AbstractAutonomous mobility is increasingly entering commercial urban transport services through robotaxi fleets, while its impacts on urban transport and energy sustainability remain uncertain. Here, using more than 4 million order records from human-driven taxis and robotaxis in Wuhan, we examine how fully driverless ride-hailing interacts with existing mobility systems and shapes operational energy demand. Robotaxi activity spatially overlaps with human-driven taxi demand, indicating potential competition within on-demand mobility markets. Compared with human-driven taxis, robotaxi trips exhibit lower station-to-station ratios within metro- and bus-station catchments (46.9% and 61.6%, respectively), suggesting a more complementary relationship to public transit. Robotaxi operations concentrate on less complex street networks, and incorporating network complexity into the demand model improves predictive performance. Under an upper-bound dispatch and ride-sharing optimization scenario, the required fleet size could be reduced by 62.5% and daily energy consumption by 44.8%. These empirical findings provide support for aligning robotaxi deployment with urban sustainability goals.This is a preview of subscription content, access via your institutionAccess options Access through your institutionAccess Nature and 54 other Nature Portfolio journalsGet Nature+, our best-value online-access subscription27,99 € / 30 dayscancel any timeLearn moreSubscribe to this journalReceive 12 digital issues and online access to articles118,99 € per yearonly 9,92 € per issueLearn moreBuy this articlePurchase on SpringerLinkInstant access to the full article PDF.39,95 €Prices may be subject to local taxes which are calculated during checkoutFig. 1: Spatiotemporal characteristics of robotaxi services in Wuhan.Fig. 2: Comparative operating profiles, spatial interactions and energy implications of robotaxi deployment in Wuhan.Fig. 3: Demand-model performance and hourly fleet-state composition of robotaxi operations.Fig. 4: Road-network complexity, fleet optimization and system-level impacts of robotaxi operations.Fig. 5: Conceptual synthesis of Wuhan-based operational findings and deployment implications.Data availabilityRepresentative sample datasets for the robotaxi and HV analyses are available via GitHub at https://github.com/Tlab-seu-code/Urban_Robotaxi_Analysis-. The full robotaxi operational records and HV trajectory records cannot be made publicly available because they were obtained under third-party data-use agreements and contain privacy-sensitive mobility information. Qualified researchers may request access by contacting the corresponding author. Approved access requires execution of a data-use agreement and is restricted to non-commercial research. Other datasets used in this study, including the POI dataset and the night-time light dataset, are available via GitHub at https://github.com/Tlab-seu-code/Urban_Robotaxi_Analysis-/releases/tag/v1.0. The full intermediate and derived datasets are available from the corresponding author upon reasonable request. Source data are provided with this paper.Code availabilityThe analysis, simulation and optimization code of this work is available via GitHub at https://github.com/Tlab-seu-code/Urban_Robotaxi_Analysis-.ReferencesXia, H., Liu, R., Li, L. & Zhang, Y. 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The work of the other authors, including Q.C., Y.L. and X.L., was not funded by any specific grant.Author informationAuthors and AffiliationsJiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing, ChinaZelin Wang, Chengqi Liu, Yunpeng Xin, Yuhao Zhang & Zhiyuan LiuDepartment of Civil and Environmental Engineering, National University of Singapore, Singapore, SingaporeYang ZhangSchool of Instrument Science and Engineering, Southeast University, Wuxi, ChinaKai HuangUniversity of Bristol Business School, University of Bristol, Bristol, UKQixiu ChengDepartment of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI, USAXiaopeng LiSchool of Statistics and Data Science, Southeast University, Nanjing, ChinaYixuan Zhang & Zhiyuan LiuClimate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, AustraliaYanming LiuSchool of Electrical Engineering, Southeast University, Nanjing, ChinaWei JiangAuthorsZelin WangView author publicationsSearch author on:PubMed Google ScholarChengqi LiuView author publicationsSearch author on:PubMed Google ScholarYunpeng XinView author publicationsSearch author on:PubMed Google ScholarYang ZhangView author publicationsSearch author on:PubMed Google ScholarKai HuangView author publicationsSearch author on:PubMed Google ScholarQixiu ChengView author publicationsSearch author on:PubMed Google ScholarYuhao ZhangView author publicationsSearch author on:PubMed Google ScholarXiaopeng LiView author publicationsSearch author on:PubMed Google ScholarYixuan ZhangView author publicationsSearch author on:PubMed Google ScholarYanming LiuView author publicationsSearch author on:PubMed Google ScholarWei JiangView author publicationsSearch author on:PubMed Google ScholarZhiyuan LiuView author publicationsSearch author on:PubMed Google ScholarContributionsZ.W. and Z.L. conceived and designed the study. Analysis was performed by Z.W., C.L., Y.X., Yang Zhang, K.H., Q.C., Yuhao Zhang, Yixuan Zhang and Y.L. Z.L., W.J. and X.L. supervised the study. All authors contributed to methodological discussions and the writing of this paper.Corresponding authorsCorrespondence to Wei Jiang or Zhiyuan Liu.Ethics declarationsCompeting interestsThe authors declare no competing interests.Peer reviewPeer review informationNature Sustainability thanks Marvin Greifenstein, Alexandros Nikitas, Laura Pemberton and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.Additional informationPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary informationSource dataRights and permissionsSpringer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.Reprints and permissionsAbout this article