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Dr. Ilgın Gökaşar (Director of Boun-ITS LAB) has been working as a faculty member of Civil Engineering department in Bogazici University since 2007. She teaches undergraduate and graduate courses and supervises MSc and PhD students in the Civil Engineering Department. She also offers courses in Construction Engineering Management (CEM) Program in Civil Engineering Department.

Intelligent Transportation Systems & Traffic Simulation
Traffic microsimulation describes the process of creating a virtual model of a city's transportation infrastructure for simulating the interactions of road traffic, and other forms of transportation, in microscopic detail. This involves treating each vehicle in the model as a unique entity with its own goals and behavioral characteristics; each possessing the ability to interact with other entities in the model.

Dr. Gökaşar’s research about traffic engineering focuses on traffic micro-simulation and traffic data analysis for the application of Intelligent Transportation Systems (e.g., Ramp Metering, Incident Management, Advanced Public Transportation Systems, Advanced Traffic Management Systems, and Advanced Traveler Information Systems). Using traffic data of a selected area, traffic conditions are simulated for investigating different parameters influencing traffic. Additionally, big data gathered with traffic sensors is processed using machine learning tools and its inference displays the traffic conditions in a macro level. Dr. Gökaşar is also studying on trajectory data of transport fleets which have been augmented with automated vehicle location systems using GPS to collect probe data and support Real-Time Information systems. Her current project contains different steps including data mining, map matching, data aggregation, traffic data analysis.

Sustaiable Transportation Planning
Sustainable Transport is any form of transport that does not use or rely on diminishing natural resources that are finite, but relies on renewable or regenerated energy, which are environmentally friendly. With the increase of the global awareness about sustainability and health in 21st century, sustainable transportation has become an important topic in transportation science.

Dr. Gökaşar’s interests are mainly focused on applications of transportation demand management strategies in sustainable transportation planning, and carpooling, carsharing, ridesharing topics. Both traditional and modern planning approaches are used together to address the issues. Sustainable campus transportation planning is another field that Dr. Gökaşar interested in. Monitoring and data collection applications (RFID based vehicle identification) in universities, travel behavior differences between students, administrative staff and faculty, and transportation demand management strategies suitable for university communities are her research topics.

Travel Behavior
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, various types of real time traffic information are acquired by traffic applications, enabling road users to decide on their travel patterns. Travelers’ response to this information is critical to the design and implementation of effective Intelligent Transportation Systems.

Dr. Gökaşar’s interests are currently related to drivers’ route choice behavior under the real-time traffic information and the effect of real-time travel information on activity-based models. Special attention is given on modelling travelers’ decision making patterns on freeways as a result of the provision of various types of real-time traffic information acquired by traffic applications which were analyzed separately due to their special features. The research should be useful for modelling travel behavior using discrete choice models.



Ali A. Arısoy, Research Assistant

Ali A. Arısoy’s studies focus on autonomous vehicles, public transportation systems  and data analysis. By utilizing simulation and data analysis software, the impact of autonomous vehicles on the traffic is inspected. Using diverse optimization algorithms the efficiency of the public transportation systems is expected to be increased. By converting these public tranportation vehicles into autonomous vehicles, further improvements in terms of safety and accessibility are to be expected. However, an increase in traffic congestion and insufficient infrastructure issues are potential risks. Reseach about this matter is in progress to avoid any future problems and maximize the benefits.