Print Email Facebook Twitter Integrating human drivers' behavioural rules into microscopic traffic simulation Title Integrating human drivers' behavioural rules into microscopic traffic simulation Author Vonk, Martijn (TU Delft Mechanical, Maritime and Materials Engineering; TU Delft Delft Center for Systems and Control) Contributor Grammatico, S. (mentor) Farah, H. (mentor) Degree granting institution Delft University of Technology Programme Mechanical Engineering | Systems and Control Date 2023-03-03 Abstract Autonomous vehicles (AVs) can solve a lot of problems related to traffic safety, comfort and congestion. While the sensors used by these vehicles are getting cheaper, more accurate, and software is improving, the first completely automated vehicle does not exist yet. When AVs start gradually driving on the roads, there will be a mixed traffic situation consisting of AVs and human driven vehicles. To understand the implications on the traffic performance, this thesis will implement a Model Predictive Controller (MPC) and the behavioural models for AVs into a numerical simulation in SUMO. The MPC can be used to control multiple AVs in larger traffic simulations to analyse the effects of certain penetration rates and traffic densities when changing the AVs driving behaviour. Both the Post-Encroachment Time (PET) and Time To Collision (TTC) will be used for decision making in overtaking and collision avoidance strategies. In this thesis, the MPC which is solving a quadratic programming problem has proven to successfully overtake other vehicles in an on- and off-ramp highway scenario which results in a smaller average travel time for the AVs than for the human drivers. It is shown that the decrease in average travel time for the AVs was not at the cost of the Human Vehicles (HVs). This is done by decreasing the TTC used by the AVs as a headway for longitudinal overtaking behaviour, and the PET used for lateral lane changing behaviour, independently to a minimum of 0.1 seconds to guaranty safety, and measure the average travel times for both HVs and AVs. Multiple simulations using different penetration rates ranging from 0 to 40 percent also show that the decrease in average travel time for the AVs was not at the cost of the HVs. We can conclude that using an MPC integrated together with the behavioural rules of human drivers into numerical simulation can give a good indication of the implications that AVs have on traffic performance. Subject Autonomous VehiclesNumerical SimulationMPCModel predictive controlSUMOHuman driven vehiclesPost Encroachment Time (PET)Time to Collision (TTC)Highway To reference this document use: http://resolver.tudelft.nl/uuid:80febbbb-39c0-41f1-8f2f-4457386e468d Part of collection Student theses Document type master thesis Rights © 2023 Martijn Vonk Files PDF Thesis_Martijn_Vonk.pdf 1.51 MB Close viewer /islandora/object/uuid:80febbbb-39c0-41f1-8f2f-4457386e468d/datastream/OBJ/view