Citation

Reul J, Grube T, Stolten D. Transp. Res. D Trans. Environ. 2021; 92: e102733.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.trd.2021.102733

PMID

unavailable

Abstract

Urban transportation is in the midst of a two-fold transformation: On the one hand, cities are beginning to acknowledge their climate responsibilities and are seeking to establish environmentally-friendly, sustainable transport systems. On the other hand, new transportation trends, such as shared mobility and autonomous driving, carry the potential to disruptively change conventional practices. In this study, we develop an activity-based transport demand model to quantify the effects of potential influencing factors on urban transportation in a synthetic city. We develop 18 scenarios to investigate urban transportation against the backdrop of mode availability, the deployment of shared mobility services, urban structure and societal change, such as urbanization and an aging population, as well as behavioral shifts in mode choice preferences. With respect to the results, we highlight the derived modal split for a city without private cars but with access to shared autonomous vehicles for all agents: We find a distribution of mode choices of 55% for walking and biking, 40% for public transportation and 5% for shared modes. Given this modal split, the total driven distance, as well as the total number of vehicles in the city, decreases by over 90% against current levels. Thus, an efficient future urban transport system should build upon public transportation for meeting the major share of transport demand, with slow modes for convenient travel across short distances and shared mobility for the intermodal connection of both.

Language: en

Keywords

Activity-based modeling; Shared autonomous vehicles; Shared mobility; Transportation trends; Urban transportation