{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T19:23:42Z","timestamp":1773775422062,"version":"3.50.1"},"reference-count":28,"publisher":"Association for Computing Machinery (ACM)","issue":"4","funder":[{"DOI":"10.13039\/100022283","name":"Alabama Department of Economic and Community Affairs","doi-asserted-by":"crossref","award":["1ARDEF2103"],"award-info":[{"award-number":["1ARDEF2103"]}],"id":[{"id":"10.13039\/100022283","id-type":"DOI","asserted-by":"crossref"}]},{"name":"U.S. Department of Transportation through the Southeastern Transportation Research, Innovation, Development, and Education (STRIDE I2) Region 4 University Transportation Center","award":["69A3551747104"],"award-info":[{"award-number":["69A3551747104"]}]},{"name":"DOE ECRP Award","award":["0000274975, NSF OAC-2414474, NSF OAC-2414185"],"award-info":[{"award-number":["0000274975, NSF OAC-2414474, NSF OAC-2414185"]}]},{"name":"Radiance Technology Innovation Bowl 2023 (GEOINT) Winner Award"},{"name":"NSF","award":["OAC-2152085, IIS-2207072, OAC-2402946 and OAC-2410884"],"award-info":[{"award-number":["OAC-2152085, IIS-2207072, OAC-2402946 and OAC-2410884"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Spatial Algorithms Syst."],"published-print":{"date-parts":[[2025,12,31]]},"abstract":"<jats:p>The popularity of smartphones and 4G\/5G network have enabled various novel transportation modes based on shared mobility, such as app-based ride-hailing services (e.g., Uber and Lyft) and shared micromobility services (e.g., Veo and Gotcha). However, little is known about to what degree their operations impact urban traffic, which is important for transportation planning and policy making. These companies seldom share their ride data due to business and user privacy reasons, and they are young and still exploring and growing their market to new locations. Recently, transportation engineering researchers began to collect data in large cities trying to understand the transportation impacts of shared mobility services, but (1)\u00a0there does not exist a general analytics framework applicable to any city, and (2)\u00a0the studies were based on historical data and cannot project the future easily to catch up with the rapid development of shared mobility services.<\/jats:p>\n          <jats:p>In this article, we introduce a general framework for multi-modal urban traffic analytics. The goal is to build a digital twin of the transportation in a city, i.e., an accurate agent-based transportation simulation model, based on a medium-sized dataset of the interested transportation modes collected by the research group combined with other open data sources such as US Census Bureau. With this digital twin, transportation engineering researchers can flexibly analyze the impact of shared mobility services under different scenarios, such as \u201cif the number of Uber drivers doubles\u201d or \u201cif the number of deployed e-scooters doubles\u201d. The digital twin may also enable new opportunities, such as being an environment for learning policies with reinforcement learning. Our framework consists of three steps: (1)\u00a0fitting the spatiotemporal distribution of the shared mobility rides on the underlying road network, (2)\u00a0generating the travel day-plans of the entire urban population based on the learned spatiotemporal ride distribution and user-specified parameters, and (3)\u00a0configuring an agent-based simulation software such as MATSim to execute the generated realistic day-plans, which provides detailed transportation data for analytics. At the core of our approach is a new spatiotemporal network kernel density estimation (KDE) method that fixes the flaw of prior methods where the contributions of different data samples are not equal. We also propose a crowdsourcing method to collect app-based ride data that is easy to carry out in any city. Using Birmingham, AL as an example, we demonstrate how our framework can be applied to help transportation engineering researchers analyze the impacts of Uber ride-hailing and Veo e-scooter services.