Determinants of ground transport modal choice in long-distance trips in Spain

In transport economics, modeling modal choice is a fundamental key for policy makers trying to improve the sustainability of transportation systems. However, existing empirical literature has focused on short-distance travel within urban systems. This paper contributes to the limited number of investigations on mode choice in medium- and long-distance travel. The main objective of this research is to study the impacts of socio-demographic and economic variables, land-use features and trip attributes on long-distance travel mode choice. Using data from 2007 Spanish National Mobility Survey we apply a multilevel multinomial logit model that accounts for the potential problem of spatial heterogeneity in order to explain long-distance travel mode choice. This approach permits us to compute how the probability of choosing among private car, bus and train varies depending on the traveler spatial location at regional level. Results indicate that travelers characteristics, trip features, cost of usage of transport modes and geographical variables have significant impacts on long-distance mode choice.     

An investigation into the feasibility of increasing rail use as an alternative to the car

With rail travel largely seen to be a more sustainable method than road-based transport, this paper examines the market segments amongst existing motorists that would be most likely to travel by train in the UK. The analysis is based on a large survey in London and the south-east of England, the area surrounding the routes operated by the train company First Capital Connect. Findings show that train travellers tend to be middle-aged and of a higher social grade, typically taking commuting or business trips. Individuals living within four miles of a station are considerably more likely to travel by rail than those further away. Given the competition from road-based transport, it is of particular interest that the measure highlighted to increase rail use for those living further away from the rail network is to enhance car parking at train stations.     

Use of a novel dataset to explore spatial and social variations in car type,size, usage and emissions

The ’MOT’ vehicle inspection test record dataset recently released by the UK Department for Transport (DfT) provides the ability to estimate annual mileage figures for every individual light duty vehicle greater than 3 years old within Great Britain. Vehicle age, engine size and fuel type are also provided in the dataset and these allow further estimates to be made of fuel consumption, energy use, and per vehicle emissions of both air pollutants and greenhouse gases. The use of this data permits the adoption of a new vehicle-centred approach to assessing emissions and energy use in comparison to previous road-flow and national fuel consumption based approaches. The dataset also allows a spatial attribution of each vehicle to a postcode area, through the reported location of relevant vehicle testing stations. Consequently, this new vehicle data can be linked with socio-demographic data in order to determine the potential characteristics of vehicle owners.This paper provides a broad overview of the types of analyses that are made possible by these data, with a particular focus on distance driven and pollutant emissions. The intention is to demonstrate the very broad potential for this data, and to highlight where more focused analysis could be useful. The findings from the work have important implications for understanding the distributional impacts of transport related policies and targeting messaging and interventions for the reduction of car use.