{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T12:11:47Z","timestamp":1767183107568,"version":"3.37.3"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,12,3]],"date-time":"2022-12-03T00:00:00Z","timestamp":1670025600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,12,3]],"date-time":"2022-12-03T00:00:00Z","timestamp":1670025600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. ITS Res."],"published-print":{"date-parts":[[2023,4]]},"DOI":"10.1007\/s13177-022-00334-0","type":"journal-article","created":{"date-parts":[[2022,12,3]],"date-time":"2022-12-03T09:03:28Z","timestamp":1670058208000},"page":"48-62","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Reinforcement Learning Based Control Scheme for Emergency Vehicle Preemption with Edge Computing"],"prefix":"10.1007","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6057-8793","authenticated-orcid":false,"given":"Prakash","family":"Rosayyan","sequence":"first","affiliation":[]},{"given":"Jasmine","family":"Paul","sequence":"additional","affiliation":[]},{"given":"Senthilkumar","family":"Subramaniam","sequence":"additional","affiliation":[]},{"given":"Saravana Ilango","family":"Ganesan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,12,3]]},"reference":[{"issue":"1","key":"334_CR1","doi-asserted-by":"publisher","first-page":"142","DOI":"10.3109\/10903127.2011.614046","volume":"16","author":"E Ian","year":"2012","unstructured":"Ian, E., Blanchard, C.J., Doig, B.E., Hagel, A.R., Anton, D.A., Zygun, J.B., Kortbeek, D., Gregory Powell, T.S., Williamson, G.H., Fick, Grant, D., Innes: Emergency medical services response time and mortality in an urban setting. Prehospital Emerg. Care 16(1), 142\u2013151 (2012). https:\/\/doi.org\/10.3109\/10903127.2011.614046","journal-title":"Prehospital Emerg. Care"},{"key":"334_CR2","doi-asserted-by":"crossref","unstructured":"He, Q., Head, K.L., Ding, J.: Multi-modal traffic signal control with priority, signal actuation and coordination. Transp. Res. Part C.\u00a046, 65\u201382 (2014)","DOI":"10.1016\/j.trc.2014.05.001"},{"key":"334_CR3","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/j.trb.2014.03.004","volume":"64","author":"SI Guler","year":"2014","unstructured":"Guler, S.I., Menendez, M.: Analytical formulation and empirical evaluation of pre-signals for bus priority. Transp. Res. Part. B 64, 41\u201353 (2014)","journal-title":"Transp. Res. Part. B"},{"key":"334_CR4","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1016\/j.trb.2013.11.003","volume":"66","author":"MG Bell","year":"2014","unstructured":"Bell, M.G., Fonzone, A., Polyzoni, C.: Depot location in degradable transport networks. Transp. Res Part B 66, 148\u2013161 (2014)","journal-title":"Transp. Res Part B"},{"key":"334_CR5","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.trb.2015.02.014","volume":"75","author":"JJ Salazar-Gonz\u00e1lez","year":"2015","unstructured":"Salazar-Gonz\u00e1lez, J.J., Santos-Hern\u00e1ndez, B.: The split-demand one-commodity pickup-and-delivery travelling salesman problem. Transp. Res. Part. B 75, 58\u201373 (2015)","journal-title":"Transp. Res. Part. B"},{"key":"334_CR6","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.trb.2018.11.012","volume":"119","author":"K Liu","year":"2019","unstructured":"Liu, K., Li, Q., Zhang, Z.H.: Distributionally robust optimization of an emergency medical service station location and sizing problem with joint chance constraints. Transp. Res. Part. B 119, 79\u2013101 (2019)","journal-title":"Transp. Res. Part. B"},{"issue":"5","key":"334_CR7","doi-asserted-by":"publisher","first-page":"1409","DOI":"10.1287\/trsc.2019.0891","volume":"53","author":"Q