{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T18:38:59Z","timestamp":1742927939092,"version":"3.40.3"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031170973"},{"type":"electronic","value":"9783031170980"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-17098-0_17","type":"book-chapter","created":{"date-parts":[[2022,9,27]],"date-time":"2022-09-27T14:19:41Z","timestamp":1664288381000},"page":"330-347","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Detecting Extended Incidents in Urban Road Networks for Organic Traffic Control Using Density-Based Clustering of Traffic Flows"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0850-4786","authenticated-orcid":false,"given":"Ingo","family":"Thomsen","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5825-8915","authenticated-orcid":false,"given":"Sven","family":"Tomforde","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,9,28]]},"reference":[{"key":"17_CR1","unstructured":"Aimsun SLU: Aimsun Next Professional, Version 22. Barcelona, Spain (2021). http:\/\/www.aimsun.com\/"},{"key":"17_CR2","unstructured":"Berndt, D.J., Clifford, J. (eds.): Using dynamic time warping to find patterns in time series, vol. 10. Seattle, WA, USA (1994)"},{"key":"17_CR3","doi-asserted-by":"publisher","unstructured":"Breunig, M.M., Kriegel, H.P., Ng, R.T., Sander, J.: LOF. In: Dunham, M., Naughton, J.F., Chen, W., Koudas, N. (eds.) Proceedings of the 2000 ACM SIGMOD international conference on Management of data - SIGMOD 2000, pp. 93\u2013104. ACM Press, New York (2000). https:\/\/doi.org\/10.1145\/342009.335388","DOI":"10.1145\/342009.335388"},{"key":"17_CR4","doi-asserted-by":"publisher","unstructured":"Dogru, N., Subasi, A.: Traffic accident detection using random forest classifier. In: 2018 15th Learning and Technology Conference (L T), pp. 40\u201345 (2018). https:\/\/doi.org\/10.1109\/LT.2018.8368509","DOI":"10.1109\/LT.2018.8368509"},{"key":"17_CR5","doi-asserted-by":"crossref","unstructured":"Dusparic, I., Cahill, V.: Using distributed w-learning for multi-policy optimization in decentralized autonomic systems. In: Proceedings of 6th International Conference on Autonomic Computing, pp. 63\u201364. ACM (2009)","DOI":"10.1145\/1555228.1555247"},{"key":"17_CR6","unstructured":"Ester, M., Kriegel, H.P., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise, pp. 226\u2013231. AAAI Press (1996)"},{"issue":"3","key":"17_CR7","doi-asserted-by":"publisher","first-page":"714","DOI":"10.1109\/TITS.2010.2050688","volume":"11","author":"B Gokulan","year":"2010","unstructured":"Gokulan, B., Srinivasan, D.: Distributed geometric fuzzy multiagent urban traffic signal control. IEEE Trans. Int. Transp. Syst. 11(3), 714\u2013727 (2010)","journal-title":"IEEE Trans. Int. Transp. Syst."},{"key":"17_CR8","doi-asserted-by":"crossref","unstructured":"Helbing, D., L\u00e4mmer, S., Lebacque, J.: Self-organized control of irregular or perturbed network traffic. Optimal control and dynamic games, pp. 239\u2013274 (2005)","DOI":"10.1007\/0-387-25805-1_15"},{"key":"17_CR9","doi-asserted-by":"crossref","unstructured":"Mauro, V., Taranto, C.D.: Utopia. Control, computers, communications in transportation (1990)","DOI":"10.1016\/B978-0-08-037025-5.50042-6"},{"key":"17_CR10","series-title":"Autonomic Systems","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-68477-2","volume-title":"Organic Computing \u2013 Technical Systems for Survival in the Real World","author":"C M\u00fcller-Schloer","year":"2017","unstructured":"M\u00fcller-Schloer, C., Tomforde, S.: Organic Computing \u2013 Technical Systems for Survival in the Real World. AS, Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-68477-2"},{"issue":"1","key":"17_CR11","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.trc.2009.04.022","volume":"18","author":"LD Oliveira","year":"2010","unstructured":"Oliveira, L.D., Camponogara, E.: Multi-agent model predictive control of signaling split in urban traffic networks. Transp. Res. Part C: Emerg. Tech. 18(1), 120\u2013139 (2010)","journal-title":"Transp. Res. Part C: Emerg. Tech."},{"key":"17_CR12","unstructured":"Parkany, E., Xie, C.: A complete review of incident detection algorithms & their deployment: what works and what doesn\u2019t (2005). https:\/\/www.dot.ny.gov\/gisapps\/roadway-inventory-system-viewer"},{"key":"17_CR13","unstructured":"Payne, H.J., Tignor, S.C.: Freeway incident-detection algorithms based on decision trees with states. In: Urban system operation and freeways. Transportation research record, National Academy of Sciences, Washington, DC (1978)"},{"issue":"1","key":"17_CR14","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1109\/25.69966","volume":"40","author":"D Robertson","year":"1991","unstructured":"Robertson, D., Bretherton, D.: Optimizing networks of traffic signals in real time - the SCOOT method. IEEE Trans. Veh. Tech. 40(1), 11\u201315 (1991)","journal-title":"IEEE Trans. Veh. Tech."