Preparing Urban Curbside for Increasing Mobility-on-Demand Using Data-Driven Agent-Based Simulation: Case Study of City of Gainesville, Florida
Publication: Journal of Management in Engineering
Volume 38, Issue 3
Abstract
Cities in many countries are witnessing an era of transformative innovations in vehicular technologies and mobility-on-demand (MoD) services in the context of global initiatives of smart and connected cities. However, advances in the built environment where vehicles operate have not maintained the same pace. The new MoD especially burdens curb environments in urban cores due to competition for spaces for pick-ups and drop-offs (PUDO). These uncoordinated and diverse uses without data-driven management have led to increased safety and sustainability issues. This research intends to address the increasing curbside uses of PUDO activities due to MoD services and proposes a data-driven agent-based simulation approach to plan designated PUDO zones in limited public curbside spaces. A case study was conducted for five street blocks in urban cores of the City of Gainesville, Florida, United States, based on longitudinal parking transaction and violation records, place visitation data, and geospatial data of parking assets. The results show that temporary PUDO zones should be designated at all investigated blocks during peak hours even when the MoD market penetration rate is low (i.e., 10%), which helps mitigate the occurrences of competing use events, while permanent PUDO zones should be designated for the two busiest blocks when the MoD market penetration rates increase to 30% or 50%. Sensitivity analyses suggest that the designated PUDO zones can mitigate curbside stresses more effectively when regulating MoD users’ PUDO dwell time (e.g., within one minute). This research aims to contribute to data-driven public asset managerial decision-making and strategies in smart cities and benefits more accessible and sustainable living environments in urban cores.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Parking transaction data, violation data, and POI visitation frequency data used during the study were provided by a third party. Direct requests for these materials may be made to the provider as indicated in the Acknowledgments. Matlab and Python code generated or used during the study are available from the corresponding author upon reasonable request.
Acknowledgments
This material is based upon work supported by the National Science Foundation under Grant No. 2124858, the University of Florida’s faculty start-up funds, and the Graduate School Fellowship Award. The authors are grateful for the parking data shared by the City of Gainesville and the POIs’ visitation data shared by SafeGraph data. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation and the University of Florida.
References
Aftab, K., P. Kulkarni, I. Shergold, M. Jones, M. Dogramadzi, P. Carnelli, and M. Sooriyabandara. 2020. “Reducing parking space search time and environmental impacts: A technology driven smart parking case study.” IEEE Technol. Soc. Mag. 39 (3): 62–75. https://doi.org/10.1109/MTS.2020.3012329.
APA (American Planning Association). 2019. Curb control. Chicago, IL: APA.
Bauer, G. S., J. B. Greenblatt, and B. F. Gerke. 2018. “Cost, energy, and environmental impact of automated electric taxi fleets in Manhattan.” Environ. Sci. Technol. 52 (8): 4920–4928. https://doi.org/10.1021/acs.est.7b04732.
Bosa, N. 2019. “Scooter study at UF to look at danger, pollution.” Accessed February 5, 2021. https://www.gainesville.com/news/20191017/scooter-study-at-uf-to-look-at-danger-pollution.
Butrina, P., S. Le Vine, A. Henao, J. Sperling, and S. E. Young. 2020. “Municipal adaptation to changing curbside demands: Exploratory findings from semi-structured interviews with ten US cities.” Transp. Policy 92 (Jun): 1–7. https://doi.org/10.1016/j.tranpol.2020.03.005.
Chase, R. 2017. “Shared mobility principles for livable cities.” Accessed February 5, 2021. https://www.sharedmobilityprinciples.org/.
City of Gainesville. n.d. “Gainesville Bike-ped.” Accessed February 5, 2021. http://gnvbikeped.com/.
City of Gainesville. 2020. “Strategic plan: 2020–2025—2035/Mayor and City Commission/Gainesville, Florida.” Accessed February 5, 2021. https://www.cityofgainesville.org/Portals/0/splan/strategic%20plan/Gainesville%20200505%20Strategic%20Plan%202020-2025-2035%20Combined.pdf.
Davidson, P., and A. Spinoulas. 2016. “Driving alone versus riding together—How shared autonomous vehicles can change the way we drive.” Road Transp. Res. 25 (3): 51–66.
de Castro, F. 2021. “fitmethis.” Accessed April 4, 2021. https://www.mathworks.com/matlabcentral/fileexchange/40167-fitmethis.
Du, J., and M. El-Gafy. 2015. “Using agent-based modeling to investigate goal incongruence issues in proposal development: Case study of an EPC project.” J. Manage. Eng. 31 (6): 05014025. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000343.
Dumbaugh, E., and W. Li. 2010. “Designing for the safety of pedestrians, cyclists, and motorists in urban environments.” J. Am. Plann. Assoc. 77 (1): 69–88. https://doi.org/10.1080/01944363.2011.536101.
Fagnant, D. J., and K. M. Kockelman. 2014. “The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios.” Transp. Res. Part C Emerging Technol. 40 (Mar): 1–13. https://doi.org/10.1016/j.trc.2013.12.001.
Francisco, A., N. Mohammadi, and J. E. Taylor. 2020. “Smart city digital twin-enabled energy management: Toward real-time urban building energy benchmarking.” J. Manage. Eng. 36 (2): 04019045. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000741.
Goodchild, A., D. MacKenzie, A. Ranjbari, J. Machado, and G. Dalla Chiara. 2019. Curb allocation change project. Seattle: Univ. of Washington.
Greenblatt, J. B., and S. Shaheen. 2015. “Automated vehicles, on-demand mobility, and environmental impacts.” Curr. Sustainable/Renewable Energy Rep. 2 (3): 74–81. https://doi.org/10.1007/s40518-015-0038-5.
Inan, M. O., E. Inci, and C. R. Lindsey. 2019. “Spillover parking.” Transp. Res. Part B Methodol. 125: 197–228. https://doi.org/10.1016/j.trb.2019.05.012.
IPMI (International Parking & Mobility Institute). 2018. “Emerging trends in parking.” Accessed April 5, 2021. https://www.parking-mobility.org/.
ITF (International Transport Forum). 2018. “The shared-use city: Managing the curb.” Accessed April 5, 2021. https://www.itf-oecd.org/shared-use-city-managing-curb-0.
Kondor, D., P. Santi, D. T. Le, X. Zhang, A. Millard-Ball, and C. Ratti. 2020. “Addressing the ‘minimum parking’ problem for on-demand mobility.” Sci. Rep. 10 (1): 1–10. https://doi.org/10.1038/s41598-020-71867-1.
Marsden, G., I. Docherty, and R. Dowling. 2020. “Parking futures: Curbside management in the era of ‘new mobility’ services in British and Australian cities.” Land Use Policy 91 (Feb): 104012. https://doi.org/10.1016/j.landusepol.2019.05.031.
Mckinsey Center for Future Mobility. n.d. “Shared mobility.” Accessed April 5, 2021. https://www.mckinsey.com/features/mckinsey-center-for-future-mobility/overview/shared-mobility#.
NACTO (National Association of City Transportation Officials). 2013. “Active design. Shaping the sidewalk experience.” Accessed April 11, 2021. https://nacto.org/docs/usdg/active_design_shaping_the_sidewalk_experience_nycdot.pdf.
Oh, S., R. Seshadri, C. L. Azevedo, N. Kumar, K. Basak, and M. Ben-Akiva. 2020. “Assessing the impacts of automated mobility-on-demand through agent-based simulation: A study of Singapore.” Transp. Res. Part A Policy Pract. 138 (Aug): 367–388. https://doi.org/10.1016/j.tra.2020.06.004.
Pierce, G., and D. Shoup. 2013. “Getting the prices right: An evaluation of pricing parking by demand in San Francisco.” J. Am. Plann. Assoc. 79 (1): 67–81. https://doi.org/10.1080/01944363.2013.787307.
Ranjbari, A., J. Luis Machado-León, G. Dalla Chiara, D. MacKenzie, and A. Goodchild. 2020. “Testing curbside management strategies to mitigate the impacts of ridesourcing services on traffic.” Transp. Res. Rec. 2675 (2): 219–232. https://doi.org/10.1177/0361198120957314.
Roe, M., and C. Toocheck. 2017. Curb appeal: Curbside management strategies for improving transit reliability, 1–12. New York: National Association of City Transportation Officials.
Rosenblum, J., A. W. Hudson, and E. Ben-Joseph. 2020. “Parking futures: An international review of trends and speculation.” Land Use Policy 91 (Feb): 104054. https://doi.org/10.1016/j.landusepol.2019.104054.
SafeGraph. 2020. “Determining point-of-interest visits from location data: A technical guide to visit attribution.” Accessed April 5, 2021. https://www.safegraph.com/visit-attribution-whitepaper.
Schaller, B. 2019. “Making the most of the curb.” Accessed April 5, 2021. http://www.schallerconsult.com/rideservices/makingmostofcurb.pdf.
Seattle.gov. n.d. “Flex zone/Curb use priorities in Seattle.” Accessed April 5, 2021. https://www.seattle.gov/transportation/projects-and-programs/programs/parking-program/parking-regulations/flex-zone/curb-use-priorities-in-seattle.
SFMTA (San Francisco Municipal Transportation Agency). 2020. “Curb management strategy.” Accessed April 5, 2021. https://www.sfmta.com/sites/default/files/reports-and-documents/2020/02/curb_management_strategy_report.pdf.
Swarup, S. 2021. “Improved travel demand modeling with synthetic populations.” In Vol. 12316 of Proc. 21st Int. Workshop, Multi-Agent-Based Simulation 21 MABS 2020. Taylor & Francis. Auckland, New Zealand, May 10, 2020, Revised Selected Papers, 94. New York: Springer.
University of Florida. 2018. “Transportation & parking strategic plan.” Accessed April 5, 2021. https://taps.ufl.edu/wp-content/uploads/2020/11/TransportationStrategicPlan.pdf.
USDOT. 2018. Preparing for the future of transportation: Automated vehicles 3.0 (AV 3.0). Washington, DC: USDOT.
Wadud, Z., D. MacKenzie, and P. Leiby. 2016. “Help or hindrance? The travel, energy, and carbon impacts of highly automated vehicles.” Transp. Res. Part A Policy Pract. 86 (Apr): 1–18. https://doi.org/10.1016/j.tra.2015.12.001.
Wang, B., S. A. Ordoñez Medina, and P. J. Fourie. 2018. “Operator and user perspectives on fleet mix, parking strategy and drop-off bay size for autonomous transit on demand.” Arbeitsberichte Verkehrs-und Raumplanung 1370. https://doi.org/10.3929/ethz-b-000283489.
Wang, C., J. Delport, and Y. Wang. 2019. “Lateral motion prediction of on-road preceding vehicles: A data-driven approach.” Sensors 19 (9): 2111. https://doi.org/10.3390/s19092111.
Wang, Y., J. E. Taylor, and M. J. Garvin. 2020. “Measuring resilience of human–spatial systems to disasters: Framework combining spatial-network analysis and fisher information.” J. Manage. Eng. 36 (4): 04020019. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000782.
Weinberger, R. R., A. Millard-Ball, and R. C. Hampshire. 2020. “Parking search caused congestion: Where’s all the fuss?” Transp. Res. Part C Emerging Technol. 120 (Nov): 102781. https://doi.org/10.1016/j.trc.2020.102781.
Winter, K., O. Cats, K. Martens, and B. van Arem. 2020. “Relocating shared automated vehicles under parking constraints: Assessing the impact of different strategies for on-street parking.” Transportation 48 (4): 1931–1965. https://doi.org/10.1007/s11116-020-10116-w.
Wu, P., F. Chu, N. Saidani, H. Chen, and W. Zhou. 2020. “IoT-based location and quality decision-making in emerging shared parking facilities with competition.” Decis. Support Syst. 134 (Jul): 113301. https://doi.org/10.1016/j.dss.2020.113301.
Ye, Q., S. M. Stebbins, Y. Feng, E. Candela, M. Stettler, and P. Angeloudis. 2020. “Intelligent management of on-street parking provision for the autonomous vehicles era.” In Proc., 2020 IEEE 23rd Int. Conf. on Intelligent Transport System (ITSC), 1–7. New York: IEEE.
Young, S., and A. Henao. 2020. Cities topology—Curbs and parking. Golden, CO: National Renewable Energy Lab.
Zhang, K., and S. Batterman. 2013. “Air pollution and health risks due to vehicle traffic.” Sci. Total Environ. 450 (Apr): 307–316. https://doi.org/10.1016/j.scitotenv.2013.01.074.
Zhang, M., H. Chai, J. Song, M. Jaller, and C. Rodier. 2020. The impacts of automated vehicles on center city parking demand. Davis: Univ. of California.
Zhang, W., S. Guhathakurta, J. Fang, and G. Zhang. 2015. “Exploring the impact of shared autonomous vehicles on urban parking demand: An agent-based simulation approach.” Sustainable Cities Soc. 19 (Dec): 34–45. https://doi.org/10.1016/j.scs.2015.07.006.
Zhang, W., and K. Wang. 2020. “Parking futures: Shared automated vehicles and parking demand reduction trajectories in Atlanta.” Land Use Policy 91 (Feb): 103963. https://doi.org/10.1016/j.landusepol.2019.04.024.
Zhao, D., N. Thakur, and J. Chen. 2020. “Optimal design of energy storage system to buffer charging infrastructure in smart cities.” J. Manage. Eng. 36 (2): 04019048. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000742.
Zuo, T., H. Wei, N. Chen, and C. Zhang. 2020. “First-and-last mile solution via bicycling to improving transit accessibility and advancing transportation equity.” Cities 99 (Apr): 102614. https://doi.org/10.1016/j.cities.2020.102614.
Information & Authors
Information
Published In
Journal of Management in Engineering
Volume 38 • Issue 3 • May 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Apr 13, 2021
Accepted: Nov 23, 2021
Published online: Jan 28, 2022
Published in print: May 1, 2022
Discussion open until: Jun 28, 2022
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
Cited by
- Chen Xia, Yuqing Hu, Jianli Chen, Haiyan Hao, A Spatial-Temporal Community Vulnerability Assessment Framework Based on Human Mobility Trajectory Simulation, Computing in Civil Engineering 2023, 10.1061/9780784485248.005, (36-43), (2024).
- Samar M. Idrees, Mohamed S. Eid, Rita Awwad, Impact of Altering the Bid Selection Method to Below-Average Method: An Agent-Based Modeling Approach, Journal of Management in Engineering, 10.1061/JMENEA.MEENG-5084, 39, 3, (2023).
- Abdelaziz Tami, Sofiane Boukli Hacene, A Review of a Smart Roadside and On-Street Parking System, International Journal of Organizational and Collective Intelligence, 10.4018/IJOCI.313599, 12, 1, (1-14), (2022).