Profile

Saeed is a PhD candidate in the Department of Transport and Planning at the Faculty of Civil Engineering and Geosciences at Delft University of Technology. After receiving his master’s degree in Transportation Engineering in 2017, Saeed joined Traffic Research Laboratory at IUST as a traffic engineer and data scientist and contributed to several regional and national projects in the transportation domain, such as Iran’s Transportation Masterplan Studies, Travel Pattern Discovery using Anonymized Mobile Phone Data in Tehran, and Tehran’s Taxi Fleet Management Study. After a while, he was appointed as a part-time engineer at the department of Intelligent Transportation Systems at Tehran Municipality to study various intelligent transportation systems in the city, including advanced traffic management systems and travelers information systems. In 2021, he and his colleagues in Traffic Research Laboratory launched Transportation Data Analytics Center at IUST, which is the first academic center in the country focusing on collecting and analyzing transportation data.

In 2022, Saeed joined the department of Transport and Planning at TU Delft as a PhD candidate participating in HiDrive, a flagship EU-funded project, that aims to make driving automation robust and reliable by taking intelligent vehicle technologies to conditions and scenarios neither extensively tested nor demonstrated earlier in European and overseas traffic. Saeed is using AI and theory to study the complex interactions in a mixed flow of automated vehicles (AVs) and human-driven vehicles in order to assess the impacts of AVs on traffic flow and transportation network efficiency and safety.

Research

Saeed is specifically interested in combining AI and theory to make use of the bests of the two worlds toward solving traffic and transportation problems. At TU Delft, he is to develop an AI-based control logic for automated vehicles that can reproduce diverse driving styles and strategies and execute complex maneuvers in heterogeneous traffic conditions. This AI-based control logic could be applied in simulation environments to 1. assess the impact of automated vehicles on traffic flow in complex environments and 2. evaluate the applicability and safety of currently developed motion planning models in more realistic traffic conditions. To achieve such a model, Saeed aims to develop a generic framework that is built upon artificial intelligence (learns from data and over time), but at the same time may benefit from theory (to be as interpretable as possible and also consistent with physics rules).