{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T17:51:03Z","timestamp":1766598663595,"version":"build-2065373602"},"reference-count":60,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T00:00:00Z","timestamp":1760054400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52302388"],"award-info":[{"award-number":["52302388"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>Parking shortages and high costs in Chinese central business districts (CBDs) remain major urban challenges. Emerging automated vehicles (AVs) are expected to diversify parking options and mitigate these problems. However, AV users\u2019 parking preferences and their influencing factors within existing urban zoning frameworks remain unclear. This study examines Nanjing as a representative case, proposing six distinct AV parking modes. Using survey data from 4644 responses collected from 1634 potential users, we employed nested logit models and random forest algorithms to analyze parking choice behavior. Results indicate that diversified AV parking modes would significantly reduce CBD parking demand. Users with medium- to long-term needs prefer home-parking, while short-term users favor CBD proximity. Key influencing factors include parking service satisfaction, duration, congestion time, AV punctuality, and individual characteristics, with satisfaction attributes showing the greatest impact across all modes. Comparative analysis reveals that random forest algorithms provide superior predictive accuracy for parking mode importance, while nested logit models better explain causal relationships between choices and influencing factors. This study establishes a dual analytical framework combining interpretability and predictive accuracy for urban AV parking research, providing valuable insights for transportation management and future metropolitan studies.<\/jats:p>","DOI":"10.3390\/systems13100891","type":"journal-article","created":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:50:16Z","timestamp":1760107816000},"page":"891","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Parking Choice Analysis of Automated Vehicle Users: Comparing Nested Logit and Random Forest Approaches"],"prefix":"10.3390","volume":"13","author":[{"given":"Ying","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Transportation, Southeast University, Nanjing 211189, China"}]},{"given":"Chu","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, Nanjing 211189, China"},{"name":"Zhejiang Urban Governance Studies Center, Hangzhou 311121, China"}]},{"given":"He","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Civil Engineering, Fuzhou University, Fuzhou 350108, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2360-3712","authenticated-orcid":false,"given":"Jun","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, Nanjing 211189, China"},{"name":"Zhejiang Urban Governance Studies Center, Hangzhou 311121, China"},{"name":"School of Electronic Information Engineering, Suzhou Polytechnic University, Suzhou 215104, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-4005-1919","authenticated-orcid":false,"given":"Shuhong","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, Nanjing 211189, China"}]},{"given":"Weidong","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, Nanjing 211189, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,10]]},"reference":[{"key":"ref_1","unstructured":"Shen, J. (2024, December 15). Parking Problems: How to Solve High Costs and Limited Availability?. Available online: https:\/\/news.qq.com\/rain\/a\/20210609A003FL00."},{"key":"ref_2","unstructured":"Song, Y. (2024, October 12). Big Data Reveals: Which Areas Face the Worst Parking Challenges?. Available online: https:\/\/auto.cctv.com\/2022\/01\/10\/ARTIzD41fXREQaB9Y7oqAM9v220110.shtml."},{"key":"ref_3","first-page":"44","article-title":"Analysis of Parking Choice Behavior Based on Psychological Perception","volume":"22","author":"Qin","year":"2020","journal-title":"Transp. Sci. Econ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"9004","DOI":"10.1109\/TITS.2023.3271187","article-title":"A Network Traffic Model for the Control of Autonomous Vehicles Acting as Moving Bottlenecks","volume":"24","author":"Li","year":"2023","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"102924","DOI":"10.1016\/j.trc.2020.102924","article-title":"Optimal parking management of connected autonomous vehicles: A control-theoretic approach","volume":"124","author":"Wang","year":"2021","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.tbs.2021.07.007","article-title":"Research on parking app choice behavior based on MNL","volume":"25","author":"Ye","year":"2021","journal-title":"Travel Behav. Soc."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"103853","DOI":"10.1016\/j.trc.2022.103853","article-title":"Curbing cruising-as-substitution-for-parking in automated mobility","volume":"143","author":"Radvand","year":"2022","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"103001","DOI":"10.1016\/j.trc.2021.103001","article-title":"Parking management of automated vehicles in downtown areas","volume":"126","author":"Bahrami","year":"2021","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"102838","DOI":"10.1016\/j.trc.2020.102838","article-title":"Parking infrastructure design for repositioning autonomous vehicles","volume":"120","author":"Levin","year":"2020","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"103318","DOI":"10.1016\/j.trd.2022.103318","article-title":"Willingness-to-relocate: Examining preferences for parking relocation of privately-owned automated vehicles","volume":"108","author":"Jia","year":"2022","journal-title":"Transp. Res. Part D Transp. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"100688","DOI":"10.1016\/j.tbs.2023.100688","article-title":"Adoption of shared autonomous vehicles: Combined effects of the external environment and personal attributes","volume":"34","author":"Si","year":"2024","journal-title":"Travel Behav. Soc."