Assessment of travel time reliability as a fundamental factor in travel behaviour has become a very important aspect in both transport modelling and economic appraisal. Improved reliability could provide a significant economic benefit if it is adequately calculated in cost-benefit analyses for which the theoretical background has already been set. However, methods to forecast travel time reliability as well as travel behaviour models including its effects are rather scarce and there is a need for development in this field. Another important aspect could be the influencing factor of reliability in travel demand management and related policy-making. Therefore, this paper intends to further analyse reliability focusing exclusively on urban road transport based on automatic measurements of journey times and traffic volumes from a dataset of the city of Budapest. The main finding and the novelty of the study is a model which can forecast the standard deviation of travel times based on the volume-capacity ratio and the free-flow travel time. The paper also provides a real-life numerical experiment in which the proposed model has been compared with other, existing ones. It proves that besides existing mean-delay-based models, travel time reliability can be forecasted based on the volume-capacity ratio with an adequate accuracy.

Management and development of transport systems should always rely on the knowledge of travel demand. It is suggested to shape transport networks and services based on long-term strategies, which is obviously adjusted to long-term trends in the demand. However, it might be difficult to get to know the prompt demand, and even harder to forecast it. Before and during the economic crisis a simple, over-optimistic approach could be noticed in Hungarian appraisals. Realistically there was a complex change in travel patterns. The objective of this paper is to assess the recent changes in travel demand in Budapest and collect the possible main drivers. In this evaluation an extensive database from 2004 was compared with the results of recent analyses. From the data comparison conclusion could be drawn concerning the changes in the transport system usage in a changing economic environment.