Automatic bottleneck detection using AVL data: A case study in Amsterdam

In daily practice, public transport authorities and operators are constantly searching for improvements in public transport operations. To this end, it is necessary to identify inefficiencies and bottlenecks in the current public transport services. In this paper, we propose a method to automatically detect bottlenecks in the public transport network, using Automatic Vehicle Location data. A tool is developed to automatically process AVL data to identify bottlenecks for the current situation. This tool is applied to Amsterdam, capital of the Netherlands, where a new metro line will come into operation in the summer of 2018. The results show that bottlenecks are mainly found on radial lines and in the inner city. Therefore we expect that the operations of the tram network will improve in terms of operating speed and reliability due to the opening of the metro line, since the tram lines are expected to become less crowded and fewer lines will traverse the inner city.