Abstract
Activity-based micro-scale simulation models for transport modelling provide better evaluations of public transport accessibility, enabling researchers to overcome the shortage of reliable real-world data. Current simulation systems face simplifications of personal behaviour, zonal patterns, non-optimisation of public transport trips (choice of the fastest option only), and do not work with real targets and their characteristics. The new TRAMsim system uses a Monte Carlo approach, which evaluates all possible public transport and walking origin–destination (O–D) trips for k-nearest stops within a given time interval, and selects appropriate variants according to the expected scenarios and parameters derived from local surveys. For the city of Ostrava, Czechia, two commuting models were compared based on simulated movements to reach (a) randomly selected large employers and (b) proportionally selected employers using an appropriate distance–decay impedance function derived from various combinations of conditions. The validation of these models confirms the relevance of the proportional gravity-based model. Multidimensional evaluation of the potential accessibility of employers elucidates issues in several localities, including a high number of transfers, high total commuting time, low variety of accessible employers and high pedestrian mode usage. The transport accessibility evaluation based on synthetic trips offers an improved understanding of local situations and helps to assess the impact of planned changes.
Highlights
Increasing traffic is an inherent symptom of vigorous urban development and its prosperity, but is concurrently one of the main factors that contribute to the deterioration of the urban environment and the endangerment of the sustainability of urban development
The aim of this paper is to highlight some specific features of the system, such as the utilisation of personal characteristics, activity-driven modelling, and optimised Public transport (PT) trips selected from the full set of possibilities within the given time interval and k-nearest stops according to several criteria, as well as a discrete choice of targets, and implementation into the distributed client-server software enabling large computations
The model was tested and evaluated for Ostrava, the centre of the Moravian–Silesian region situated in northeastern Czechia
Summary
Increasing traffic is an inherent symptom of vigorous urban development and its prosperity, but is concurrently one of the main factors that contribute to the deterioration of the urban environment and the endangerment of the sustainability of urban development. Public transport (PT) represents the main sustainable mode of urban mobility [1] and improves social equity and cohesion. Local governments aim to improve PT’s utilisation and attractiveness to decrease the volume of individual car transport and to motivate people to shift their transport modes towards more environmentally friendly means. Ingrained habits and social perceptions play a larger role than economic reasons, and a coherent urban transport policy must be applied to achieve increased PT usage [8]. Increasing usage of PT is determined by the improvement of PT performance and quality, as well as by increasing opportunities around PT infrastructure [8]
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