{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T10:06:35Z","timestamp":1784801195978,"version":"3.55.0"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T00:00:00Z","timestamp":1778716800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T00:00:00Z","timestamp":1778716800000},"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":[[2026,8]]},"DOI":"10.1007\/s13177-026-00669-y","type":"journal-article","created":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T07:59:04Z","timestamp":1778745544000},"page":"1527-1542","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-Objective Reinforcement Learning With Physics-Aware Vehicle Dynamics for Safe and Efficient Adaptive Cruise Control"],"prefix":"10.1007","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8929-525X","authenticated-orcid":false,"given":"Haneesh","family":"K. M.","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1596-3657","authenticated-orcid":false,"given":"Jisha","family":"P","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,14]]},"reference":[{"issue":"1","key":"669_CR1","doi-asserted-by":"publisher","first-page":"688","DOI":"10.1109\/TIE.2023.3239878","volume":"71","author":"Y Zhang","year":"2023","unstructured":"Zhang, Y., Lin, Y., Qin, Y., Dong, M., Gao, L., Hashemi, E.: A new adaptive cruise control considering crash avoidance for intelligent vehicle. IEEE Trans. Ind. Electron. 71(1), 688\u2013696 (2023)","journal-title":"IEEE Trans. Ind. Electron."},{"key":"669_CR2","doi-asserted-by":"publisher","first-page":"13636","DOI":"10.1109\/ACCESS.2023.3241140","volume":"11","author":"S Vasebi","year":"2023","unstructured":"Vasebi, S., Hayeri, Y.M., Saghiri, A.M.: A literature review of energy optimal adaptive cruise control algorithms. IEEE Access 11, 13636\u201313646 (2023)","journal-title":"IEEE Access"},{"issue":"10","key":"669_CR3","doi-asserted-by":"publisher","first-page":"7084","DOI":"10.1080\/03772063.2021.2012282","volume":"69","author":"S Chaturvedi","year":"2023","unstructured":"Chaturvedi, S., Kumar, N.: Design and implementation of an optimized PID controller for the adaptive cruise control system. IETE J. Res. 69(10), 7084\u20137091 (2023)","journal-title":"IETE J. Res."},{"issue":"12","key":"669_CR4","doi-asserted-by":"publisher","first-page":"751","DOI":"10.3390\/fractalfract8120751","volume":"8","author":"DE Elgezouli","year":"2024","unstructured":"Elgezouli, D.E., Eltayeb, H., Abdoon, M.A.: Novel GPID: Gr\u00fcnwald-Letnikov fractional PID for enhanced adaptive cruise control. Fractal Fract. 8(12), 751 (2024)","journal-title":"Fractal Fract."},{"issue":"9","key":"669_CR5","doi-asserted-by":"publisher","first-page":"1658","DOI":"10.1109\/JAS.2022.105806","volume":"9","author":"H Mo","year":"2022","unstructured":"Mo, H., Meng, Y., Wang, F.-Y., Wu, D.: Interval type-2 fuzzy hierarchical adaptive cruise following-control for intelligent vehicles. IEEE\/CAA J. Autom. Sin. 9(9), 1658\u20131672 (2022)","journal-title":"IEEE\/CAA J. Autom. Sin."},{"key":"669_CR6","doi-asserted-by":"publisher","first-page":"109008","DOI":"10.1016\/j.engappai.2024.109008","volume":"136","author":"Z Mehraban","year":"2024","unstructured":"Mehraban, Z., Zadeh, A.Y., Khayyam, H., Mallipeddi, R., Jamali, A.: Fuzzy adaptive cruise control with model predictive control responding to dynamic traffic conditions for automated driving. Eng. Appl. Artif. Intell. 136, 109008 (2024)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"669_CR7","doi-asserted-by":"publisher","unstructured":"Quan,Y.S., Kim, J.S., Chung, C.C.: Robust adaptive cruise control design using model predictive control. IEEE Trans. Intell. Veh. Early Access. 1\u201310 (2024). https:\/\/doi.org\/10.1109\/TIV.2024.3411012","DOI":"10.1109\/TIV.2024.3411012"},{"key":"669_CR8","doi-asserted-by":"publisher","first-page":"103801","DOI":"10.1016\/j.trc.2022.103801","volume":"142","author":"H Zhou","year":"2022","unstructured":"Zhou, H., Zhou, A., Li, T., Chen, D., Peeta, S., Laval, J.: Congestion-mitigating MPC design for adaptive cruise control based on Newell\u2019s car following model: history outperforms prediction. Transp. Res. C Emerg. Technol. 142, 103801 (2022)","journal-title":"Transp. Res. C Emerg. Technol."