Intelligent Transportation Systems & Traffic Simulation
Traffic microsimulation describes the process of creating a virtual model of a city's transportation infrastructure in order to simulate the interactions of road traffic, and other forms of transportation, in microscopic detail. Traffic microsimulation computer models capture the interactions of real world road traffic through a series of complex algorithms describing car following, lane changing, gap acceptance, and spatial collision detection. In addition, free form pedestrian movement is replicated using agent based spatially aware models allowing road traffic to interact with pedestrians as they do in the real world.
Dr. Ilgin Gokasar’s research in the area of traffic engineering focuses on traffic micro-simulation and traffic data analysis for the application of Intelligent Transportation Systems. Using traffic data of a selected area, traffic conditions are simulated in order to investigate different parameters influencing traffic. Additionally, big data gathered with traffic sensors is processed using machine learning tools and resulting the inference enables the estimation of traffic conditions on a macro level. Dr. Gokasar is also studying on trajectory data of transport fleets which have been augmented with automated vehicle location (AVL) systems which use GPS to collect probe data and support Real-Time Information (RTI) systems. The project contains different steps including data mining, map matching, data aggregation, traffic data analysis.
Sustaiable Transportation Planning
Sustainable Transportation is any form of transportation that does not use or rely on diminishing natural resources such as fossil fuels. Instead, it relies on renewable or regenerated energy. For this reason it is said to have a low or a negative effect on the environment since it makes use of energy sources that are sustainable. With the increase of the global awareness about sustainability and health in 21st century, sustainable transportation has become an important and priority topic in transportation science.
Dr. Ilgin Gokasar’s interests in sustainable transportation is mainly focused on applications of transportation demand management strategies in sustainable transportation planning. Traditional planning tools and modern planning approaches are used together to adress the issues in sustainable transportation. Sustainable campus transportation planning is another topic that Dr. Gokasar is interested in with focus on monitoring and data collection applications, travel behaviors, and transportation demand management strategies suitable for university communities.
Travel behavior is crucial in travel demand management as well as in urban and transport planning. Over the past decade, with the advancement of data collection techniques such as GPS and mobile phones, various types of real time traffic information are acquired by some traffic applications. Real time traffic information enables road users to make decision about their travel pattern and to avoid unexpected severe congestion. Traveler response to this information is critical to the design and implementation of effective Intelligent Transportation Systems.
Dr. Ilgin Gokasar’s interests are currently related to drivers’ route choice behavior under real-time traffic information and the effect of real-time travel information on activity-based models.