Skip to main content

Tracking a system of shared autonomous vehicles across the Austin, Texas network using agent-based simulation


This study provides a large-scale micro-simulation of transportation patterns in a metropolitan area when relying on a system of shared autonomous vehicles (SAVs). The six-county region of Austin, Texas is used for its land development patterns, demographics, networks, and trip tables. The agent-based MATSim toolkit allows modelers to track individual travelers and individual vehicles, with great temporal and spatial detail. MATSim’s algorithms help improve individual travel plans (by changing tour and trip start times, destinations, modes, and routes). Here, the SAV mode requests were simulated through a stochastic process for four possible fare levels: $0.50, $0.75, $1, and $1.25 per trip-mile. These fares resulted in mode splits of 50.9, 12.9, 10.5, and 9.2% of the region’s person-trips, respectively. Mode choice results show longer-distance travelers preferring SAVs to private, human-driven vehicles (HVs)—thanks to the reduced burden of SAV travel (since one does not have to drive the vehicle). For travelers whose households do not own an HV, SAVs (rather than transit, walking and biking) appear preferable for trips under 10 miles, which is the majority of those travelers’ trip-making. It may be difficult for traditional transit services and operators to survive once SAVs become available in regions like Austin, where dedicated rail lines and bus lanes are few. Simulation of SAV fleet operations suggest that higher fare rates allow for greater vehicle replacement (ranging from 5.6 to 7.7 HVs per SAV, assuming that the average SAV serves 17–20 person-trips per day); when fares rise, travel demands shift away from longer trip distances. Empty vehicle miles traveled by the fleet of SAVs ranged from 7.8 to 14.2%, across the scenarios in this study. Implications of mobility and sustainability benefits of SAVs are also discussed in the paper.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8


Download references


The authors would like to thank Texas Department of Transportation (TxDOT) for financially supporting this research (under research project 6838, “Bringing Smart Transport to Texans: Ensuring the Benefits of a Connected and Autonomous Transport System in Texas”). The authors are grateful to the developers of MATSim for their consistent efforts in improving this toolkit (available at Special thanks to Scott Schauer-West, for his constructive comments, edits, and administrative support.

Author information

Authors and Affiliations



JL Defining the Topic, Setting-up the Method, Literature Search and Review, Data Preparation, Performing Simulations and Analysis, and Manuscript Writing; KK Defining the Topic, Setting-up the Method, Literature Search and Review, Manuscript Writing and Editing, and Research Outreach/Correspondence; and PB & FC Simulation Design and Manuscript Editing.

Corresponding author

Correspondence to Kara M. Kockelman.

Additional information

Proceedings of the 96th Annual Meeting of the Transportation Research Board & under review for publication in Transportation, August 2017.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, J., Kockelman, K.M., Boesch, P.M. et al. Tracking a system of shared autonomous vehicles across the Austin, Texas network using agent-based simulation. Transportation 44, 1261–1278 (2017).

Download citation

  • Published:

  • Issue Date:

  • DOI: