References
- Abdul Aziz, H. M., Zhu, F., & Ukkusuri, S. V. (2018). Learning based traffic signal control algorithms with neighborhood information sharing: An application for sustainable mobility. Journal of Intelligent Transportation Systems, 22(1), 40–52. https://doi.org/10.1080/15472450.2017.1387546
- Aboudolas, K., Papageorgiou, M., & Kosmatopoulos, E. (2009). Store-and-forward based methods for the signal control problem in large-scale congested urban road networks. Transportation Research Part C: Emerging Technologies, 17(2), 163–174. https://doi.org/10.1016/j.trc.2008.10.002
- Berg, M. V. d., Hegyi, A., De Schutter, B., & Hellendoorn, H. (2007). Integrated traffic control for mixed urban and freeway networks: A model predictive control approach. European Journal of Transport and Infrastructure Research, 7(3), 223–250.
- Cai, C., Wong, C. K., & Heydecker, B. G. (2009). Adaptive traffic signal control using approximate dynamic programming. Transportation Research Part C: Emerging Technologies, 17(5), 456–474.
- Clegg, R. G., Clune, A., & Smith, M. (2000). Traffic signal settings for diverse policy goals. In Proc. of PTRC (pp. 93–104). https://trid.trb.org/view/676009
- Cui, Y., Xu, H., Wu, J., Sun, Y., & Zhao, J. (2019). Automatic vehicle tracking with roadside lidar data for the connected-vehicles system. IEEE Intelligent Systems, 34(3), 44–51. https://doi.org/10.1109/MIS.2019.2918115
- Diakaki, P., Kotsialos, D. & Wang, Y. (2003). Review of road traffic control strategies. Proceedings of the IEEE, 91(12), 2041–2042. https://doi.org/10.1109/JPROC.2003.819606
- Dinopoulou, V., Diakaki, C., & Papageorgiou, M. (2000). Simulation investigations of the traffic-responsive urban control strategy TUC [Paper presentation]. In ITSC2000. 2000 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.00TH8493) (pp. 458–463). IEEE. https://doi.org/10.1109/ITSC.2000.881110
- Dixon, P. M., Weiner, J., Mitchell-Olds, T., & Woodley, R. (1987). Bootstrapping the Gini coefficient of inequality. Ecology, 68(5), 1548–1551. https://doi.org/10.2307/1939238
- Dresner, K., & Stone, P. (2008). A multiagent approach to autonomous intersection management. Journal of Artificial Intelligence Research, 31, 591–656. https://doi.org/10.1613/jair.2502
- Farges, J. L., Khoudour, I., Lesort, J. B. (1994). PRODYN: On site evaluation. In Third International Conference on Road Traffic Control, 1990 (pp. 62–66). IET.
- Gartner, N., Little, J. D. C., & Gabbay, H. (1975). Optimization of traffic signal settings by mixed-integer linear programming. Transportation Science, 9(4), 344–363. https://doi.org/10.1287/trsc.9.4.344
- Gartner, N., Pooran, F., & Andrews, C. (2001). Implementation of the OPAC adaptive control strategy in a traffic signal network [Paper presentation]. In ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585) (pp. 195–200). IEEE. https://doi.org/10.1109/ITSC.2001.948655
- Genders, W., & Razavi, S. (2019). Asynchronous n-step q-learning adaptive traffic signal control. Journal of Intelligent Transportation Systems, 23(4), 319–331. https://doi.org/10.1080/15472450.2018.1491003
- Geroliminis, N., Haddad, J., & Ramezani, M. (2013). Optimal perimeter control for two urban regions with macroscopic fundamental diagrams: a model predictive approach. IEEE Transactions on Intelligent Transportation Systems, 14(1), 348–359. https://doi.org/10.1109/TITS.2012.2216877
- Gregoire, J., Qian, X., Frazzoli, E., De La Fortelle, A., & Wongpiromsarn, T. (2015). Capacity-aware backpressure traffic signal control. IEEE Transactions on Control of Network Systems, 2(2), 164–173. https://doi.org/10.1109/TCNS.2014.2378871
