{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T13:55:09Z","timestamp":1766152509933,"version":"3.48.0"},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","funder":[{"name":"UW-Madison Data Science Institute"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,3]]},"DOI":"10.1145\/3764912.3770832","type":"proceedings-article","created":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T13:51:23Z","timestamp":1766152283000},"page":"161-173","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["GeoAI for Driving Risk Assessment via Vision-Language Models: A Knowledge Guided RAG System and Dual Evaluation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-0946-9821","authenticated-orcid":false,"given":"Chen","family":"Wei","sequence":"first","affiliation":[{"name":"University of Wisconsin - Madison, Madison, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2368-9483","authenticated-orcid":false,"given":"Yiwei","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Wisconsin - Madison, Madison, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8453-2287","authenticated-orcid":false,"given":"Xi","family":"Guan","sequence":"additional","affiliation":[{"name":"Cornell University, Ithaca, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-1436-7105","authenticated-orcid":false,"given":"Qianheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Wisconsin - Madison, Madison, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-6775-8360","authenticated-orcid":false,"given":"Yanbing","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Wisconsin - Madison, Madison, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5497-1879","authenticated-orcid":false,"given":"Yuhan","family":"Ji","sequence":"additional","affiliation":[{"name":"University of Wisconsin - Madison, Madison, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0045-3849","authenticated-orcid":false,"given":"Yibo","family":"Zhao","sequence":"additional","affiliation":[{"name":"University of Wisconsin - Madison, Madison, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8920-4402","authenticated-orcid":false,"given":"Maoping","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Wisconsin - Madison, Madison, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9425-8468","authenticated-orcid":false,"given":"Ying","family":"Nie","sequence":"additional","affiliation":[{"name":"University of Wisconsin - Madison, Madison, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1759-1933","authenticated-orcid":false,"given":"Hanchen","family":"Zhuang","sequence":"additional","affiliation":[{"name":"University of Wisconsin - Madison, Madison, WI, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4359-6302","authenticated-orcid":false,"given":"Song","family":"Gao","sequence":"additional","affiliation":[{"name":"University of Wisconsin - Madison, Madison, USA"}]}],"member":"320","published-online":{"date-parts":[[2025,12,19]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/j.aap.2008.12.014","article-title":"Kernel density estimation and K-means clustering to profile road accident hotspots","volume":"41","author":"Anderson Tessa K","year":"2009","unstructured":"Tessa K Anderson. 2009. Kernel density estimation and K-means clustering to profile road accident hotspots. Accident Analysis & Prevention 41, 3 (2009), 359\u2013364.","journal-title":"Accident Analysis & Prevention"},{"key":"e_1_3_2_1_2_1","volume-title":"A data-driven approach for driving safety risk prediction using driver behavior and roadway information data","author":"Arbabzadeh Nasim","year":"2017","unstructured":"Nasim Arbabzadeh and Mohsen Jafari. 2017. A data-driven approach for driving safety risk prediction using driver behavior and roadway information data. IEEE transactions on intelligent transportation systems 19, 2 (2017), 446\u2013460."},{"key":"e_1_3_2_1_3_1","volume-title":"Recent advances in traffic accident analysis and prediction: a comprehensive review of machine learning techniques. arXiv preprint arXiv:2406.13968","author":"Behboudi Noushin","year":"2024","unstructured":"Noushin Behboudi, Sobhan Moosavi, and Rajiv Ramnath. 2024. Recent advances in traffic accident analysis and prediction: a comprehensive review of machine learning techniques. arXiv preprint arXiv:2406.13968 (2024)."},{"key":"e_1_3_2_1_4_1","volume-title":"Modeling and analyzing urban networks and amenities with OSMnx. Geographical Analysis","author":"Boeing Geoff","year":"2025","unstructured":"Geoff Boeing. 2025. Modeling and analyzing urban networks and amenities with OSMnx. Geographical Analysis (2025)."