He","year":"2019","unstructured":"He, Q., Irnich, S., Song, Y.: Branch-and-cut-and-price for the vehicle routing problem with time windows and convex node costs. Transp. Sci 53(5), 1409\u20131426 (2019)","journal-title":"Transp. Sci"},{"issue":"1","key":"334_CR8","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1287\/trsc.2015.0610","volume":"51","author":"S Ansari","year":"2015","unstructured":"Ansari, S., McLay, L.A., Mayorga, M.E.: A maximum expected covering problem for district design. Transp. Sci 51(1), 376\u2013390 (2015)","journal-title":"Transp. Sci"},{"issue":"4","key":"334_CR9","doi-asserted-by":"publisher","first-page":"2113","DOI":"10.1109\/TITS.2015.2395419","volume":"16","author":"YS Huang","year":"2015","unstructured":"Huang, Y.S., Weng, Y.S., Zhou, M.: Design of traffic safety control systems for emergency vehicle preemption using timed petri nets. IEEE Trans. Intell. Transp. Syst 16(4), 2113\u20132120 (2015)","journal-title":"IEEE Trans. Intell. Transp. Syst"},{"issue":"9","key":"334_CR10","doi-asserted-by":"publisher","first-page":"3546","DOI":"10.1109\/TITS.2018.2877758","volume":"20","author":"GJ Hannoun","year":"2018","unstructured":"Hannoun, G.J., Murray-Tuite, P., Heaslip, K., Chantem, T.: Facilitating emergency response vehicles\u2019 movement through a road segment in a connected vehicle environment. IEEE Trans. Intell. Transp. Syst 20(9), 3546\u20133557 (2018)","journal-title":"IEEE Trans. Intell. Transp. Syst"},{"key":"334_CR11","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1016\/j.trb.2013.11.005","volume":"59","author":"D Chen","year":"2014","unstructured":"Chen, D., Ahn, S., Laval, J., Zheng, Z.: On the periodicity of traffic oscillations and capacity drop: the role of driver characteristics. Transp. Res. Part. B 59, 117\u2013136 (2014)","journal-title":"Transp. Res. Part. B"},{"key":"334_CR12","doi-asserted-by":"publisher","unstructured":"Rosayyan, P., Subramaniam, S., Ganesan, S.I.: Decentralized emergency service vehicle pre-emption system using RF communication and GNSS-based geo- fencing.\u00a0IEEE Transactions on Intelligent Transportation Systems, pp. 1\u201310. https:\/\/doi.org\/10.1109\/TITS.2020.3007671","DOI":"10.1109\/TITS.2020.3007671"},{"issue":"3","key":"334_CR13","doi-asserted-by":"publisher","first-page":"1826","DOI":"10.1109\/COMST.2018.2814571","volume":"20","author":"M Mukherjee","year":"2018","unstructured":"Mukherjee, M., Shu, L., Wang, D.: Survey of fog omputing: fundamental, network applications, and research challenges. IEEE Commun. Surv. Tutor 20(3), 1826\u20131857 (2018)","journal-title":"IEEE Commun. Surv. Tutor"},{"key":"334_CR14","doi-asserted-by":"publisher","first-page":"825","DOI":"10.1016\/j.future.2019.02.058","volume":"97","author":"Q Wu","year":"2019","unstructured":"Wu, Q., Shen, J., Yong, B., Wu, J., Li, F., Wang, J., Zhou, Q.: Smart fog based workflow for traffic control networks. Future Gener. Comput. Syst 97, 825\u2013835 (2019)","journal-title":"Future Gener. Comput. Syst"},{"key":"334_CR15","doi-asserted-by":"publisher","first-page":"817","DOI":"10.1016\/j.future.2017.02.017","volume":"78","author":"J Liu","year":"2017","unstructured":"Liu, J., Li, L., Zhang, F., Dai, Y., Zhang, X., Meng, J., Shen: Secure intelligent traffic light control using fog computing. Future Gener. Comput. Syst 78, 817\u2013824 (2017). https:\/\/doi.org\/10.1016\/j.future.2017.02.017","journal-title":"Future Gener. Comput. Syst"},{"key":"334_CR16","doi-asserted-by":"publisher","unstructured":"Jinjian, L., Jacques, B., Arnaud, D., Guillaume, L.: Multi-models machine learning methods for traffic flow estimation from floating car data. Transp. Res. Part C: Emerg Technol. 