Efficiency analysis of transit signal priority using microsimulations : A case study in Turku City

Abstract

This paper studies the effectiveness of implementing a transit signal priority (TSP) system in Turku city using microsimulations. TSP is a technology that prioritises buses at traffic lights to make the public transport system faster and more punctual. The research was conducted by building a microsimulation using real-world data from induction loops placed along the route and with the help of bus logs. The paper tests different variables by altering the detector distance between 60,90,120,150 and 180 metres. The effect on non-prioritised traffic is also studied in the paper.

The TSP system being implemented in Turku is a centralised GPS based TSP system. While GPS based TSP systems exist around the world, there are many other technologies also used for TSP systems. Therefore, the paper reviews and compares the result from previous studies on what differs between the technologies. The literature chapter also reviews studies that can help Turku to improve their system further, once the TSP system has been implemented.

According to the results, a TSP system reduces the total route duration by 7.8-10.8% for the east direction and 10.5-15.8% for the west direction. The lower limit is when the detectors are placed 60 metres from the intersection, and the upper limit is when the detectors are placed 180 metres from the intersection. Moving the detector distance 30 metres farther from the intersection showed a significant improvement. However, the returns were diminishing after 150 metres from the intersection. Placing the detector farther away from the intersection also doubled the number of extensions given, and after 150 metres, the other priority types started to reduce. Extensions are preferred to red light shortenings and extra greens, as they have the least amount of disturbance on the general traffic. The result also showed that implementing a TSP system did not have a significant effect on general traffic.

The paper also reviews whether simulations should be used more in traffic planning within Turku city. Therefore, the paper explains in great detail all the steps necessary to build a simulation in SUMO. From the result, it is recommended that Turku city does not focus on large scale simulation as they are very time consuming, and their accuracy can often be questioned. However, it is recommended that Turku city continues to use small scale simulations as they are much quicker to build compared to large scale simulations. With simulations, the traffic planning department can quickly test many different variables and gain a more comprehensive understanding of the system, which could take up to years to test in the real world.