Traffic parameter estimation on motorway networks by combination of filtering techniques

In order to perform road traffic control, it is very important to estimate the traffic parameters which can not be measured directly from sensors. In this paper, we will focus on turn fraction estimation based on a new road network representation which is used in traffic control software at the Dutch traffic management company Trinite Automatisering B.V. The common approach for the turn fraction estimation is by applying Kalman filter. However, the sensor information for motorways is not always available due to the fact that there are no physical sensors or detector failure on some parts of motorways. In this case, Kalman filter can not be applied to estimate turn fraction. A new approach by combining of Kalman filter and a low pass data filtering technology called Treiber-Helbing-filter is presented. This approach can contribute solving the problem by using Treiber-Helbing-filter to complete the missing data firstly. Then, turn fraction is able to estimate by using Kalman filter and visualize in traffic control software.