132 (2021). https:\/\/doi.org\/10.1016\/j.trc.2021.103389","DOI":"10.1016\/j.trc.2021.103389"},{"key":"334_CR17","doi-asserted-by":"publisher","unstructured":"Posor, J.E., Belzner, L., Knapp, A.: Joint action learning for multi-agent cooperation using recurrent reinforcement learning. Digitale Welt. 479\u201384 (2020). https:\/\/doi.org\/10.1007\/s42354-019-0239-y","DOI":"10.1007\/s42354-019-0239-y"},{"key":"334_CR18","unstructured":"Sunehag, P., et al.: Value-decomposition networks for cooperative multi-agent learning, 2017, arXiv preprint arXiv:1706.05296, https:\/\/arxiv.org\/abs\/1706.05296"},{"issue":"5","key":"334_CR19","doi-asserted-by":"publisher","first-page":"4671","DOI":"10.1109\/JIOT.2019.2923611","volume":"7","author":"MA Saleem","year":"2020","unstructured":"Saleem, M.A., Mahmood, K., Kumari, S.: Comments on AKM-IoV: Authenticated key management protocol in fog computing-based internet of vehicles deployment. IEEE Internet Things J 7(5), 4671\u20134675 (2020). https:\/\/doi.org\/10.1109\/JIOT.2019.2923611","journal-title":"IEEE Internet Things J"},{"issue":"7","key":"334_CR20","doi-asserted-by":"publisher","first-page":"4235","DOI":"10.1109\/TII.2019.2902878","volume":"15","author":"AH Sodhro","year":"2019","unstructured":"Sodhro, A.H., Pirbhulal, S., de Albuquerque, V.H.C.: Artificial intelligence driven mechanism for edge computing-based industrial applications. IEEE Trans. Ind. Inform 15(7), 4235\u20134243 (2019). https:\/\/doi.org\/10.1109\/TII.2019.2902878","journal-title":"IEEE Trans. Ind. Inform"},{"issue":"5","key":"334_CR21","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1109\/JIOT.2016.2579198","volume":"3","author":"W Shi","year":"2016","unstructured":"Shi, W., Cao, J., Zhang, Q., Li, Y., Xu, L.: Edge computing: vision and challenges. IEEE Internet Things J 3(5), 637\u2013646 (2016)","journal-title":"IEEE Internet Things J"},{"key":"334_CR22","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1016\/j.neucom.2020.05.097","volume":"411","author":"F Zhang","year":"2020","unstructured":"Zhang, F., Li, J., Li, Z.: A TD3-based multi-agent deep reinforcement learning method in mixed cooperation- competition environment. Neurocomputing 411, 206\u2013215 (2020)","journal-title":"Neurocomputing"},{"key":"334_CR23","doi-asserted-by":"publisher","unstructured":"Cao, W., Xu, S., An emergency warning message dissemination policy of vehicular ad hoc network: 9th International Symposium on Computational Intelligence and Design (ISCID), 2016, pp. 227\u2013230 (2016). https:\/\/doi.org\/10.1109\/ISCID.2016.2061","DOI":"10.1109\/ISCID.2016.2061"},{"key":"334_CR24","doi-asserted-by":"crossref","unstructured":"Hollinghurst, J., Ganesh, A., Baug\u00e9, T.: Latency reduction in communication networks using redundant messages. Paper presented at: Proceedings of the 2017 29th International Teletraffic Congress (ITC 29), pp. 241\u2013249. (2017)","DOI":"10.23919\/ITC.2017.8064361"},{"issue":"50","key":"334_CR25","first-page":"35","volume":"1","author":"S Kausar","year":"2020","unstructured":"Kausar, S., Habib, M., Shabir, M.Y., et al.: Secure and efficient data transfer using spreading and assimilation in MANET. Softw. Pract. Exp 1(50), 35\u201350 (2020)","journal-title":"Softw. Pract. Exp"},{"key":"334_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.knosys.2019.105201","volume":"196","author":"X Wu","year":"2020","unstructured":"Wu, X., Chen, H., Chen, C., Zhong, M., Xie, S., Guo, Y., Fujita, H.: The autonomous navigation and obstacle avoidance for USVs with ANOA deep