<\/jats:p>","DOI":"10.1145\/3704918","type":"journal-article","created":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T22:56:45Z","timestamp":1731970605000},"page":"1-31","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Urban Traffic Simulation with Shared Mobility Services: An Approach Using Spatiotemporal Network Kernel Density Estimation and MATSim"],"prefix":"10.1145","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9853-2352","authenticated-orcid":false,"given":"Jalal","family":"Khalil","sequence":"first","affiliation":[{"name":"St. Cloud State University","place":["St. Cloud, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4653-0408","authenticated-orcid":false,"given":"Da","family":"Yan","sequence":"additional","affiliation":[{"name":"Computer Science, Indiana University Bloomington","place":["Bloomington, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4374-8161","authenticated-orcid":false,"given":"Lyuheng","family":"Yuan","sequence":"additional","affiliation":[{"name":"Computer Science, Indiana University Bloomington","place":["Bloomington, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5052-7458","authenticated-orcid":false,"given":"Mostafa","family":"Jafarzadehfadaki","sequence":"additional","affiliation":[{"name":"Arcadis","place":["Atlanta, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7846-2200","authenticated-orcid":false,"given":"Saugat","family":"Adhikari","sequence":"additional","affiliation":[{"name":"Computer Science, Indiana University Bloomington","place":["Bloomington, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4152-182X","authenticated-orcid":false,"given":"Jiao","family":"Han","sequence":"additional","affiliation":[{"name":"Computer Science, Indiana University Bloomington","place":["Bloomington, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4262-8990","authenticated-orcid":false,"given":"Virginia","family":"Sisiopiku","sequence":"additional","affiliation":[{"name":"Civil, Construction, & Environmental Engineering, The University of Alabama at Birmingham","place":["Birmingham, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3576-6976","authenticated-orcid":false,"given":"Zhe","family":"Jiang","sequence":"additional","affiliation":[{"name":"University of Florida","place":["Gainesville, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,8,25]]},"reference":[{"key":"e_1_3_2_2_2","volume-title":"Introduction to Machine Learning","author":"Alpaydin Ethem","year":"2004","unstructured":"Ethem Alpaydin. 2004. Introduction to Machine Learning. MIT Press."},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2020.102890"},{"key":"e_1_3_2_4_2","article-title":"News on E-scooter Concerns in Fort Wayne, IN","author":"Carroll Joe","year":"2023","unstructured":"Joe Carroll and Mia Pettigrew. 2023. News on E-scooter Concerns in Fort Wayne, IN. Retrieved Nov. 22, 2024 from https:\/\/www.wane.com\/news\/local-news\/bye-bye-scooters-fort-wayne-ends-partnership-with-veo\/","journal-title":"https:\/\/www.wane.com\/news\/local-news\/bye-bye-scooters-fort-wayne-ends-partnership-with-veo\/"},{"key":"e_1_3_2_5_2","article-title":"News on E-scooter Concerns in Birmingham, AL","author":"Chapman Jake","year":"2021","unstructured":"Jake Chapman. 2021. News on E-scooter Concerns in Birmingham, AL. Retrieved Nov. 22, 2024 from https:\/\/www.cbs42.com\/news\/electric-scooters-growing-in-popularity-leaders-urge-people-to-ride-cautiously\/","journal-title":"https:\/\/www.cbs42.com\/news\/electric-scooters-growing-in-popularity-leaders-urge-people-to-ride-cautiously\/"},{"key":"e_1_3_2_6_2","unstructured":"Giovanni Circella Farzad Alemi Kate Tiedeman Susan Handy Patricia L. Mokhtarian et\u00a0al. 2018. The Adoption of Shared Mobility in California and its Relationship with other Components of Travel Behavior. National Center for Sustainable Transportation Davis (2018). https:\/\/rosap.ntl.bts.gov\/view\/dot\/35032"},{"issue":"42","key":"e_1_3_2_7_2","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1177\/0361198118798459","article-title":"Profiling transport network company activity using big data","volume":"2672","author":"Cooper Drew","year":"2018","unstructured":"Drew Cooper, Joe Castiglione, Alan Mislove, and Christo Wilson. 2018. Profiling transport network company activity using big data. Transportation Research Record 2672, 42 (2018), 192\u2013202.","journal-title":"Transportation Research Record"},{"key":"e_1_3_2_8_2","article-title":"Veo Pilot Program in Birmingham","author":"Council Birmingham City","year":"2021","unstructured":"Birmingham City Council. 2021. Veo Pilot Program in Birmingham. Retrieved Nov. 22, 2024 from https:\/\/www.birminghamal.gov\/2021\/04\/18\/shared-bikes-and-scooters-now-available-in-birmingham\/","journal-title":"https:\/\/www.birminghamal.gov\/2021\/04\/18\/shared-bikes-and-scooters-now-available-in-birmingham\/"},{"issue":"5","key":"e_1_3_2_9_2","doi-asserted-by":"crossref","first-page":"eaau2670","DOI":"10.1126\/sciadv.aau2670","article-title":"Do transportation network companies decrease or increase congestion?","volume":"5","author":"Erhardt Gregory D.","year":"2019","unstructured":"Gregory D. Erhardt, Sneha Roy, Drew Cooper, Bhargava Sana, Mei Chen, and Joe Castiglione. 