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Project info

What this project is about? Vehicle manufacturers and the automotive industry are investing huge efforts and resources in realizing the vision of fully automated vehicles. However, the deployment of these vehicles in traffic will be gradual. This will result in a long transition period, in which vehicles with various levels of automation and traditional vehicles co-existing, resulting in mixed traffic. As a consequence, new types of interactions will emerge between vehicles at different levels of automation. Currently we lack understanding and knowledge on the nature of these interactions and their resulting impacts on traffic flow and traffic safety . There is also a lack of knowledge on how these interactions are affected by the surrounding environment and conditions, such as the physical and digital infrastructure, and penetration levels of automated vehicles. This is what we will investigate in this project. What are the main project objectives? This project will have three main objectives: Create knowledge and in-depth understanding of the interactions between human driven vehicles and automated vehicles at different penetration rates, and in different road environments; Develop mathematical models for the interaction behaviours of human driven vehicles and automated vehicles and implement them in a microscopic traffic simulation platform; Assess the implications of different road environment conditions (physical and digital infrastructure), penetration rates of automation in mixed traffic, and connectivity on traffic flow efficiency and safety. What is our approach? In this project we will develop a hybrid approach for creating a mixed traffic environment. We will merge the strengths of empirical data collected from field tests using real automated vehicles, with the strength of interactive driving simulators for the purpose of studying human drivers’ behaviour and the role of human factor, and the power of enhanced simulation platform for evaluating the implications of mixed traffic on traffic flow and safety. Tackling such a complex and multidisciplinary problem requires close collaboration among vehicle manufacturers, road operators and contractors, academia and knowledge institutes. How this will be achieved? The project will be composed of three main work packages: WP-A. Human drivers’ behaviour and modelling in mixed traffic This work package will create knowledge on human behavioural adaptation in mixed traffic, and will develop mathematical models for the lateral and longitudinal behaviour while accounting for the existence or lack of connectivity (V2I and V2V) and different penetration rates of automation. WP-B. Automated vehicles’ modelling & Operational Design Domain (ODD) This work package will identify the hotspots for vehicles at different automation levels and different types of roads using both field tests and simulation, and develop accurate and reliable models and algorithms for hotspots’ features extraction, recognition and prediction algorithms. Solutions (vehicle or/and infrastructure based) for the identified hotspots will be proposed to enlarge the ODD and define the minimal infrastructure design requirements. WP-C. Implications of (connected/ unconnected) automated driving in mixed traffic on the traffic flow efficiency and traffic safety This work package will develop a tool for assessing the implications of mixed traditional and automated vehicles, at different penetration rates, on traffic efficiency and traffic safety by implementing the developed models in WP-B in a simulation platform. Following this, recommendations with respect to the design of roads for mixed traffic, and the digital infrastructure requirements will be proposed. Open menu Home Project info Research Team members Publications Partners Research Facilities News & upcoming events Contact

Research

WP-A Human drivers’ behaviour and modelling in mixed traffic In WP-A we will investigate how the emergence of AVs and connectivity might change the way human drivers behave in traffic. Traffic flow efficiency and safety are the consequences and result of the interactions between vehicles. We lack proper understanding of how these interactions will change when AVs are introduced, and how human drivers adapt their behaviour when interacting with AVs on such demanding road sections. Behavioural adaptation, is an important human factor that will affect the dynamics of mixed traffic. The two main research objectives of WP-A are: RO-A1: To understand human drivers’ behavioural adaptation when interacting with AVs, and to develop a behavioural theory and mathematical models for these interactions; RO-A2: To investigate the implications of CAVs penetration rate on drivers’ behavioural adaptation. WP-B Automated vehicles Operational Design Domain (ODD) In WP-B we will develop algorithms and models which expands AVs Operational Design Domain (ODD). To deal with infrastructure peculiarities and complex traffic interactions safely and efficiently we need to increase AVs capabilities by understanding how to expand the ODD. The interactions in mixed traffic are dependent on AVs’ capabilities and limitations, i.e. the ODD. Among the main determinants of the ODD are two types of interactions: first, the interaction of AVs with the infrastructure; and second, the interactions of AVs with other vehicles. The two main research objectives of WP-B are: RO-B1: To develop a methodology for peculiarities identification on different roads and traffic conditions, and to develop accurate and reliable algorithms for peculiarities features’ extraction, recognition and prediction using data driven approach; RO-B2: To examine and evaluate the implications of different driving strategies and driving styles of AVs on human-drivers’ behaviour of nearby vehicles. WP-C Implications of mixed traffic on traffic efficiency and safety In WP-C we will implement the new developed behavioural models in WP-A and WP-B in existing open source simulation platform and assess the implications of mixed traffic on traffic flow efficiency and safety. Previous studies have already used microscopic simulation tools to assess the effect of the longitudinal control task of automation, i.e. ACC (Adaptive Cruise Control) and cooperative ACC (CACC) systems with V2V communications on traffic flow efficiency and stability, as well as in mixed traffic. However, these studies reached widely varying results because of different assumptions about the behaviour of human drivers and automated systems. While using simulation is a reasonable compromise in this circumstance, there is a high risk of oversimplification because an important component, human behaviour adaptation when interacting with AVs, is not accounted for. Therefore, we will investigate the importance of this assumption and its impact on the simulation results. This is a prerequisite to have a reliable simulation tool for mixed traffic. The two main research objectives of WP-C are: RO-C1: Implementing the new knowledge on humans’ behavioural adaptation when interacting with AVs, and AVs behavioural models in an existing open source simulation platform; RO-C2: Assessing the implications of different scenarios on traffic flow efficiency and safety, and consequently propose recommendations regarding the infrastructure (physical and digital) requirements. Open menu Home Project info Research Team members Publications Partners Research Facilities News & upcoming events Contact

