HFauto

Dr. Haneen Farah

Haneen Farah is an assistant professor at the Department of Transport and Planning, the Faculty of Civil Engineering and Geosciences, at Delft University of Technology. Her research interests and experience spans the areas of traffic safety, driving behaviour modelling, road geometric design, and automated vehicles. Haneen’s research combines elements from the transport systems analysis, behavioural and human factors sciences, and econometrics.

She received her Ph.D. degree from the Technion – Israel Institute of Technology in 2009. Haneen’s Ph.D. thesis focused on the development of models to evaluate safety of two-lane highways based on infrastructure, traffic characteristics and drivers’ behaviour. From 2009 – 2011, she was post-doctoral researcher at the Department of Transport Sciences, KTH – Royal Institute of Technology, Stockholm, Sweden. During that time Haneen focused on important problems in the area of emerging technologies and on advancing the state of the art in modelling driver behaviour. She developed new car-following and lane changing models. She was actively involved in several European projects, COOPERS “CO -OPerative SystEms for Intelligent Road Safety”, MULTITUDE “Methods and tools for supporting the use, calibration and validation of traffic simulation models”, and TEMPUS IV “Highway Design and Management: Curricular Reform for Russian Federation – Design and Implementation of Higher Education Master Courses in Russia”.

Haneen got also the opportunity to work at a non-profit organizations from 2012-2014, Ran Naor Foundation, where she was involved in conducting research with a strong application orientation, such as improving the safety of young drivers during their first year of driving and affecting the Israeli policy on driving licensing rules, and studying the walking routes of children to school and investigating potential effective interventions.

Currently, at TU Delft, Haneen is involved in the HFAuto project (Human Factors of Automated Driving) where we focus on predicting the effects of transient manoeuvres on traffic flow efficiency; the WEPod project, focusing on defining the requirements in the road infrastructure for the self-driving Pods, especially from the point of view of safety; in a STW funded project “Taking the fast lane”, focusing on developing a persuasive lane use advice provision in relation to driver workload and user acceptance.

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