{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T13:09:18Z","timestamp":1765544958318,"version":"3.44.0"},"reference-count":90,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"NSF","award":["2047822,1952096,1951890"],"award-info":[{"award-number":["2047822,1952096,1951890"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2024,5,13]]},"abstract":"<jats:p>Accurate road networks play a crucial role in modern mobile applications such as navigation and last-mile delivery. Most existing studies primarily focus on generating road networks in open areas like main roads and avenues, but little attention has been given to the generation of community road networks in closed areas such as residential areas, which becomes more and more significant due to the growing demand for door-to-door services such as food delivery. This lack of research is primarily attributed to challenges related to sensing data availability and quality. In this paper, we design a novel framework called SmallMap that leverages ubiquitous multi-modal sensing data from last-mile delivery to automatically generate community road networks with low costs. Our SmallMap consists of two key modules: (1) a Trajectory of Interest Detection module enhanced by exploiting multi-modal sensing data collected from the delivery process; and (2) a Dual Spatio-temporal Generative Adversarial Network module that incorporates Trajectory of Interest by unsupervised road network adaptation to generate road networks automatically. To evaluate the effectiveness of SmallMap, we utilize a two-month dataset from one of the largest logistics companies in China. The extensive evaluation results demonstrate that our framework significantly outperforms state-of-the-art baselines, achieving a precision of 90.5%, a recall of 87.5%, and an F1-score of 88.9%, respectively. Moreover, we conduct three case studies in Beijing City for courier workload estimation, Estimated Time of Arrival (ETA) in last-mile delivery, and fine-grained order assignment.<\/jats:p>","DOI":"10.1145\/3659596","type":"journal-article","created":{"date-parts":[[2024,5,15]],"date-time":"2024-05-15T12:20:41Z","timestamp":1715775641000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["SmallMap: Low-cost Community Road Map Sensing with Uncertain Delivery Behavior"],"prefix":"10.1145","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3682-4290","authenticated-orcid":false,"given":"Zhiqing","family":"Hong","sequence":"first","affiliation":[{"name":"JD Logistics, China and Rutgers University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9783-6389","authenticated-orcid":false,"given":"Haotian","family":"Wang","sequence":"additional","affiliation":[{"name":"JD Logistics, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1226-341X","authenticated-orcid":false,"given":"Yi","family":"Ding","sequence":"additional","affiliation":[{"name":"University of Texas at Dallas, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7739-7945","authenticated-orcid":false,"given":"Guang","family":"Wang","sequence":"additional","affiliation":[{"name":"Florida State University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6062-2619","authenticated-orcid":false,"given":"Tian","family":"He","sequence":"additional","affiliation":[{"name":"JD Logistics, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9307-8736","authenticated-orcid":false,"given":"Desheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Rutgers University, USA"}]}],"member":"320","published-online":{"date-parts":[[2024,5,15]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2023. Baidu Maps. 2023. https:\/\/maps.baidu.com\/."},{"key":"e_1_2_1_2_1","unstructured":"2023. Gaode Maps. 2023. https:\/\/maps.gaode.com\/."},{"key":"e_1_2_1_3_1","unstructured":"2023. Google Maps. 2023. https:\/\/maps.google.com\/."},{"volume-title":"Keep B2 Bracelet","year":"2023","key":"e_1_2_1_4_1","unstructured":"2023. Keep B2 Bracelet. 2023. https:\/\/www.gotokeep.com\/aiot."},{"key":"e_1_2_1_5_1","unstructured":"2023. OpenStreetMap (OSM). 2023. https:\/\/www.openstreetmap.org\/."},{"volume-title":"Scikit mobility","year":"2023","key":"e_1_2_1_6_1","unstructured":"2023. Scikit mobility. 2023. https:\/\/scikit-mobility.github.io\/scikit-mobility\/."},{"volume-title":"Youboxun i9000","year":"2023","key":"e_1_2_1_7_1","unstructured":"2023. Youboxun i9000. 2023. https:\/\/en.urovo.com\/products\/payment\/I9000S.html."},{"key":"e_1_2_1_8_1","volume-title":"Using Air Pollution Monitoring As A Usecase. In Network and Distributed Systems Security Symposium.","author":"Abidi Ismi","year":"2022","unstructured":"Ismi Abidi, Ishan Nangia, Paarijaat Aditya, and Rijurekha Sen. 2022. Privacy in Urban Sensing with Instrumented Fleets, Using Air Pollution Monitoring As A Usecase. In Network and Distributed Systems Security Symposium."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6638314"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01169"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.3141\/2291-08"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/2500423.2504574"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2005.1520084"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/IPSN.2018.00009"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1653771.1653776"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939833"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939833"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351236"},{"key":"e_1_2_1_19_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3343857","article-title":"BikeGPS: Localizing shared bikes in street canyons with low-level GPS cooperation","volume":"15","author":"Chen Kongyang","year":"2019","unstructured":"Kongyang Chen and Guang Tan. 2019. BikeGPS: Localizing shared bikes in street canyons with low-level GPS cooperation. ACM Transactions on Sensor Networks (TOSN) 15, 4 (2019), 1--28.","journal-title":"ACM Transactions on Sensor Networks (TOSN)"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3463495"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2014.6848175"},{"key":"e_1_2_1_22_1","volume-title":"GREC 2009","author":"Chiang Yao-Yi","year":"2010","unstructured":"Yao-Yi Chiang and Craig A Knoblock. 2010. Extracting road vector data from raster maps. In Graphics Recognition. Achievements, Challenges, and Evolution: 8th International Workshop, GREC 2009, La Rochelle, France, July 22-23, 2009. Selected Papers 8. Springer, 93--105."},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2017.246"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jtrangeo.2015.12.007"},{"key":"e_1_2_1_25_1","volume-title":"Emil Stubbe Kolvig-Raun, and Mikkel Baun Kj\u00e6rgaard","author":"Das Anooshmita","year":"2020","unstructured":"Anooshmita Das, Emil Stubbe Kolvig-Raun, and Mikkel Baun Kj\u00e6rgaard. 2020. Accurate Trajectory Prediction in a Smart Building Using Recurrent Neural Networks. In UbiComp-ISWC'20. ACM, 619--628."},{"volume-title":"Computer science in perspective","author":"Edelkamp Stefan","key":"e_1_2_1_26_1","unstructured":"Stefan Edelkamp and Stefan Schr\u00f6dl. 2003. Route planning and map inference with global positioning traces. In Computer science in perspective. Springer, 128--151."},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3448076"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-86514-6_25"},{"key":"e_1_2_1_29_1","volume-title":"Greedy function approximation: a gradient boosting machine. Annals of statistics","author":"Friedman Jerome H","year":"2001","unstructured":"Jerome H Friedman. 2001. Greedy function approximation: a gradient boosting machine. Annals of statistics (2001), 1189--1232."},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3422622"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3474717.3484264"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599915"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534574"},{"key":"e_1_2_1_34_1","volume-title":"Streetgan: Towards road network synthesis with generative adversarial networks.","author":"Hartmann Stefan","year":"2017","unstructured":"Stefan Hartmann, Michael Weinmann, Raoul Wessel, and Reinhard Klein. 2017. Streetgan: Towards road network synthesis with generative adversarial networks. (2017)."},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3274895.3274974"},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380097"},{"key":"e_1_2_1_38_1","doi-asserted-by":"crossref","unstructured":"Tianfu He Jie Bao Ruiyuan Li Sijie Ruan Yanhua Li Chao Tian and Yu Zheng. 2018. Detecting Vehicle Illegal Parking Events using Sharing Bikes' Trajectories.. In KDD. 340--349.","DOI":"10.1145\/3219819.3219887"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3384419.3430579"},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3557915.3560944"},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3614724"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3557915.3560999"},{"key":"e_1_2_1_43_1","volume-title":"Road network construction with complex intersections based on sparsely sampled private car trajectory data. ACM Transactions on Knowledge Discovery from Data (TKDD) 13, 3","author":"Huang Yourong","year":"2019","unstructured":"Yourong Huang, Zhu Xiao, Xiaoyou Yu, Dong Wang, Vincent Havyarimana, and Jing Bai. 2019. Road network construction with complex intersections based on sparsely sampled private car trajectory data. ACM Transactions on Knowledge Discovery from Data (TKDD) 13, 3 (2019), 1--28."},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3386901.3388944"},{"key":"e_1_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/2307636.2307659"},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.632"},{"key":"e_1_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/321765.321768"},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3596252"},{"key":"e_1_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/3550333"},{"key":"e_1_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3557915.3560958"},{"key":"e_1_2_1_51_1","first-page":"1","article-title":"Traffic Flow Prediction with Vehicle Trajectories","volume":"35","author":"Li Mingqian","year":"2021","unstructured":"Mingqian Li, Panrong Tong, Mo Li, Zhongming Jin, Jianqiang Huang, and Xian-Sheng Hua. 2021. Traffic Flow Prediction with Vehicle Trajectories. AAAI 35, 1 (May 2021), 294--302.","journal-title":"AAAI"},{"key":"e_1_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/1463434.1463477"},{"key":"e_1_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557481"},{"key":"e_1_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339637"},{"key":"e_1_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3386901.3388945"},{"key":"e_1_2_1_56_1","first-page":"2177","article-title":"STAN","volume":"2021","author":"Luo Yingtao","year":"2021","unstructured":"Yingtao Luo, Qiang Liu, and Zhaocheng Liu. 2021. STAN: Spatio-Temporal Attention Network for Next Location Recommendation. In WWW 2021. 