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Zhang, C., Chen, J., Yang, G., and Wang, W. (2024). Can Relocation Influence Human Acceptance of Connected and Automated Vehicles?. Systems, 12.","DOI":"10.3390\/systems12080296"},{"key":"ref_13","unstructured":"Nanjing.gov (2025, October 08). Notice on Issuing the \u201cNanjing Municipal Vehicle Parking Service Fee Management Measures\u201d, Available online: https:\/\/cgj.nanjing.gov.cn\/njscsglj\/202209\/t20220926_3708331.html."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.trc.2020.01.027","article-title":"Automated vehicle acceptance in China: Social influence and initial trust are key determinants","volume":"112","author":"Zhang","year":"2020","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1016\/j.trc.2019.12.009","article-title":"Traffic automation and lane management for communicant, autonomous, and human-driven vehicles","volume":"111","author":"Amirgholy","year":"2020","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"104741","DOI":"10.1016\/j.trc.2024.104741","article-title":"Connected automated vehicles orchestrating human-driven vehicles: Optimizing traffic speed and density in urban networks","volume":"165","author":"Amirgholy","year":"2024","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_17","first-page":"159","article-title":"Parking design and pricing for regular and autonomous vehicles: A morning commute problem","volume":"10","author":"Nourinejad","year":"2022","journal-title":"Transp. B Transp. Dyn."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1177\/03611981241242064","article-title":"Understanding Drivers\u2019 Behavioral attitudes and Intentions to Use Guidance Systems in Urban Complex Parking Lots Based on the C-TAM-TPB Framework","volume":"2678","author":"Yang","year":"2024","journal-title":"Transp. Res. Rec."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.tranpol.2012.10.003","article-title":"Modelling demand under parking and cordon pricing policy","volume":"25","author":"Arintono","year":"2013","journal-title":"Transp. Policy"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"103823","DOI":"10.1016\/j.tra.2023.103823","article-title":"Understanding Delivery Drivers\u2019 Parking Preferences in Urban Freight Operations","volume":"176","author":"Amaya","year":"2023","journal-title":"Transp. Res. Part A Policy Pract."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.tra.2018.03.003","article-title":"Accounting for attitudes on parking choice: An integrated choice and latent variable approach","volume":"111","author":"Soto","year":"2018","journal-title":"Transp. Res. Part A Policy Pract."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.trc.2016.01.019","article-title":"Assessing public opinions of and interest in new vehicle technologies: An Austin perspective","volume":"67","author":"Bansal","year":"2016","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.trf.2022.05.012","article-title":"Research on parking choice behavior of shared autonomous vehicle services by measuring users\u2019 intention of usage","volume":"88","author":"Ye","year":"2022","journal-title":"Transp. Res. Part F Traffic Psychol. Behav."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"104471","DOI":"10.1016\/j.trc.2023.104471","article-title":"Modeling the joint choice behavior of commuters\u2019 travel mode and parking options for private autonomous vehicles","volume":"159","author":"Xue","year":"2024","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"103763","DOI":"10.1016\/j.tra.2023.103763","article-title":"Where to park an autonomous vehicle? Results of a stated choice experiment","volume":"175","author":"Tian","year":"2023","journal-title":"Transp. Res. Part A Policy Pract."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"104437","DOI":"10.1016\/j.trd.2024.104437","article-title":"Automated vehicles and the urban parking paradigm: Environmental implications and Citizen preference","volume":"136","author":"Garus","year":"2024","journal-title":"Transp. Res. Part D Transp. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1214\/ss\/1009213726","article-title":"Statistical Modeling: The Two Cultures","volume":"16","author":"Breiman","year":"2001","journal-title":"Stat. Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"112201","DOI":"10.1016\/j.engappai.2025.112201","article-title":"A novel approach for understanding the parking demand for internal access roads in hub car parks","volume":"161","author":"Hu","year":"2025","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_29","unstructured":"(2024, December 13). Tesla Autopilot and Full Self-Driving (Supervised). Available online: https:\/\/www.tesla.com\/support\/autopilot."},{"key":"ref_30","unstructured":"Nanjing.gov (2019). Investigation Report on the Construction of Public Parking Facilities in Nanjing."},{"key":"ref_31","unstructured":"(2024, October 22). Amap.corp China\u2019s Major Cities Traffic Health Index Ranking. Available online: https:\/\/report.amap.com\/mpages\/320100.html."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.tra.2021.08.010","article-title":"Determinants to parking mode alternatives: A model integrating technology acceptance model and satisfaction\u2013loyalty model","volume":"152","author":"Niu","year":"2021","journal-title":"Transp. Res. Part A Policy Pract."},{"key":"ref_33","unstructured":"Wenjuanxing Technology Co., Ltd. (2024, December 10). Available online: https:\/\/www.wjx.cn\/."},{"key":"ref_34","unstructured":"Baidu.Corp (2024, May 12). Apollo Parking. Available online: https:\/\/www.apollo.auto\/avp."},{"key":"ref_35","unstructured":"Baidu.Corp (2024, May 12). Video of Baidu Apollo Autonomous Driving Vehicle Road Tests. Available online: https:\/\/apollo-new.cdn.bcebos.com\/self-driving\/anp\/cityroad5.mp4."