Automation is expected to gradually arrive in all transport domains, such as passenger cars, urban public and freight transport. Therefore, it is imperative that the Connected and Automated Transport Systems (CATS) impacts are estimated. The LEVITATE project aims to prepare an impact assessment framework enabling policymakers to manage the CATS introduction, culminating with the creation of an online Policy Support Tool (PST). The present research provides a closer examination of the forecasting capabilities of the PST. Three methodologies were utilized: microsimulation, system dynamics and Delphi method and their estimations feeds information to the PST forecasting and backcasting sub-systems. In the forecasting sub-system, the user selects policy intervention, defines CATS factors and the module provides quantified on the expected impacts. In the backcasting sub-system, the user sets impact targets and time-frames and the system provides feedback as to which measures can be used to attain them. To combine interventions, the US FHWA methodology is modified to create combined Impact Modification Factors (cIMFs). The Levitate PST aspires to become the go-to, one-stop-shop tool for the calculation of societal impacts of automation by experts, authorities, stakeholders and any other interested party.
|Tags||impact assessment, statistical modelling, traffic automation|