In-Vehicle Sensor Data for Traffic Management II

Greater accessibility in the Netherlands is a goal that is being pursued for a long time. With regard to transportation it refers to the ease of reaching destinations from various locations. The improvement of the accessibility is beneficial for every road user, because it leads to a better flow of the traffic. An improvement of the traffic flow allows road users to adjust their behaviour before and during their time on the highways.

Nowadays the information of inductive loop detectors is used to measure the traffic flow. However, automobiles and the roads they are driving on, are equipped with a lot of sensors. The Smart in-car project is launched to gather the relevant data from these sensors, such as speed, steer position and brakes. For this project, three hundred cars in Eindhoven are equipped with a uCAN which makes the data accessible.

As a step in removing the inductive loop detectors, this thesis will focus on the possibility of measuring the traffic flow with data of the uCANs. With the simulation model Fosim we will determine the smallest percentage of cars with a uCAN that is needed to measure the traffic flow accurately.

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