},{"issue":"12","key":"669_CR9","doi-asserted-by":"publisher","first-page":"5722","DOI":"10.3390\/s23125722","volume":"23","author":"J Guo","year":"2023","unstructured":"Guo, J., Wang, Y., Chu, L., Bai, C., Hou, Z., Zhao, D.: Adaptive cruise system based on fuzzy MPC and machine learning state observer. Sensors 23(12), 5722 (2023)","journal-title":"Sensors"},{"issue":"3","key":"669_CR10","doi-asserted-by":"publisher","first-page":"1974","DOI":"10.1109\/TIV.2024.3440643","volume":"10","author":"P Xue","year":"2024","unstructured":"Xue,P., Yan, Y., Wang, H., Sun, P., Sun, X., Liu, Y., Wang, X., Pi, D.: A real-time dynamic adjustment cooperative adaptive cruise control method based on fuzzy-robust MPC. IEEE Trans. Intell. Veh. 10(3), 1974\u20131988 (2024). https:\/\/doi.org\/10.1109\/TIV.2024.3440643","journal-title":"IEEE Trans. Intell. Veh."},{"key":"669_CR11","doi-asserted-by":"publisher","first-page":"103305","DOI":"10.1016\/j.trc.2021.103305","volume":"130","author":"B Ciuffo","year":"2021","unstructured":"Ciuffo, B., Mattas, K., Makridis, M., Albano, G., Anesiadou, A., He, Y., Josvai, S., et al.: Requiem on the positive effects of commercial adaptive cruise control on motorway traffic and recommendations for future automated driving systems. Transp. Res. Part C Emerg. Technol. 130, 103305 (2021)","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"669_CR12","doi-asserted-by":"publisher","first-page":"234292","DOI":"10.1016\/j.jpowsour.2024.234292","volume":"601","author":"Q Su","year":"2024","unstructured":"Su, Q., Huang, R., He, H.: Heterogeneous multi-agent deep reinforcement learning for eco-driving of hybrid electric tracked vehicles: a heuristic training framework. J. Power. Sources 601, 234292 (2024)","journal-title":"J. Power. Sources"},{"issue":"6","key":"669_CR13","doi-asserted-by":"publisher","first-page":"7603","DOI":"10.1109\/TVT.2024.3352543","volume":"73","author":"J Liu","year":"2024","unstructured":"Liu, J., Cui, Y., Duan, J., Jiang, Z., Pan, Z., Xu, K., Li, H.: Reinforcement learning-based high-speed path following control for autonomous vehicles. IEEE Trans. Veh. Technol. 73(6), 7603\u20137615 (2024)","journal-title":"IEEE Trans. Veh. Technol."},{"issue":"10","key":"669_CR14","doi-asserted-by":"publisher","first-page":"6436","DOI":"10.1109\/TIV.2024.3368025","volume":"9","author":"D Chen","year":"2024","unstructured":"Chen,D., Zhang, K., Wang, Y., Yin, X., Li, Z., Filev, D.: Communication-efficient decentralized multi-agent reinforcement learning for cooperative adaptive cruise control. IEEE Trans. Intell. Veh. 9(10), 6436\u20136449 (2024). https:\/\/doi.org\/10.1109\/TIV.2024.3368025","journal-title":"IEEE Trans. Intell. Veh."},{"issue":"1","key":"669_CR15","doi-asserted-by":"publisher","first-page":"835","DOI":"10.1109\/TITS.2024.3488519","volume":"26","author":"J Liang","year":"2025","unstructured":"Liang,J., Yang, K., Tan, C., Wang, J., Yin, G.: Enhancing high-speed cruising performance of autonomous vehicles through integrated deep reinforcement learning framework. IEEE Trans. Intell. Transp. Syst. 26(1), 835\u2013848 (2025). https:\/\/doi.org\/10.1109\/TITS.2024.3488519","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"669_CR16","doi-asserted-by":"crossref","unstructured":"Li, P., Yang, S., Lu, Y., Ming, X., Qi, W., Huang, Y.: An adaptive MPC based on RL for vehicle longitudinal control. In: 2024 8th CAA International Conference on Vehicular Control and Intelligence (CVCI), pp. 1\u20136. IEEE, (2024)","DOI":"10.1109\/CVCI63518.2024.10830092"},{"issue":"1","key":"669_CR17","doi-asserted-by":"publisher","first-page":"3667","DOI":"10.1109\/TTE.2024.3429186","volume":"11","author":"H Liu","year":"2025","unstructured":"Liu,H., Sun, J., Wang, H., Cheng, K.W.E.: Comprehensive analysis of adaptive soft actor-critic reinforcement learning-based control framework for autonomous driving in varied scenarios. IEEE Trans. Trans. Electrific. 11(1), 3667\u20133679 (2025). https:\/\/doi.org\/10.1109\/TTE.2024.3429186","journal-title":"IEEE Trans. Trans. Electrific"},{"issue":"4","key":"669_CR18","doi-asserted-by":"publisher","first-page":"505","DOI":"10.4271\/12-08-04-0033","volume":"8","author":"F Javidi-Niroumand","year":"2025","unstructured":"Javidi-Niroumand,F., Sargolzaei, A.: A reinforcement learning-based parameter tuning approach for a secure cooperative adaptive cruise control system. SAE Int. J. Connect. Automat Veh. 8(4), 505\u2013522 (2025). https:\/\/doi.org\/10.4271\/12-08-04-0033","journal-title":"SAE Int. J. Connect. Automat Veh."