose, we study the one-armed bandit problem where a driver selects, day after day, either a safe or a random road. Four information regimes are envisaged. The visionary driver knows beforehand, with certainty, the travel time on the random road, while the locally informed driver needs to select a road to acquire information on it. Two intermediary information regimes (fully and globally) are also envisaged. We analyze these four regimes and compare the optimal strategies and the individual benefits with respect to individual risk aversion. A numerical example also illustrates the impact of risk aversion on dynamic optimal strategies.

Route Choice Behaviour with Risk-Averse Users

We study route choice behavior for a simple network consisting in two routes in parallel when the travel time on one route is uncertain. User’s preferences are described by a utility function including a risk aversion parameter. We assume that users select the route with the highest expected utility and therefore we generalize the Wardrop principle. We study the impact of the risk aversion parameter on route choice. Finally, we propose a measure for computing the cost of uncertainty and apply it to a simple example. This analysis provides an alternative method to compute the benefit of Intelligent Traveller Systems.

Imperfect competition and congestion in a city with asymmetric subcentres

This paper develops a model for the monopolistic competition of subcenters for the shoppers and workers of a central city. The model is an extension of the de Palma & Proost (2004) model that is limited to the symmetric case. Inhabitants of a CBD can choose one of the subcenters to buy a differentiated product and choose one of the subcenters to supply differentiated labour. The subcenters compete in prices and wages and the access to the subcenters can be congested. The short term and free entry equilibria are studied. As general properties are rare in the non-symmetrical monopolistic competition case, this paper draws more on numerical examples than on hard theorems. Starting from a symmetric base case, the paper explores the effects on welfare and number of subcenters of introducing diversity in the distances to the subcenter, quality of the subcenters, congestion and attractiveness of the subcenter as workplace. The paper shows cases where asymmetry can increase welfare and where the order in which firms enter the market matters for the equilibrium outcome.