reinforcement learning method. Knowl. -Based Syst 196, 1\u201312 (2020)","journal-title":"Knowl. -Based Syst"},{"key":"334_CR27","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.knosys.2019.07.026","volume":"183","author":"S Yang","year":"2019","unstructured":"Yang, S., Yang, B., Wong, H., Kang, Z.: Cooperative traffic signal control using multi-step return and off-policy asynchronous advantage actor-critic graph algorithm. Knowl. -Based Syst 183, 1\u201319 (2019)","journal-title":"Knowl. -Based Syst"},{"key":"334_CR28","first-page":"431","volume":"109","author":"F Rasheed","year":"2020","unstructured":"Rasheed, F., Yau, K.A., Low, Y.: Deep reinforcement learning for traffic signal control under disturbances: a case study on sunway city, Malaysia, Future Gener. Comput. Syst 109, 431\u2013445 (2020)","journal-title":"Comput. Syst"},{"key":"334_CR29","doi-asserted-by":"crossref","unstructured":"Wang, H., Li, J., Chen, Q.Y., Ni, D.: Logistic modeling of equilibrium speed\u2013density relationship. Transp. Res. Part A: Policy Pract 45, 554\u2013566 (2011)","DOI":"10.1016\/j.tra.2011.03.010"},{"key":"334_CR30","doi-asserted-by":"crossref","unstructured":"Wei, H., Chen, C., Zheng, G., Wu, K., Gayah, V., Xu, K., Li, Z., Presslight: Learning max pressure control to coordinate traffic signals in arterial network. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 1290\u20131298 (2019)","DOI":"10.1145\/3292500.3330949"},{"key":"334_CR31","doi-asserted-by":"publisher","unstructured":"Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning representations by back-propagating errors. Nature 323, 533\u2013536 (1986). https:\/\/doi.org\/10.1038\/323533a0","DOI":"10.1038\/323533a0"},{"key":"334_CR32","unstructured":"Lowe, R., Wu, Y., Tamar, A., Harb, J., Abbeel, O.P., Mordatch, I.: Multi-agent actor-critic for mixed cooperative- competitive environments. In: Advances in Neural Information Processing Systems, pp. 6379\u20136390 (2017)"},{"key":"334_CR33","unstructured":"Fedesoriano.: Traffic Prediction Dataset, Version 1. Retrieved November 2021 from https:\/\/www.kaggle.com\/fedesoriano\/traffic-prediction-dataset (2021)"},{"key":"334_CR34","doi-asserted-by":"crossref","unstructured":"Haizhong, W., Jia, L., Qian-Yong, C., Daiheng, N., Logistic modeling of the equilibrium speed\u2013density relationship. Transp. Res. Part A: Policy Pract. 45(6), 554\u2013566 (2011)","DOI":"10.1016\/j.tra.2011.03.010"}],"container-title":["International Journal of Intelligent Transportation Systems Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13177-022-00334-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13177-022-00334-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13177-022-00334-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T07:44:34Z","timestamp":1679643874000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13177-022-00334-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,3]]},"references-count":34,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["334"],"URL":"https:\/\/doi.org\/10.1007\/s13177-022-00334-0","relation":{},"ISSN":["1348-8503","1868-8659"],"issn-type":[{"type":"print","value":"1348-8503"},{"type":"electronic","value":"1868-8659"}],"subject":[],"published":{"date-parts":[[2022,12,3]]},"assertion":[{"value":"10 December 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 October 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 November 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 December 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The Authors declared that there is no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}}]}}