},{"key":"e_1_3_2_1_5_1","volume-title":"Driving with Regulation: Interpretable Decision-Making for Autonomous Vehicles with Retrieval-Augmented Reasoning via LLM. arXiv preprint arXiv:2410.04759","author":"Cai Tianhui","year":"2024","unstructured":"Tianhui Cai, Yifan Liu, Zewei Zhou, Haoxuan Ma, Seth Z Zhao, Zhiwen Wu, and Jiaqi Ma. 2024. Driving with Regulation: Interpretable Decision-Making for Autonomous Vehicles with Retrieval-Augmented Reasoning via LLM. arXiv preprint arXiv:2410.04759 (2024)."},{"key":"e_1_3_2_1_6_1","volume-title":"2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, 1527\u20131533","author":"Chandar Srikanth","year":"2020","unstructured":"Srikanth Chandar, Anish Reddy, Muvazima Mansoor, and Suresh Jamadagni. 2020. Road accident proneness indicator based on time, weather and location specificity using graph neural networks. In 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, 1527\u20131533."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2024.04.024"},{"key":"e_1_3_2_1_8_1","volume-title":"Citygpt: Empowering urban spatial cognition of large language models. arXiv preprint arXiv:2406.13948","author":"Feng Jie","year":"2024","unstructured":"Jie Feng, Yuwei Du, Tianhui Liu, Siqi Guo, Yuming Lin, and Yong Li. 2024. Citygpt: Empowering urban spatial cognition of large language models. arXiv preprint arXiv:2406.13948 (2024)."},{"key":"e_1_3_2_1_9_1","volume-title":"Urbanvlp: A multi-granularity vision-language pre-trained foundation model for urban indicator prediction. arXiv e-prints","author":"Hao Xixuan","year":"2024","unstructured":"Xixuan Hao, Wei Chen, Yibo Yan, Siru Zhong, Kun Wang, Qingsong Wen, and Yuxuan Liang. 2024. Urbanvlp: A multi-granularity vision-language pre-trained foundation model for urban indicator prediction. arXiv e-prints (2024), arXiv-2403."},{"key":"e_1_3_2_1_10_1","volume-title":"Annual Report","author":"RAP.","year":"2021","unstructured":"iRAP. 2021. International Road Assessment Programme Annual Report 2021. Technical Report. International Road Assessment Programme. https:\/\/irap.org\/2022\/04\/2021-annual-report-showcases-partner-success\/"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1080\/00330124.2012.700499"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1080\/00330124.2014.968886","article-title":"The evolution of natural cities from the perspective of location-based social media","volume":"67","author":"Jiang Bin","year":"2015","unstructured":"Bin Jiang and Yufan Miao. 2015. The evolution of natural cities from the perspective of location-based social media. The Professional Geographer 67, 2 (2015), 295\u2013306.","journal-title":"The Professional Geographer"},{"key":"e_1_3_2_1_13_1","volume-title":"Proceedings of the AAAI conference on artificial intelligence","volume":"33","author":"Kumar Yaman","year":"2019","unstructured":"Yaman Kumar, Swati Aggarwal, Debanjan Mahata, Rajiv Ratn Shah, Ponnurangam Kumaraguru, and Roger Zimmermann. 2019. Get it scored using autosas\u2014an automated system for scoring short answers. In Proceedings of the AAAI conference on artificial intelligence, Vol. 33. 9662\u20139669."},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 14948\u201314957","author":"Li Boyi","year":"2024","unstructured":"Boyi Li, Yue Wang, Jiageng Mao, Boris Ivanovic, Sushant Veer, Karen Leung, and Marco Pavone. 2024. Driving everywhere with large language model policy adaptation. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 14948\u201314957."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","unstructured":"Yuebing Liang Yichao Liu Xiaohan Wang and Zhan Zhao. 2024. Exploring large language models for human mobility prediction under public events. 102153 pages.","DOI":"10.1016\/j.compenvurbsys.2024.102153"},{"key":"e_1_3_2_1_16_1","volume-title":"LLM comparative assessment: Zero-shot NLG evaluation through pairwise comparisons using large language models. arXiv preprint arXiv:2307.07889","author":"Liusie Adian","year":"2023","unstructured":"Adian Liusie, Potsawee Manakul, and Mark JF Gales. 2023. LLM comparative assessment: Zero-shot NLG evaluation through pairwise comparisons using large language models. arXiv preprint arXiv:2307.07889 (2023)."},{"key":"e_1_3_2_1_17_1","volume-title":"Redefining Chinese city system with emerging new data. Applied geography 75","author":"Long Ying","year":"2016","unstructured":"Ying Long. 2016. Redefining Chinese city system with emerging new data. Applied geography 75 (2016), 36\u201348."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tra.2010.02.001"},{"key":"e_1_3_2_1_19_1","volume-title":"International Encyclopedia of Geography: People, the Earth, Environment and Technology","author":"Mai Gengchen","year":"2024","unstructured":"Gengchen Mai. 2024. Geo-Foundation Models. International Encyclopedia of Geography: People, the Earth, Environment and Technology (2024), 1\u201314."