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Project info

What this project is about? Vehicle manufacturers and the automotive industry are investing huge efforts and resources in realizing the vision of fully automated vehicles. However, the deployment of these vehicles in traffic will be gradual. This will result in a long transition period, in which vehicles with various levels of automation and traditional vehicles co-existing, resulting in mixed traffic. As a consequence, new types of interactions will emerge between vehicles at different levels of automation. Currently we lack understanding and knowledge on the nature of these interactions and their resulting impacts on traffic flow and traffic safety . There is also a lack of knowledge on how these interactions are affected by the surrounding environment and conditions, such as the physical and digital infrastructure, and penetration levels of automated vehicles. This is what we will investigate in this project. What are the main project objectives? This project will have three main objectives: Create knowledge and in-depth understanding of the interactions between human driven vehicles and automated vehicles at different penetration rates, and in different road environments; Develop mathematical models for the interaction behaviours of human driven vehicles and automated vehicles and implement them in a microscopic traffic simulation platform; Assess the implications of different road environment conditions (physical and digital infrastructure), penetration rates of automation in mixed traffic, and connectivity on traffic flow efficiency and safety. What is our approach? In this project we will develop a hybrid approach for creating a mixed traffic environment. We will merge the strengths of empirical data collected from field tests using real automated vehicles, with the strength of interactive driving simulators for the purpose of studying human drivers’ behaviour and the role of human factor, and the power of enhanced simulation platform for evaluating the implications of mixed traffic on traffic flow and safety. Tackling such a complex and multidisciplinary problem requires close collaboration among vehicle manufacturers, road operators and contractors, academia and knowledge institutes. How this will be achieved? The project will be composed of three main work packages: WP-A. Human drivers’ behaviour and modelling in mixed traffic This work package will create knowledge on human behavioural adaptation in mixed traffic, and will develop mathematical models for the lateral and longitudinal behaviour while accounting for the existence or lack of connectivity (V2I and V2V) and different penetration rates of automation. WP-B. Automated vehicles’ modelling & Operational Design Domain (ODD) This work package will identify the hotspots for vehicles at different automation levels and different types of roads using both field tests and simulation, and develop accurate and reliable models and algorithms for hotspots’ features extraction, recognition and prediction algorithms. Solutions (vehicle or/and infrastructure based) for the identified hotspots will be proposed to enlarge the ODD and define the minimal infrastructure design requirements. WP-C. Implications of (connected/ unconnected) automated driving in mixed traffic on the traffic flow efficiency and traffic safety This work package will develop a tool for assessing the implications of mixed traditional and automated vehicles, at different penetration rates, on traffic efficiency and traffic safety by implementing the developed models in WP-B in a simulation platform. Following this, recommendations with respect to the design of roads for mixed traffic, and the digital infrastructure requirements will be proposed. Open menu Home Project info Research Team members Publications Partners Research Facilities News & upcoming events Contact