- Jeon, H., Lee, J., & Sohn, K. (2018). Artificial intelligence for traffic signal control based solely on video images. Journal of Intelligent Transportation Systems, 22(5), 433–445. https://doi.org/10.1080/15472450.2017.1394192
- Jeong, Y., & Kim, Y. (2014). Tram passive signal priority strategy based on the MAXBAND model. KSCE Journal of Civil Engineering, 18(5), 1518–1527. https://doi.org/10.1007/s12205-014-0159-1
- Ke, R., Li, Z., Tang, J., Pan, Z., & Wang, Y. (2019). Real-time traffic flow parameter estimation from uav video based on ensemble classifier and optical flow. IEEE Transactions on Intelligent Transportation Systems, 20(1), 54–11. https://doi.org/10.1109/TITS.2018.2797697
- Kenworthy, J. R., & Laube, F. B. (1999). Patterns of automobile dependence in cities: an international overview of key physical and economic dimensions with some implications for urban policy. Transportation Research Part A: Policy and Practice, 33(7–8), 691–723. https://doi.org/10.1016/S0965-8564(99)00006-3
- Kulcsr, B., Ampountolas, K., & Dabiri, A. (2015). Single-region robust perimeter traffic flow control [Paper presentation]. In 2015 European Control Conference (ECC) (pp. 2628–2633). IEEE. https://doi.org/10.1109/ECC.2015.7330934
- Le, T., Kovács, P., Walton, N., Vu, H. L., Andrew, L. L. H., & Hoogendoorn, S. S. P. (2015). Decentralized signal control for urban road networks. Transportation Research Part C: Emerging Technologies, 58, 431–450. https://doi.org/10.1016/j.trc.2014.11.009
- Li, L., Zhang, J., Wang, Y., & Ran, B. (2019). Missing value imputation for traffic-related time series data based on a multi-view learning method. IEEE Transactions on Intelligent Transportation Systems, 20(8), 2933–2911. https://doi.org/10.1109/TITS.2018.2869768
- Li, X., & Sun, J.-Q. (2019). Multi-objective optimal predictive control of signals in urban traffic network. Journal of Intelligent Transportation Systems, 23(4), 370–388. https://doi.org/10.1080/15472450.2018.1504294
- Lin, S., De Schutter, B., Xi, Y., & Hellendoorn, H. (2012). Efficient network-wide model-based predictive control for urban traffic networks. Transportation Research Part C: Emerging Technologies, 24, 122–140. https://doi.org/10.1016/j.trc.2012.02.003
- Lämmer, S., Kori, H., Peters, K., & Helbing, D. (2006). Decentralised control of material or traffic flows in networks using phase-synchronisation. Physica A: Statistical Mechanics and Its Applications, 363(1), 39–47. https://doi.org/10.1016/j.physa.2006.01.047
- Ma, D., Li, W., Song, X., Wang, Y., & Zhang, W. (2019). Time-of-day breakpoints optimisation through recursive time series partitioning. IET Intelligent Transport Systems, 13(4), 683–692. https://doi.org/10.1049/iet-its.2018.5162
- Ma, D., Luo, X., Jin, S., Guo, W., & Wang, D. (2018). Estimating maximum queue length for traffic lane groups using travel times from video-imaging data. IEEE Intelligent Transportation Systems Magazine, 10(3), 123–134. https://doi.org/10.1109/MITS.2018.2842047
- McKeown, N., Mekkittikul, A., Anantharam, V., & Walrand, J. (1999). Achieving 100% throughput in an input-queued switch. IEEE Transactions on Communications, 47(8), 1260–1267. https://doi.org/10.1109/26.780463
- Mirchandani, P., & Wang, F. Y. (2005). RHODES to intelligent transportation systems. IEEE Intelligent Systems, 20(1), 10–15. https://doi.org/10.1109/MIS.2005.15
- Robertson, D., & Bretherton, R. (1991). Optimizing networks of traffic signals in real time-the SCOOT method. IEEE Transactions on Vehicular Technology, 40(1), 11–15. https://doi.org/10.1109/25.69966
- Shen, G. J. (2006). Urban traffic trunk two-direction green wave intelligent control strategy and its application. In 2006 6th World Congress on Intelligent Control and Automation (pp. 8563–8567). IEEE.
