Modelling travel time in urban networks: comparable measures for private car and public transport

Analysing the accessibility disparity between different travel modes is recognised as an efficient way to assess the environmental and social sustainability of transport and land use arrangements. Travel times by different travel modes form an essential part of such an analysis. This paper aims to assess the comparability of different methods for calculating travel time by different travel modes. First, we briefly review the methods used in previous studies and identify different typical approaches, which we then compare. We use three computational models respectively for car and public transport (PT), implemented in our case study area, the capital region of Finland. In the car models, (1) the simple model ignores congestion and parking in travel time calculation; (2) the intermediate car model accounts for congestion but ignores parking; and (3) the more advanced car model takes into account all parts of the journey, including congestion and parking. For PT, (1) the simple model accounts for transit routes but ignores schedules; (2) the intermediate model incorporates schedule data in a simplistic way; and (3) the more advanced model adopts a door-to-door approach where true schedules (incl. congestion) and realistic route combinations are accounted for. Our results show that absolute differences in car and PT travel times are notable in the Greater Helsinki area, no matter which models are used for comparison. Modal travel time disparity appears smallest in the city centre area. We conclude that using conceptually corresponding models for car and PT travel time calculations is the key to achieving a reliable analysis of modal accessibility disparity. A door-to-door approach in travel time calculations (adopted in the most advanced models) also makes the results truly comparable in absolute terms. Finally, the more advanced the applied methods are, the more data hungry the analysis is. Here, recent developments in open data policies among urban transport data producers become very helpful.