A performance analysis of a congested multimodal intersection using VISSIM: A case study of Åkareplatsen, Göteborg

Sammanfattning

Åkareplatsen is a complex intersection in the city centre of Gothenburg, Sweden’ssecond-largest city, that is utilised by buses, trams, cars, trucks, bicyclists and pedestrians. Since the rebuilding in 2018, Åkareplatsen has been struck by recurringcongestion, gridlocks and accidents. To study this roundabout with tram-crossingtraffic, a model created in VISSIM was analysed, calibrated and validated using 2024traffic data. This study is limited to what is possible wihtin the bounds of VISSIM.The method primarily consisted of collecting traffic data in the field and official data,model calibration and validation, interviews, suggestions for improvements, and astress test. To capture the stochastic variability of the model simulations, the sim ulation time was set to 3 hours in 15-minute intervals and was repeated in 10 runs.Queue length and travel time were the measures of effectiveness (MOEs) used tocompare the model versions and reality during maximum traffic flow. The deviationbetween the simulation results and the field measurements was evaluated visuallyfrom video recordings and statistically using Root Mean Square Error (RMSE). Thefinal model calibration was able to capture realistic diving behaviour and deviatedby 33 minutes and 49 seconds in travel time and 104 m in queue length, an improvement compared to the original model. During validation, it was found that thecalibrated model is about equal at estimating travel time and queue length duringcalmer and more dense traffic states. From the simulation results of suggestions forimprovements, removing signal heads for tram-crossing traffic and re-routing someof the bus lines greatly reduced queues and the number of gridlocks. The stress testwith a higher public density load shows that the suggested design can manage a50 % increase in public transportation density without extensive gridlocks forming.Realistic traffic models are time-consuming to build, require a lot of data, and donot directly reflect reality. Nonetheless, they can be beneficially used to anticipatetraffic-related problems, avoid potential damages they cause, and provide citizenswith their need for mobility.