2019. Do transportation network companies decrease or increase congestion? Science Advances 5, 5 (2019), eaau2670.","journal-title":"Science Advances"},{"issue":"2","key":"e_1_3_2_10_2","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1007\/s11116-020-10081-4","article-title":"Are travelers substituting between transportation network companies (TNC) and public buses? A case study in Pittsburgh","volume":"48","author":"Grahn Rick","year":"2021","unstructured":"Rick Grahn, Sean Qian, H. Scott Matthews, and Chris Hendrickson. 2021. Are travelers substituting between transportation network companies (TNC) and public buses? A case study in Pittsburgh. Transportation 48, 2 (2021), 977\u20131005.","journal-title":"Transportation"},{"key":"e_1_3_2_11_2","first-page":"4512","volume-title":"Proceedings of the 2019 IEEE International Conference on BigData","author":"Guo Guimu","year":"2019","unstructured":"Guimu Guo, Jalal Majed Khalil, Da Yan, and Virginia P. Sisiopiku. 2019. Realistic transport simulation: Tackling the small data challenge with open data. In Proceedings of the 2019 IEEE International Conference on BigData. IEEE, 4512\u20134519."},{"key":"e_1_3_2_12_2","first-page":"6066","volume-title":"Proceedings of the 2019 IEEE International Conference on BigData","author":"Guo Guimu","year":"2019","unstructured":"Guimu Guo, Jalal Majed Khalil, Da Yan, and Virginia P. Sisiopiku. 2019. Realistic transport simulation with open data. In Proceedings of the 2019 IEEE International Conference on BigData. IEEE, 6066\u20136068."},{"key":"e_1_3_2_13_2","first-page":"1114","volume-title":"Proceedings of the IEEE International Conference on Data Mining, ICDM 2021","author":"Hui Bo","year":"2021","unstructured":"Bo Hui, Da Yan, Haiquan Chen, and Wei-Shinn Ku. 2021. Trajectory WaveNet: A trajectory-based model for traffic forecasting. In Proceedings of the IEEE International Conference on Data Mining, ICDM 2021. IEEE, 1114\u20131119."},{"key":"e_1_3_2_14_2","first-page":"716","volume-title":"KDD \u201921: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","author":"Hui Bo","year":"2021","unstructured":"Bo Hui, Da Yan, Haiquan Chen, and Wei-Shinn Ku. 2021. TrajNet: A trajectory-based deep learning model for traffic prediction. In KDD \u201921: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. ACM, 716\u2013724."},{"key":"e_1_3_2_15_2","first-page":"5935","volume-title":"Proceedings of the 2021 IEEE International Conference on Big Data","author":"Khalil Jalal","year":"2021","unstructured":"Jalal Khalil, Da Yan, Guimu Guo, Mirza Tanzim Sami, Joy Bhadhan Roy, and Virginia P. Sisiopiku. 2021. Realistic transport simulation for studying the impacts of shared micromobility services. In Proceedings of the 2021 IEEE International Conference on Big Data. IEEE, 5935\u20135937."},{"key":"e_1_3_2_16_2","first-page":"3691","volume-title":"Proceedings of the 2021 IEEE International Conference on BigData","author":"Khalil Jalal","year":"2021","unstructured":"Jalal Khalil, Da Yan, Guimu Guo, Mirza Tanzim Sami, Joy Bhadhan Roy, and Virginia P. Sisiopiku. 2021. Traffic study of shared micromobility services by transportation simulation. In Proceedings of the 2021 IEEE International Conference on BigData. IEEE, 3691\u20133699."},{"key":"e_1_3_2_17_2","first-page":"29:1\u201329:10","volume-title":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2022","author":"Khalil Jalal","year":"2022","unstructured":"Jalal Khalil, Da Yan, Lyuheng Yuan, Mostafa Jafarzadehfadaki, Saugat Adhikari, Virginia P. Sisiopiku, and Zhe Jiang. 2022. Realistic urban traffic simulation with ride-hailing services: A revisit to network kernel density estimation (systems paper). In Proceedings of the 30th International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2022. ACM, 29:1\u201329:10."},{"issue":"1","key":"e_1_3_2_18_2","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1111\/poms.13530","article-title":"How do on-demand ridesharing services affect traffic congestion? The moderating role of urban compactness","volume":"31","author":"Li Ziru","year":"2022","unstructured":"Ziru Li, Chen Liang, Yili Hong, and Zhongju Zhang. 2022. How do on-demand ridesharing services affect traffic congestion? The moderating role of urban compactness. Production and Operations Management 31, 1 (2022), 239\u2013258.","journal-title":"Production and Operations Management"},{"key":"e_1_3_2_19_2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1007\/978-3-642-40235-7_3","volume-title":"Advances in Spatial and Temporal Databases SSTD 2013","author":"Mokbel Mohamed F.","year":"2013","unstructured":"Mohamed F. Mokbel, Louai Alarabi, Jie Bao, Ahmed Eldawy, Amr Magdy, Mohamed Sarwat, Ethan Waytas, and Steven Yackel. 