- Sims, A., & Dobinson, K. (1980). The Sydney coordinated adaptive traffic (SCAT) system philosophy and benefits. IEEE Transactions on Vehicular Technology, 29(2), 130–137. https://doi.org/10.1109/T-VT.1980.23833
- Smith, M. (2011). Dynamics of route choice and signal control in capacitated networks. Journal of Choice Modelling, 4(3), 30–51. https://doi.org/10.1016/S1755-5345(13)70041-1
- Song, X., Li, W., Ma, D., Wang, D., Qu, L., & Wang, Y. (2018). A match-then-predict method for daily traffic flow forecasting based on group method of data handling. Computer-Aided Civil and Infrastructure Engineering, 33(11), 982–998. https://doi.org/10.1111/mice.12381
- Tassiulas, L., & Bhattacharya, P. P. (2000). Allocation of interdependent resources for maximal throughput. Communications in Statistics. Stochastic Models, 16(1), 27–48. https://doi.org/10.1080/15326340008807575
- Tassiulas, L., & Ephremides, A. (1992). Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks. IEEE Transactions on Automatic Control, 37(12), 1936–1948. https://doi.org/10.1109/9.182479
- Varaiya, P. (2013). Max pressure control of a network of signalized intersections. Transportation Research Part C: Emerging Technologies, 36, 177–195. https://doi.org/10.1016/j.trc.2013.08.014
- Villalobos, I. A., Poznyak, A. S., & Tamayo, A. M. (2008). Urban traffic control problem: a game theory approach. IFAC Proceedings Volumes, 41(2), 7154–7159. https://doi.org/10.3182/20080706-5-KR-1001.01213
- Viti, F., & Zuylen, H. J. V. (2009). The dynamics and the uncertainty of queues at fixed and actuated controls: A probabilistic approach. Journal of Intelligent Transportation Systems, 13(1), 39–51. https://doi.org/10.1080/15472450802644470
- Wongpiromsarn, T., Uthaicharoenpong, T., Wang, Y., Frazzoli, E., & Wang, D. (2012). Distributed traffic signal control for maximum network throughput. In 2012 15th International IEEE Conference on Intelligent Transportation Systems (pp. 588–595). IEEE.
- Xu, H., Liu, H., & Tian, Z. (2010). Control delay at signalized diamond interchanges considering internal queue spillback. Transportation Research Record: Journal of the Transportation Research Board, 2173(1), 123–132. https://doi.org/10.3141/2173-15
- Xu, M., An, K., Vu, L. H., Ye, Z., Feng, J., & Chen, E. (2019). Optimizing multi-agent based urban traffic signal control system. Journal of Intelligent Transportation Systems, 23(4), 357–369. https://doi.org/10.1080/15472450.2018.1501273
- Xu, M., Wu, J., Huang, L., Zhou, R., Wang, T., & Hu, D. (2020). Network-wide traffic signal control based on the discovery of critical nodes and deep reinforcement learning. Journal of Intelligent Transportation Systems, 24(1), 1–10. https://doi.org/10.1080/15472450.2018.1527694
- Yao, Z., Jiang, Y., Zhao, B., Luo, X., & Peng, B. (2020). A dynamic optimization method for adaptive signal control in a connected vehicle environment. Journal of Intelligent Transportation Systems, 24(2), 184–200. https://doi.org/10.1080/15472450.2019.1643723
- Yu, C., Feng, Y., Liu, H., Ma, W., & Yang, X. (2018). Integrated optimization of traffic signals and vehicle trajectories at isolated urban intersections. Transportation Research Part B: Methodological, 112, 89–112. https://doi.org/10.1016/j.trb.2018.04.007
- Yu, C., Feng, Y., Liu, H., Ma, W., & Yang, X. (2019). Corridor level cooperative trajectory optimization with connected and automated vehicles. Transportation Research Part C: Emerging Technologies, 105, 405–421.
- Yuan, Y., Yang, M., Wu, J., Rasouli, S., & Lei, D. (2019). Assessing bus transit service from the perspective of elderly passengers in Harbin, China. International Journal of Sustainable Transportation, 13(10), 761–716. https://doi.org/10.1080/15568318.2018.1512691
- Zhang, J., Dong, S., Li, Z., Ran, B., Li, R., & Wang, H. (2019). An eco-driving signal control model for divisible electric platoons in cooperative vehicle-infrastructure systems. IEEE Access, 7, 83277–83285.
- Zhang, R., Li, Z., Feng, C., & Jiang, S. (2012). Traffic routing guidance algorithm based on backpressure with a trade-off between user satisfaction and traffic load [Paper presentation]. In 2012 IEEE Vehicular Technology Conference (VTC Fall) (pp. 1–5). IEEE. https://doi.org/10.1109/VTCFall.2012.6399177