Agent-based simulation of city-wide autonomous ride-pooling and the impact on traffic noise. (January 2021)

• Record Type: Journal Article
• Authors: Zwick, Felix; Kuehnel, Nico; Moeckel, Rolf; Axhausen, Kay W.
• Is Part Of: Transportation research. Volume 90(2021)
• Publication Date: 2021-01
• Subjects: Ride-sharing -- Pooled on-demand mobility -- MATSim -- Traffic noise -- Noise model -- Shared autonomous vehicles -- Emerging mobility; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2020.102673
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: 2% of current car fleet is necessary to transport all car trips. Vehicle kilometers travelled are reduced by up to 54% with ride-pooling. Stop-based on-demand systems facilitate reductions of noise exposure. Door-to-door systems may increase traffic and noise in residential areas. Abstract: Pooled on-demand services promise to provide a convenient mobility experience and increase efficiency of road transport. We apply an established ride-pooling algorithm within the simulation framework MATSim to an autonomous fleet serving almost 2 million requests in Munich. Two mode choice scenarios are implemented, one substituting all car trips by ride-pooling, another one with free mode choice. For both scenarios we compare a stop-based and a door-to-door service in terms of system efficiency and noise imissions, applying an updated noise prediction model in MATSim. The results contribute to the systematic analysis of ride-pooling and show the effects of the proposed policies and service designs, which are essential for an efficient system with low noise exposure. Replacing all car trips by a stop-based ride-pooling system leads to a drastic noise reduction in residential areas whereas door-to-door systems may even increase noise exposure due to additional pick-up/drop-off rides and detours.