2013. MNTG: An extensible web-based traffic generator. In Advances in Spatial and Temporal Databases SSTD 2013, Mario A. Nascimento, Timos K. Sellis, Reynold Cheng, J\u00f6rg Sander, Yu Zheng, Hans-Peter Kriegel, Matthias Renz, and Christian Sengstock (Eds.). Lecture Notes in Computer Science, Vol. 8098, Springer, 38\u201355."},{"key":"e_1_3_2_20_2","article-title":"NACTO\u2019s 2022 Shared Micromobility Report","year":"2023","unstructured":"NACTO. 2023. NACTO\u2019s 2022 Shared Micromobility Report. Retrieved Nov. 22, 2024 from https:\/\/nacto.org\/wp-content\/uploads\/2023\/11\/NACTO_sharedmicromobilitysnapshot_correctedNov3-2023-1.pdf.","journal-title":"https:\/\/nacto.org\/wp-content\/uploads\/2023\/11\/NACTO_sharedmicromobilitysnapshot_correctedNov3-2023-1.pdf"},{"key":"e_1_3_2_21_2","article-title":"Shared Micromobility in Birmingham","author":"Program Birmingham Micromobility","year":"2021","unstructured":"Birmingham Micromobility Program. 2021. Shared Micromobility in Birmingham. Retrieved Nov. 22, 2024 from https:\/\/www.birminghamal.gov\/transportation\/shared-micromobility\/","journal-title":"https:\/\/www.birminghamal.gov\/transportation\/shared-micromobility\/"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2020.102053"},{"key":"e_1_3_2_23_2","first-page":"98:1\u201398:4","volume-title":"Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","author":"Romano Benjamin","year":"2017","unstructured":"Benjamin Romano and Zhe Jiang. 2017. Visualizing traffic accident hotspots based on spatial-temporal network kernel density estimation. In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. ACM, 98:1\u201398:4."},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.17265\/2328-2142\/2023.01.001"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.3390\/futuretransp3020030"},{"issue":"1","key":"e_1_3_2_26_2","doi-asserted-by":"crossref","first-page":"59","DOI":"10.4236\/jtts.2022.121004","article-title":"Potential benefits of increased public transit ridership in medium sized cities: A case study","volume":"12","author":"Sultana Taniya","year":"2021","unstructured":"Taniya Sultana, Virginia P. Sisiopiku, Jalal Khalil, and Da Yan. 2021. Potential benefits of increased public transit ridership in medium sized cities: A case study. Journal of Transportation Technologies 12, 1 (2021), 59\u201379.","journal-title":"Journal of Transportation Technologies"},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11116-019-10070-2"},{"issue":"5","key":"e_1_3_2_28_2","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1016\/j.compenvurbsys.2008.05.001","article-title":"Kernel Density Estimation of traffic accidents in a network space","volume":"32","author":"Xie Zhixiao","year":"2008","unstructured":"Zhixiao Xie and Jun Yan. 2008. Kernel Density Estimation of traffic accidents in a network space. Computers, Environment, and Urban Systems 32, 5 (2008), 396\u2013406.","journal-title":"Computers, Environment, and Urban Systems"},{"key":"e_1_3_2_29_2","article-title":"Didi Data Security Issue","author":"Zhu Julie","year":"2021","unstructured":"Julie Zhu, Kane Wu, and Brenda Goh. 2021. Didi Data Security Issue. Retrieved Nov. 22, 2024 from https:\/\/www.reuters.com\/world\/china\/china-asks-didi-delist-us-security-fears-bloomberg-news-2021-11-26\/","journal-title":"https:\/\/www.reuters.com\/world\/china\/china-asks-didi-delist-us-security-fears-bloomberg-news-2021-11-26\/"}],"container-title":["ACM Transactions on Spatial Algorithms and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3704918","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,25]],"date-time":"2025-08-25T12:38:30Z","timestamp":1756125510000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3704918"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,25]]},"references-count":28,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,12,31]]}},"alternative-id":["10.1145\/3704918"],"URL":"https:\/\/doi.org\/10.1145\/3704918","relation":{},"ISSN":["2374-0353","2374-0361"],"issn-type":[{"value":"2374-0353","type":"print"},{"value":"2374-0361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,25]]},"assertion":[{"value":"2024-01-03","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-11-15","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-08-25","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}