Research

WP-A Human drivers’ behaviour and modelling in mixed traffic In WP-A we will investigate how the emergence of AVs and connectivity might change the way human drivers behave in traffic. Traffic flow efficiency and safety are the consequences and result of the interactions between vehicles. We lack proper understanding of how these interactions will change when AVs are introduced, and how human drivers adapt their behaviour when interacting with AVs on such demanding road sections. Behavioural adaptation, is an important human factor that will affect the dynamics of mixed traffic. The two main research objectives of WP-A are: RO-A1: To understand human drivers’ behavioural adaptation when interacting with AVs, and to develop a behavioural theory and mathematical models for these interactions; RO-A2: To investigate the implications of CAVs penetration rate on drivers’ behavioural adaptation. WP-B Automated vehicles Operational Design Domain (ODD) In WP-B we will develop algorithms and models which expands AVs Operational Design Domain (ODD). To deal with infrastructure peculiarities and complex traffic interactions safely and efficiently we need to increase AVs capabilities by understanding how to expand the ODD. The interactions in mixed traffic are dependent on AVs’ capabilities and limitations, i.e. the ODD. Among the main determinants of the ODD are two types of interactions: first, the interaction of AVs with the infrastructure; and second, the interactions of AVs with other vehicles. The two main research objectives of WP-B are: RO-B1: To develop a methodology for peculiarities identification on different roads and traffic conditions, and to develop accurate and reliable algorithms for peculiarities features’ extraction, recognition and prediction using data driven approach; RO-B2: To examine and evaluate the implications of different driving strategies and driving styles of AVs on human-drivers’ behaviour of nearby vehicles. WP-C Implications of mixed traffic on traffic efficiency and safety In WP-C we will implement the new developed behavioural models in WP-A and WP-B in existing open source simulation platform and assess the implications of mixed traffic on traffic flow efficiency and safety. Previous studies have already used microscopic simulation tools to assess the effect of the longitudinal control task of automation, i.e. ACC (Adaptive Cruise Control) and cooperative ACC (CACC) systems with V2V communications on traffic flow efficiency and stability, as well as in mixed traffic. However, these studies reached widely varying results because of different assumptions about the behaviour of human drivers and automated systems. While using simulation is a reasonable compromise in this circumstance, there is a high risk of oversimplification because an important component, human behaviour adaptation when interacting with AVs, is not accounted for. Therefore, we will investigate the importance of this assumption and its impact on the simulation results. This is a prerequisite to have a reliable simulation tool for mixed traffic. The two main research objectives of WP-C are: RO-C1: Implementing the new knowledge on humans’ behavioural adaptation when interacting with AVs, and AVs behavioural models in an existing open source simulation platform; RO-C2: Assessing the implications of different scenarios on traffic flow efficiency and safety, and consequently propose recommendations regarding the infrastructure (physical and digital) requirements. Open menu Home Project info Research Team members Publications Partners Research Facilities News & upcoming events Contact
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Students Amos Yusuf, Mick Dam & Bas Brouwer winners of Mekel Prize 2024

Master students Amos Yusuf, from the ME faculty (Mick Dam, from the EEMCS faculty and graduate Bas Brouwer have won the Mekel Prize 2024 for the best extra scientific activity at TU Delft: the development of an initiative that brings master students into the classroom teaching sciences to the younger generations. The prize was ceremonially awarded by prof Tim van den Hagen on 13 November after the Van Hasselt Lecture at the Prinsenhof, Delft. They received a statue of Professor Jan Mekel and 1.500,- to spend on their project. Insights into climate change are being openly doubted. Funding for important educational efforts and research are being withdrawn. Short clips – so called “reels” – on Youtube and TikTok threaten to simplify complex political and social problems. AI fakes befuddle what is true and what is not. The voices of science that contribute to those discussion with modesty, careful argument and scepticism, are drowned in noise. This poses a threat for universities like TU Delft, who strive to increase student numbers, who benefit from diverse student populations and aim to pass on their knowledge and scientific virtues to the next generation. It is, therefore, alarming that student enrolments to Bachelor and Master Programs at TU Delft have declined in the past year. Students in front of the class The project is aimed to make the sciences more appealing to the next generation. They have identified the problem that students tend miss out on the opportunity of entering a higher education trajectory in the Beta sciences – because they have a wrong picture of such education. In their mind, they depict it as boring and dry. In his pilot lecture at the Stanislas VMBO in Delft, Amos Yusuf has successfully challenged this image. He shared his enthusiasm for the field of robotics and presented himself as a positive role model to the pupils. And in return the excitement of the high school students is palpable in the videos and pictures from the day. The spark of science fills their eyes. Bas Brouwer Mick Dam are the founders of NUVO – the platform that facilitates the engagement of Master Students in high school education in Delft Their efforts offer TU Delft Master Students a valuable learning moment: By sharing insights from their fields with pupils at high school in an educational setting, our students can find identify their own misunderstandings of their subject, learn to speak in front of non-scientific audiences and peak into education as a work field they themselves might not have considered. An extraordinary commitment According to the Mekel jury, the project scored well on all the criteria (risk mitigation, inclusiveness, transparency and societal relevance). However, it was the extraordinary commitment of Amos who was fully immersed during his Master Project and the efforts of Brouwer and Dam that brought together teaching and research which is integral to academic culture that made the project stand out. About the Mekel Prize The Mekel Prize will be awarded to the most socially responsible research project or extra-scientific activity (e.g. founding of an NGO or organization, an initiative or realization of an event or other impactful project) by an employee or group of employees of TU Delft – projects that showcase in an outstanding fashion that they have been committed from the beginning to relevant moral and societal values and have been aware of and tried to mitigate as much as possible in innovative ways the risks involved in their research. The award recognizes such efforts and wants to encourage the responsible development of science and technology at TU Delft in the future. For furthermore information About the project: https://www.de-nuvo.nl/video-robotica-pilot/ About the Mekel Prize: https://www.tudelft.nl/en/tpm/our-faculty/departments/values-technology-and-innovation/sections/ethics-philosophy-of-technology/mekel-prize

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