European Transport / Trasporti Europei (2010) 44/XV

The influence of land use on daily mobility patterns can be described by the two dimensions of urban form: the first is quantitative, that is density, and the second is qualitative, that is land use mix. Empirical studies usually add control variables such as sociodemographic characteristics. They suppose that urban form factors and sociodemographic factors have a separate influence on travel patterns. In this paper, we first show the possibility of a causal relationship between urban form and sociodemographic characteristics. Thus previous results, which suppose that these two kinds of factors are separated, may be biased. It describes systematic relationships between urban form, socio-demographic characteristics, and daily mobility. As a consequence, we have to use specific econometric methods to test the motives of mobility. We develop a new tool: the “typological regressions”. Travel patterns in the metropolitan area of Bordeaux are then analyzed. Results allow to disentangle the interaction between land use pattenrs and travel behaviours.

This paper presents a study on the impact of investment in the Betuweroute and alternative transport pricing schemes on port competition between Rotterdam, Hamburg and Antwerp. The Betuweroute is a 160 kilometre dedicated freight railway line connecting the port of Rotterdam with the German Ruhr area. If the line could, in the near or more remote future, attract a large share of transit freight, it will be of considerable importance for the competitive position of the port of Rotterdam relative to Hamburg and Antwerp. We use a transport network model that includes the three ports and allows for transport by road, rail and inland waterways to and from the Ruhr area. We run model simulations for scenario’s with and without the Betuweroute and with and without marginal social cost pricing. The results show that, although the Betuweroute is a welfare reducing investment, it may indeed be of crucial importance to the port of Rotterdam.

This work aims at developing a demand-based methodology for designing the bus network of a small or medium town. The proposed modelling tool adopts a multi-agent objective function which evaluates performance in the context of different stakeholders: the surplus of travellers (car and bus users); the bus service provider’s revenues and operation costs. This approach was applied to an existing bus network, serving Trapani, which is a medium town in the south of Italy (Sicily), with 100000 inhabitants. The busbased public transport system attracts only about 5% of commuter trips within Trapani (source: National Institute of Statistics, 2005). This paper reports on an analysis of the application of the proposed multiagent modelling tool to two planning scenarios: the first is short-term and characterized by a budget constraint (slight changes in the availability of drivers and vehicles) and the second long-term with new investments in new buses to improve services and increase patronage. In both cases, the impact of the recent car park charging policy launched by the local administration was considered. The decision variables for the optimisation procedure were route, service frequency and capacity of each bus line. A random utility model was employed to forecast the mode choices for trips within Trapani and the travel demand-supply equilibrium was obtained using the DUE (deterministic user equilibrium) assignment algorithm, for private transport, and the hyperpath network loading algorithm, for public transport. The optimisation procedure led to a more efficient bus network characterized by increase in bus frequencies and a better performance in terms of reduced travel time, especially for trips bound for the “old town” in the morning. In addition, a higher number of origin-destination pairs were served, at the expense of the need to interchange between the inner more frequent and the outer less frequent services. This implied that the number of transfers from one bus line to another significantly increased.

Instead of giving a negative incentive such as transport pricing, a positive incentive by rewarding travelers for ‘good behavior’ may yield different responses. In a Dutch pilot project called Peak Avoidance (in Dutch: “SpitsMijden”), a few hundred travelers participated in an experiment in which they received 3 to 7 euros per day when they avoided traveling by car during the morning rush hours (7h30–9h30). Mainly departure time shifts were observed, together with moderate mode shifts. Due to the low number of participants in the experiment, no impact on traffic conditions could be expected. In order to assess the potential of such a rewarding scheme on traffic conditions, a dynamic traffic assignment model has been developed to forecast network wide effects in the long term by assuming higher participation levels. This paper describes the mathematical model. Furthermore, the Peak Avoidance project is taken as a case study and different rewarding strategies with varying participation levels and reward levels are analyzed. First results show that indeed overall traffic conditions can be improved by giving a reward, where low to moderate reward levels and participation levels of 50% or lower are sufficient for a significant improvement. Higher participation and reward levels seem to become increasingly counter-effective.