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1177\/001316447003000308","article-title":"Determining Sample Size for Research Activities","volume":"30","author":"Krejcie","year":"1970","journal-title":"Educ. Psychol. Meas."},{"key":"ref_37","unstructured":"Orme, B. (1998). Sample Size Issues for Conjoint Analysis Studies, Sawtooth Software Inc."},{"key":"ref_38","unstructured":"Nanjing.gov (2021). Bulletin of the Seventh National Population Census of Nanjing."},{"key":"ref_39","unstructured":"Nanjing.gov (2023). Nanjing Statistical Yearbook, Statistics."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.tbs.2019.12.005","article-title":"Modeling the desire for using public transport","volume":"19","author":"Waygood","year":"2020","journal-title":"Travel Behav. Soc."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"100780","DOI":"10.1016\/j.tbs.2024.100780","article-title":"How do workers respond to dissatisfaction with commuting and work? Insights from a panel survey in Luxembourg","volume":"36","author":"Maheshwari","year":"2024","journal-title":"Travel Behav. Soc."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"104975","DOI":"10.1016\/j.scs.2023.104975","article-title":"Urban travel time and residential location choice: The impacts of traffic congestion","volume":"99","author":"Zhang","year":"2023","journal-title":"Sustain. Cities Soc."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Zhong, Q., and Miao, L. (2024). Capturing impacts of travel preference on connected autonomous vehicle adoption of risk-averse travellers in multi-modal transportation networks. Transp. A Transp. Sci., 2396921.","DOI":"10.1080\/23249935.2024.2396921"},{"key":"ref_44","unstructured":"Ben-Akiva, M.E., and Lerman, S.R. (1985). Discrete Choice Analysis: Theory and Application to Travel Demand, MIT Press."},{"key":"ref_45","unstructured":"Train, K.E. (2009). Discrete Choice Methods with Simulation, Cambridge University Press."},{"key":"ref_46","unstructured":"Greene, W.H. (2019). Econometric Analysis, Global Edition, Pearson Education."},{"key":"ref_47","unstructured":"Wooldridge, J.M. (2010). Econometric Analysis of Cross Section and Panel Data, MIT Press."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Hensher, D.A., Rose, J.M., and Greene, W.H. (2015). Applied Choice Analysis, Cambridge University Press.","DOI":"10.1017\/CBO9781316136232"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.tbs.2018.09.002","article-title":"Applying a random forest method approach to model travel mode choice behavior","volume":"14","author":"Cheng","year":"2019","journal-title":"Travel Behav. Soc."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.tbs.2022.02.004","article-title":"Does commute duration attenuate the effect of travel mode choice on commute satisfaction?","volume":"28","author":"Le","year":"2022","journal-title":"Travel Behav. Soc."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/j.tbs.2022.07.003","article-title":"Predicting the travel mode choice with interpretable machine learning techniques: A comparative study","volume":"29","author":"Jamal","year":"2022","journal-title":"Travel Behav. Soc."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"100852","DOI":"10.1016\/j.tbs.2024.100852","article-title":"Machine learning-based causal inference for evaluating intervention in travel behaviour research: A difference-in-differences framework","volume":"37","author":"Zhou","year":"2024","journal-title":"Travel Behav. Soc."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"100894","DOI":"10.1016\/j.tbs.2024.100894","article-title":"Understanding factors associated with individuals\u2019 non-mandatory activities using machine learning and SHAP interpretation: A case study of Guangzhou, China","volume":"38","author":"Zou","year":"2025","journal-title":"Travel Behav. Soc."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"103727","DOI":"10.1016\/j.tra.2023.103727","article-title":"Comparing and contrasting choice model and machine learning techniques in the context of vehicle ownership decisions","volume":"173","author":"Ali","year":"2023","journal-title":"Transp. Res. Part A Policy Pract."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"102661","DOI":"10.1016\/j.jtrangeo.2020.102661","article-title":"Using machine learning for direct demand modeling of ridesourcing services in Chicago","volume":"83","author":"Yan","year":"2020","journal-title":"J. Transp. Geogr."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.eswa.2017.01.057","article-title":"A comparative study of machine learning classifiers for modeling travel mode choice","volume":"78","author":"Hagenauer","year":"2017","journal-title":"Expert Syst. Appl."},{"key":"ref_58","unstructured":"The Documentation of Scikit-learn (2024, October 12). Classification Metrics. Available online: https:\/\/scikit-learn.org\/stable\/api\/sklearn.metrics.html."},{"key":"ref_59","unstructured":"McFadden, D. (1972). Conditional Logit Analysis of Qualitative Choice Behaviour, University of California, Institute of Urban and Regional Development."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.tbs.2020.02.003","article-title":"Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models","volume":"20","author":"Zhao","year":"2020","journal-title":"Travel Behav. Soc."}],"container-title":["Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2079-8954\/13\/10\/891\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T12:24:56Z","timestamp":1760703896000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2079-8954\/13\/10\/891"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,10]]},"references-count":60,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2025,10]]}},"alternative-id":["systems13100891"],"URL":"https:\/\/doi.org\/10.3390\/systems13100891","relation":{},"ISSN":["2079-8954"],"issn-type":[{"type":"electronic","value":"2079-8954"}],"subject":[],"published":{"date-parts":[[2025,10,10]]}}}