2177- 2185.","journal-title":"Spatio-Temporal Attention Network for Next Location Recommendation. In WWW"},{"key":"e_1_2_1_57_1","volume-title":"European Conference on Data Analysis (ECDA), Date: 2018\/07\/04-2018\/07\/06","author":"Meert Wannes","year":"2018","unstructured":"Wannes Meert and Mathias Verbeke. 2018. HMM with non-emitting states for Map Matching. In European Conference on Data Analysis (ECDA), Date: 2018\/07\/04-2018\/07\/06, Location: Paderborn, Germany."},{"key":"e_1_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.14778\/3476249.3476279"},{"key":"e_1_2_1_59_1","volume-title":"Article 20 (March","author":"Nair Suraj","year":"2019","unstructured":"Suraj Nair, Kiran Javkar, Jiahui Wu, and Vanessa Frias-Martinez. 2019. Understanding Cycling Trip Purpose and Route Choice Using GPS Traces and Open Data. IMWUT. 3, 1, Article 20 (March 2019), 26 pages."},{"key":"e_1_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1145\/3495243.3560546"},{"key":"e_1_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1145\/3274783.3274850"},{"key":"e_1_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5435"},{"key":"e_1_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539027"},{"key":"e_1_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE53745.2022.00307"},{"key":"e_1_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/3528233.3530757"},{"key":"e_1_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1145\/3191764"},{"key":"e_1_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1145\/3372224.3421461"},{"key":"e_1_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611975321.15"},{"key":"e_1_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00769"},{"key":"e_1_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1145\/3281548.3281550"},{"key":"e_1_2_1_72_1","doi-asserted-by":"publisher","DOI":"10.5555\/1972457.1972485"},{"key":"e_1_2_1_73_1","doi-asserted-by":"publisher","DOI":"10.1145\/1644038.1644048"},{"key":"e_1_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447993.3448617"},{"key":"e_1_2_1_75_1","volume-title":"Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971","author":"Touvron Hugo","year":"2023","unstructured":"Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timoth\u00e9e Lacroix, Baptiste Rozi\u00e8re, Naman Goyal, Eric Hambro, Faisal Azhar, et al. 2023. Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971 (2023)."},{"key":"e_1_2_1_76_1","volume-title":"Crowdatlas: Self-updating maps for cloud and personal use. In Proceeding of the 11th annual international conference on Mobile systems, applications, and services. 27--40.","author":"Wang Yin","year":"2013","unstructured":"Yin Wang, Xuemei Liu, Hong Wei, George Forman, Chao Chen, and Yanmin Zhu. 2013. Crowdatlas: Self-updating maps for cloud and personal use. In Proceeding of the 11th annual international conference on Mobile systems, applications, and services. 27--40."},{"key":"e_1_2_1_77_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539029"},{"key":"e_1_2_1_78_1","doi-asserted-by":"publisher","DOI":"10.1145\/3372224.3419198"},{"key":"e_1_2_1_79_1","doi-asserted-by":"publisher","DOI":"10.1145\/2639108.2639116"},{"key":"e_1_2_1_80_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/444"},{"key":"e_1_2_1_81_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219946"},{"key":"e_1_2_1_82_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403301"},{"key":"e_1_2_1_83_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403301"},{"key":"e_1_2_1_84_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351282"},{"key":"e_1_2_1_85_1","doi-asserted-by":"publisher","DOI":"10.1145\/3432214"},{"key":"e_1_2_1_86_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE48307.2020.00145"},{"key":"e_1_2_1_87_1","volume-title":"Quoc Viet Hung Nguyen, and Kai Zheng","author":"Zhao Yan","year":"2018","unstructured":"Yan Zhao, Shuo Shang, Yu Wang, Bolong Zheng, Quoc Viet Hung Nguyen, and Kai Zheng. 2018. Rest: A reference-based framework for spatio-temporal trajectory compression. In KDD'2018. 2797--2806."},{"key":"e_1_2_1_88_1","volume-title":"Experience: Adopting Indoor Outdoor Detection in On-demand Food Delivery Business.","author":"Zhou Pengfei","year":"2022","unstructured":"Pengfei Zhou, Yi Ding, Yang Li, Mo Li, Guobin Shen, and Tian He. 2022. Experience: Adopting Indoor Outdoor Detection in On-demand Food Delivery Business. (2022)."},{"key":"e_1_2_1_89_1","doi-asserted-by":"publisher","DOI":"10.1145\/2426656.2426668"},{"key":"e_1_2_1_90_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"}],"container-title":["Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3659596","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3659596","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T17:04:22Z","timestamp":1755882262000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3659596"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":90,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2024,5,13]]}},"alternative-id":["10.1145\/3659596"],"URL":"https:\/\/doi.org\/10.1145\/3659596","relation":{},"ISSN":["2474-9567"],"issn-type":[{"type":"electronic","value":"2474-9567"}],"subject":[],"published":{"date-parts":[[2024,5,13]]},"assertion":[{"value":"2024-05-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}