Using Traffic Modeling to Explore How Congestion Information Affects Traffic



Smith, Jennifer L

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Transportation plays a major role in a country as the performance of the transportation system is important to its economic or social health. The time to get to an event is dependent on transportation system or traffic. When talking about traffic, the issue is not only the distance to be traveled but it is about the number of drivers on the road and the traffic congestion created by the number drivers on the road. Traffic congestion is an increasingly common problem for drivers. It impacts travel speeds and increases the amount of time to get to the desired activities. The objective of this master’s thesis is to investigate how the information about traffic congestion affects traffic. The hypothesis is that due to the information traffic congestion such as information provided by sources such as social media, drivers would take an alternate route which helps reduce traffic congestion. Results will show that due to the information about traffic congestion, traffic was affected. Traffic congestion information could come from information from friends or by information from social media. As people see using these sources to gain information about traffic incidents and thus taking alternate routes to avoid the incidents, either from their own experience or from experiences they hear about on social media or other sources, the more alternate routes will be taken and traffic congestion would be affected.



Geospatial, Congestion, Traffic, Social media