The medium-term impacts of cooperative, connected, and automated mobility on passenger transport

The aim of the LEVITATE project is to prepare a new impact assessment framework to enable policymakers to manage the introduction of connected and automated transport systems, maximise the benefits and utilise the technologies to achieve societal objectives. As part of this work the LEVITATE project seeks to forecast societal level impacts of cooperative, connected, and automated mobility (CCAM). These include impacts on mobility, safety, environment, economy, and society.

This report presents a wide range of medium-term or systemic impacts of CCAM and various policy interventions for managing passenger car transport. The medium-term impacts analysed include congestion, amount of travel, model split using public transport, model split using active travel, shared mobility rate, vehicle utilization rate and vehicle occupancy. Based on discussions with city officials and industry professionals, a list of key interventions, termed sub-use cases (SUC), were selected to be tested through different applicable methods. These include road use pricing, provision of dedicated lanes on urban highways, parking price policies, parking space regulations, automated ride sharing, and green light optimal speed advisory (GLOSA). The methodologies for analysing the impacts of the studied interventions were selected based on their feasibility and adequacy in examining the system level or medium-term impacts. They included mesoscopic simulation, microscopic simulation, system dynamics, and Delphi method. The deployment of CAVs was tested from 0 to 100% with 20% increments under all SUCs. The behaviours of CAVs were defined based on an extensive literature review performed as part of the LEVITATE project. Two types of CAVs were included in the analysis, 1st Generation CAVs and second Generation CAVs, where 2nd generation CAVs were assumed to have improved driving characteristics and enhanced cognitive capabilities, which will lead to shorter time gaps as compared to 1st generation CAVs and human-driven vehicles. [...]