},{"issue":"8","key":"669_CR19","doi-asserted-by":"publisher","first-page":"2657","DOI":"10.3390\/s24082657","volume":"24","author":"R Zhao","year":"2024","unstructured":"Zhao, R., Wang, K., Che, W., Li, Y., Fan, Y., Gao, F.: Adaptive cruise control based on safe deep reinforcement learning. Sensors 24(8), 2657 (2024)","journal-title":"Sensors"},{"issue":"12","key":"669_CR20","doi-asserted-by":"publisher","first-page":"21946","DOI":"10.1109\/JIOT.2024.3377600","volume":"11","author":"H Kamal","year":"2024","unstructured":"Kamal,H., Y\u00e1nez, W., Hassan, S., Sobhy, D.: Digital-twin-based deep reinforcement learning approach for adaptive traffic signal control. IEEE Internet Things J. 11(12), 21946\u201321953 (2024). https:\/\/doi.org\/10.1109\/JIOT.2024.3377600","journal-title":"IEEE Internet Things J."},{"issue":"2","key":"669_CR21","doi-asserted-by":"publisher","first-page":"1216","DOI":"10.1109\/TR.2024.3373810","volume":"73","author":"A Berdich","year":"2024","unstructured":"Berdich,A., Groza, B.: Cyberattacks on Adaptive cruise controls and emergency braking systems: adversary models, impact assessment, and countermeasures. IEEE Trans. Rel. 73(2), 1216\u20131230 (2024). https:\/\/doi.org\/10.1109\/TR.2024.3373810","journal-title":"IEEE Trans. Rel"},{"key":"669_CR22","doi-asserted-by":"publisher","first-page":"105063","DOI":"10.1016\/j.trc.2025.105063","volume":"173","author":"H Yu","year":"2025","unstructured":"Yu, H., Yeo, H.: Traffic control policies for minimizing the negative effect of adaptive cruise control on highway. Transp. Res. C Emerg. Technol. 173, 105063 (2025)","journal-title":"Transp. Res. C Emerg. Technol."},{"issue":"1","key":"669_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/00423114.2012.708421","volume":"51","author":"S Eben Li","year":"2013","unstructured":"Eben Li, S., Li, K., Wang, J.: Economy-oriented vehicle adaptive cruise control with coordinating multiple objectives function. Veh. Syst. Dyn. 51(1), 1\u201317 (2013)","journal-title":"Veh. Syst. Dyn."},{"issue":"3","key":"669_CR24","doi-asserted-by":"publisher","first-page":"4312","DOI":"10.1109\/TIV.2024.3351131","volume":"9","author":"T Zhang","year":"2024","unstructured":"Zhang, T., Sun, Y., Wang, Y., Li, B., Tian, Y., Wang, F.-Y.: A survey of vehicle dynamics modeling methods for autonomous racing: theoretical models, physical\/virtual platforms, and perspectives. IEEE Trans. Intell. Veh. 9(3), 4312\u20134334 (2024)","journal-title":"IEEE Trans. Intell. Veh."},{"key":"669_CR25","doi-asserted-by":"publisher","first-page":"103692","DOI":"10.1016\/j.trc.2022.103692","volume":"139","author":"Y He","year":"2022","unstructured":"He, Y., Montanino, M., Mattas, K., Punzo, V., Ciuffo, B.: Physics-augmented models to simulate commercial adaptive cruise control (ACC) systems. Transp. Res. C. Emerg. Technol. 139, 103692 (2022)","journal-title":"Transp. Res. C. Emerg. Technol."},{"issue":"4","key":"669_CR26","doi-asserted-by":"publisher","first-page":"e01470","DOI":"10.1002\/ecm.1470","volume":"91","author":"M Auger\u2010M\u00e9th\u00e9","year":"2021","unstructured":"Auger\u2010M\u00e9th\u00e9, M., Newman, K., Cole, D., Empacher, F., Gryba, R., King, A.A., Leos\u2010Barajas, V., et al.: A guide to state\u2013space modeling of ecological time series. Ecol. Monogr. 91(4), e01470 (2021)","journal-title":"Ecol. Monogr."}],"container-title":["International Journal of Intelligent Transportation Systems Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13177-026-00669-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13177-026-00669-y","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13177-026-00669-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T09:48:51Z","timestamp":1784800131000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13177-026-00669-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,14]]},"references-count":26,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,8]]}},"alternative-id":["669"],"URL":"https:\/\/doi.org\/10.1007\/s13177-026-00669-y","relation":{},"ISSN":["1348-8503","1868-8659"],"issn-type":[{"value":"1348-8503","type":"print"},{"value":"1868-8659","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,14]]},"assertion":[{"value":"10 March 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 May 2026","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 May 2026","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 May 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"This article does not contain any studies involving human participants or animals performed by any of the authors.","order":1,"name":"Ethics","label":"Ethics Approval","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}]}}