Agent-based simulation to model mobility and electric cars in urban road networks

Electrifying road transport is seen as one of the key components in decreasing the carbon footprint of the society. Recent developments in electric drivetrain and battery technology have helped to design vehicles with ranges that make them independent of public charging infrastructure during most sub-urban and commuting trips. Once long-haul trips are planned, however, these vehicles require a dense network of charging infrastructure. This thesis presents the importance and use of agent-based simulation framework for modelling the mobility, understanding the agent behaviour at micro level along with understanding the road network and mobility pattern. This is possible with the help of a simulation environment (matsim) which build a consistent model to work. This model helps to extend mobility using electric cars in urban area and understand the requirements needed electrify the whole transport system only related to personal cars. In order to achieve our objective, we have gone through several processes, staring from modelling realistic mobility patterns and then using mobility information to deploy and model the road network with electric cars only. In the first stage we have worked to build a reliable road network for vehicles along with people demand to move from one place to other, according to available survey data. After building a basic model we have calibrated it for understanding the output observes as road network performance. Before using the model, we have checked this agent-based simulation framework several times by calibrating different parameters. This calibrated model is then used to explore future mobility scenarios by switching all cars as electric and understand the requirement and need to deploy such a system in urban area. This is done by extending the matsim framework and bind this with a specific electric module.