Planning and Operation of Automated Taxi Systems

In recent years, technology development has accelerated the future roll-out of vehicle automation. An automated vehicle (AV), also known as a driverless car and a self-driving car is an advanced type of vehicle that can drive itself on existing roads. A possible area of application for AVs is public transport. The concept of automated taxis (ATs) is supposed to offer a seamless door-to-door service within a city area for all passengers. With automation technology maturing, we may be able to see the situation in which hundreds or even thousands of ATs will be on the road replacing private vehicles accounting for the majority of people’s daily trips. However, little attention has been devoted to the usage of a fleet of ATs and their effect on a real-scale road network. In this thesis, we explore how automated driving can serve mobility and what is the best way to introduce this technology as part of the existing transport networks. This is also the research gap this thesis is going to fill. The objective of this thesis is to contribute to the planning and operational strategies that these AT systems should follow in order to satisfy mobility demand. This thesis uses mathematical optimization to address the above research problems. A mathematical optimization problem consists of maximizing or minimizing a function by systematically selecting some input values within a defined domain. It aims to find the best available values of the objective function and the corresponding values of the problem input. The purpose of this thesis is to provide a tool to support the decision-making processes both for long-term planning strategies and short-term tactical operations when ATs are going to be applied in the urban transport system.