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Gokhan Budan is originally from Turkey. He joined Oxford Brookes in April 2016 and his thesis title is ‘Non-signalised Intersection Control for Connected Human-Driven and Autonomous Vehicles’.
I am currently working full-time as an Electronic Design Engineer at Zeta and undertaking a part-time PhD as a member of the Low Carbon Vehicles Research Group within the School of Engineering, Computing and Mathematics. I heard about Oxford Brookes University through Phil Shadbolt OBE, who is the Chairman and CEO of Zeta. Phil also graduated from Oxford Brookes University.
One of the main attraction points for me is the fact that about 95% of the research work at Oxford Brookes University is recognised by the latest Research Excellence Framework. This was a clear indication for me to conduct my research here. In addition to that, the School of Engineering is well-known for its automotive and motorsports technology and engineering courses. This was also an important decision factor for me during my application process, as my research work is within the automotive sector.
Upon my graduation from Newcastle University in 2013, I started working as a Systems Verification Engineer at Schrader Electronics, the designer and manufacturer of tyre pressure monitoring systems in the automotive industry. The pursuit for knowledge and experience has always been one of my goals in life. Therefore, to satisfy my professional curiosity and to fulfil my ambitions, I started working at Zeta as an Electronic Design Engineer in 2015. This gave me the opportunity to work on many diverse projects such as advanced All-Wheel-Drive electronic control unit design for the automotive industry and solar powered smart LED lighting controller design. By working in today’s challenging automotive industry, I learnt the intricacies of algorithm development, embedded system design and programming.
From day one, I felt at home thanks to the support of the research administration team, who made my registration and introduction process easy. Moreover, my supervisors were very supportive especially in terms of project planning and technical feedback on my research subject which helped me settle in the research environment. The University has some state-of-the-art computing and laboratory equipment and resources which are all available to research students.
There is an urgent need to address the urban traffic congestion issues caused by increasing numbers of vehicles. Traffic congestion has a significant impact on the national economy, environmental pollution and high fuel usage. The introduction of traffic light control for intersections has helped to improve the congestion issues. Moreover, several recent studies investigating adaptive signal-control, based on real-time data, under non-deterministic traffic conditions have been carried out, and argue that they outperform traditional traffic light control methods. However, traffic lights still lack coordination to detect the spatial and temporal evolution of traffic congestion within the control regions and they do not take advantage of the increased sensitivity and precision of connected and autonomous vehicles.
Intersection management is an important component in urban traffic, and plays a key role in ensuring traffic safety and smoothing traffic flow. Recently, a lot of work has been reported on the theme of connected and driverless vehicles, with increasing interest in autonomous intersection management, where traditional traffic lights are replaced with intelligent roadside units. This has been shown to reduce traffic congestion and delays significantly by taking advantage of the increased sensory precision of connected and driverless vehicles as compared to human-driven traditional vehicles. The concepts of vehicle-to-infrastructure (V2I) wireless communication, multi-agent systems and artificial intelligence are central to achieving robust and reliable autonomous intersection management.
My PhD project seeks to design an autonomous intersection control system for connected human-driven and driverless vehicles without traffic lights. In this system, the intention is that vehicles will reserve time and space as they approach an intersection, and intersection manager agents control vehicles crossing in a conflict-free way. A machine learning framework will also be included to improve traffic control efficiency in terms of vehicle delays and intersection throughput by learning from experience dynamically. Therefore, intersection manager agents can learn optimal intersection control actions such as vehicle prioritisation, scheduling for crossing and trajectory planning in an iterative way by both exploring new actions and exploiting previously experienced actions for the given situations.
The proposed project offers a number of features which are innovative, both commercially and technically. The innovation is the application of non-signalised traffic intersection management within this new environment of connected vehicles by utilising vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) wireless communications to reduce average vehicle delay and to increase throughput at intersections whilst ensuring safety and lower carbon emissions.
Researchers are pushing the boundaries of human knowledge every day and I would say this is the best part of being a research student; knowing that your contributions are going to improve the lives of the next generation and make the world a better place. However, the road to success in research is not a straight highway but a bumpy off-road experience. Strong motivation and a clear sense of purpose is important in this journey. Having a project plan with deliverables and milestones throughout a research project is extremely useful and must be stuck to in order to reach the end goal.
Research training courses at the University are diverse and cater for all students. The courses include not only project-related subjects but also more general subjects such as teaching, time management, and career advice, which prepare research students for life beyond university.
My prime ambition in life is to become one of the leading engineers in intelligent machines and systems design. Studying for a PhD in this field is my first step towards achieving this goal. I believe that research is of prime importance in understanding the complexities involved in developing such systems. Hands on experience in real-time applications, accompanied by in-depth knowledge of the subject, will help me contribute to this growing field.