},{"issue":"2","key":"17_CR15","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1109\/T-VT.1980.23833","volume":"29","author":"A Sims","year":"1980","unstructured":"Sims, A., Dobinson, K.: The Sydney coordinated adaptive traffic (SCAT) system - philosophy and benefits. IEEE Trans. Veh. Tech. 29(2), 130\u2013137 (1980)","journal-title":"IEEE Trans. Veh. Tech."},{"key":"17_CR16","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1007\/978-3-319-25808-9_7","volume-title":"Autonomic Road Transport Support Systems","author":"M Sommer","year":"2016","unstructured":"Sommer, M., Tomforde, S., H\u00e4hner, J.: An organic computing approach to resilient traffic management. In: McCluskey, T.L., Kotsialos, A., M\u00fcller, J.P., Kl\u00fcgl, F., Rana, O., Schumann, R. (eds.) Autonomic Road Transport Support Systems, pp. 113\u2013130. Birkh\u00e4user, Basel (2016)"},{"issue":"195","key":"17_CR17","first-page":"2","volume":"5","author":"L Studer","year":"2015","unstructured":"Studer, L., Ketabdari, M., Marchionni, G.: Analysis of adaptive traffic control systems design of a decision support system for better choices. J. Civil Environ. Eng. 5(195), 2 (2015)","journal-title":"J. Civil Environ. Eng."},{"key":"17_CR18","doi-asserted-by":"publisher","unstructured":"Sun, L., Lin, Z., Li, W., Xiang, Y.: Freeway incident detection based on set theory and short-range communication. Transp. Lett. 11(10), 558\u2013569 (2019). https:\/\/doi.org\/10.1080\/19427867.2018.1453273. https:\/\/doi.org\/10.1080\/19427867.2018.1453273","DOI":"10.1080\/19427867.2018.1453273"},{"key":"17_CR19","unstructured":"Thomsen, I.: Incident-aware resilient traffic management for urban road networks. In: Organic Computing: Doctoral Dissertation Colloquium 2020, pp. 125\u2013138. kassel University Press GmbH (2011)"},{"key":"17_CR20","doi-asserted-by":"publisher","unstructured":"Thomsen., I., Zapfe., Y., Tomforde., S.: Urban traffic incident detection for organic traffic control: a density-based clustering approach. In: Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS, pp. 152\u2013160. INSTICC, SciTePress (2021). https:\/\/doi.org\/10.5220\/0010454101520160","DOI":"10.5220\/0010454101520160"},{"key":"17_CR21","doi-asserted-by":"publisher","unstructured":"Tomforde, S., et al.: Decentralised progressive signal systems for organic traffic control. In: 2008 Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems, pp. 413\u2013422. IEEE (2008). https:\/\/doi.org\/10.1109\/SASO.2008.31","DOI":"10.1109\/SASO.2008.31"},{"key":"17_CR22","unstructured":"Vincent, R., Peirce, J., Webb, P.: MOVA traffic control manual (1990)"},{"key":"17_CR23","doi-asserted-by":"crossref","unstructured":"Yao, Y., Xu, M., Wang, Y., Crandall, D.J., Atkins, E.M.: Unsupervised traffic accident detection in first-person videos. CoRR abs\/1903.00618 (2019). http:\/\/arxiv.org\/abs\/1903.00618","DOI":"10.1109\/IROS40897.2019.8967556"}],"container-title":["Communications in Computer and Information Science","Smart Cities, Green Technologies, and Intelligent Transport Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-17098-0_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,27]],"date-time":"2022-09-27T14:25:46Z","timestamp":1664288746000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-17098-0_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031170973","9783031170980"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-17098-0_17","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"28 September 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"VEHITS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Vehicle Technology and Intelligent Transport Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 April 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 April 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icvti2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/vehits.scitevents.org\/?y=2021","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"PRIMORIS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"108","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"13","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"12% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}