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","first-page":"100170","DOI":"10.1016\/j.commtr.2025.100170","article-title":"Lc-llm: Explainable lane-change intention and trajectory predictions with large language models","volume":"5","author":"Peng Mingxing","year":"2025","unstructured":"Mingxing Peng, Xusen Guo, Xianda Chen, Kehua Chen, Meixin Zhu, Long Chen, and Fei-Yue Wang. 2025. Lc-llm: Explainable lane-change intention and trajectory predictions with large language models. Communications in Transportation Research 5 (2025), 100170.","journal-title":"Communications in Transportation Research"},{"key":"e_1_3_2_1_21_1","volume-title":"International conference on machine learning. PmLR, 8748\u20138763","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. 2021. Learning transferable visual models from natural language supervision. In International conference on machine learning. PmLR, 8748\u20138763."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2022.106836"},{"key":"e_1_3_2_1_23_1","volume-title":"Mohammed Eunus Ali, Adel N Toosi, and Hesham A Rakha.","author":"Sohail Ammar","year":"2023","unstructured":"Ammar Sohail, Muhammad Aamir Cheema, Mohammed Eunus Ali, Adel N Toosi, and Hesham A Rakha. 2023. Data-driven approaches for road safety: A comprehensive systematic literature review. Safety science 158 (2023), 105949."},{"key":"e_1_3_2_1_24_1","volume-title":"2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 468\u2013475","author":"Sural Shounak","year":"2024","unstructured":"Shounak Sural, Ragunathan Raj Rajkumar, et al. 2024. Contextvlm: Zero-shot and few-shot context understanding for autonomous driving using vision language models. In 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 468\u2013475."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.5038\/2375-0901.14.1.6"},{"key":"e_1_3_2_1_26_1","volume-title":"Accidentgpt: Accident analysis and prevention from v2x environmental perception with multimodal large model. arXiv preprint arXiv:2312.13156","author":"Wang Lening","year":"2023","unstructured":"Lening Wang, Yilong Ren, Han Jiang, Pinlong Cai, Daocheng Fu, Tianqi Wang, Zhiyong Cui, Haiyang Yu, Xuesong Wang, Hanchu Zhou, et al. 2023. Accidentgpt: Accident analysis and prevention from v2x environmental perception with multimodal large model. arXiv preprint arXiv:2312.13156 (2023)."},{"key":"e_1_3_2_1_27_1","volume-title":"Global status report on road safety","author":"WHO.","year":"2023","unstructured":"WHO. 2023. Global status report on road safety 2023. Technical Report. World Health Organization. https:\/\/www.who.int\/publications\/i\/item\/9789240086517"},{"key":"e_1_3_2_1_28_1","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"39","author":"Xu Yunzhe","year":"2025","unstructured":"Yunzhe Xu, Yiyuan Pan, Zhe Liu, and Hesheng Wang. 2025. Flame: Learning to navigate with multimodal llm in urban environments. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 39. 9005\u20139013."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3589334.3645378"},{"key":"e_1_3_2_1_30_1","volume-title":"Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting. arXiv preprint arXiv:1709.04875","author":"Yu Bing","year":"2017","unstructured":"Bing Yu, Haoteng Yin, and Zhanxing Zhu. 2017. Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting. arXiv preprint arXiv:1709.04875 (2017)."},{"key":"e_1_3_2_1_31_1","volume-title":"Temporal data meets LLM-explainable financial time series forecasting. arXiv preprint arXiv:2306.11025","author":"Yu Xinli","year":"2023","unstructured":"Xinli Yu, Zheng Chen, Yuan Ling, Shujing Dong, Zongyi Liu, and Yanbin Lu. 2023. Temporal data meets LLM-explainable financial time series forecasting. arXiv preprint arXiv:2306.11025 (2023)."}],"event":{"name":"GeoAI '25: 8th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery","location":"The Graduate Hotel Minneapolis Minneapolis MN USA","acronym":"GeoAI '25","sponsor":["SIGSPATIAL ACM Special Interest Group on Spatial Information"]},"container-title":["Proceedings of the 8th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3764912.3770832","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T13:52:09Z","timestamp":1766152329000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3764912.3770832"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,3]]},"references-count":31,"alternative-id":["10.1145\/3764912.3770832","10.1145\/3764912"],"URL":"https:\/\/doi.org\/10.1145\/3764912.3770832","relation":{},"subject":[],"published":{"date-parts":[[2025,11,3]]},"assertion":[{"value":"2025-12-19","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}