Abstract
Quantifying the impact of the application of sustainable transport policies is essential in order to mitigate effects of greenhouse gas emissions produced by the transport sector. One of the most common approaches used for this purpose is that of traffic modelling and simulation, which consists of emulating the operation of an entire road network. This article presents the results of fitting 8 well known data science methods for transport choice modelling, the area in which more research is needed. The models have been trained with information from Biscay province in Spain in order to match as many of its commuters as possible. Results show that the best models correctly forecast more than 51% of the trips recorded. Finally, the results have been validated with a second data set from the Silesian Voivodeship in Poland, showing that all models indeed maintain their forecasting ability.
Highlights
Transport systems performance evaluation and forecasting is a difficult task currently under consideration by many research centers
GeoWorldSim is a powerful software that eases the integration of multi-agent systems with reference simulations tools such as Matlab or EPA-NET
Simulations were executed on two computers: large experiments were run on a system with an AMD Opteron 6168 CPU and 32 GB of RAM, and short experiments were run on a system with an Intel Core i7-2600 CPU and 16 GB of RAM
Summary
Transport systems performance evaluation and forecasting is a difficult task currently under consideration by many research centers. This complexity emerges mainly due to its stochastic nature, whereby a large number of variables and personal preferences come into play [1]. A cheap and flexible method for testing future transport developments is to use computer simulations supported by advanced mathematical models [3]. To calculate the impact of the transport sector, traditional approaches are relying on simulations, a paradigm that has become a popular and effective technique to analyze a wide range of dynamically changing systems. Traffic simulation allows one to check, monitor, and evaluate the behavior of the real systems under different realistic conditions in an artificial-computer-based environment [5]. Most common traffic simulations focus on simulating everyday traffic activity in search of congestions, assessing different ways of enabling traffic in intersections (crossings, roundabouts, traffic lights, etc.) or applying dynamic speed limits to avoid jams
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