Urban traffic signal control with connected and automated vehicles: A survey

Alexiadis, 2004, The next generation simulation program, Inst. Transport. Eng. ITE J., 74, 22 Altan, 2017, GlidePath: eco-friendly automated approach and departure at signalized intersections, IEEE Trans. Intell. Veh., 2, 266, 10.1109/TIV.2017.2767289 Araghi, 2016, Mode specific travel time estimation using Bluetooth Technology, J. Intell. Transport. Syst., 20, 219, 10.1080/15472450.2015.1052906 Argote-Cabañero, 2015, Connected vehicle penetration rate for estimation of arterial measures of effectiveness, Transport. Res. Part C: Emerg. Technol., 60, 298, 10.1016/j.trc.2015.08.013 Ban, X., Gruteser, M., 2010. Mobile sensors as traffic probes: addressing transportation modeling and privacy protection in an integrated framework. In: Traffic and Transportation Studies 2010, pp. 750–767. Ban, 2011, Real time queue length estimation for signalized intersections using travel times from mobile sensors, Transport. Res. Part C: Emerg. Technol., 19, 1133, 10.1016/j.trc.2011.01.002 Ban, 2009, Delay pattern estimation for signalized intersections using sampled travel times, Transport. Res. Rec.: J. Transport. Res. Board, 2130, 109, 10.3141/2130-14 Balke, 2000, Development and evaluation of intelligent bus priority concept, Transport. Res. Rec.: J. Transport. Res. Board, 1727, 12, 10.3141/1727-02 Beak, 2017, Adaptive coordination based on connected vehicle technology, Transport. Res. Rec.: J. Transport. Res. Board, 2619, 1, 10.3141/2619-01 Berkow, 2009, Prototype for data fusion using stationary and mobile data: Sources for improved arterial performance measurement, Transport. Res. Rec.: J. Transport. Res. Board, 2099, 102, 10.3141/2099-12 Bhaskar, 2011, Fusing loop detector and probe vehicle data to estimate travel time statistics on signalized urban networks, Comput.-Aided Civil Infrastruct. Eng., 26, 433, 10.1111/j.1467-8667.2010.00697.x Bhaskar, 2014, Urban traffic state estimation: Fusing point and zone based data, Transport. Res. Part C: Emerg. Technol., 48, 120, 10.1016/j.trc.2014.08.015 Bodenheimer, 2014, Enabling GLOSA for adaptive traffic lights, 167 Boriboonsomsin, 2012, Eco-routing navigation system based on multisource historical and real-time traffic information, IEEE Trans. Intell. Transport. Syst., 13, 1694, 10.1109/TITS.2012.2204051 U.S. Census Bureau, 2012. Statistical abstract of the United States: 2012. Retrieved from https://www.census.gov/library/publications/2011/compendia/statab/131ed.html. Cai, 2014, Shock wave approach for estimating queue length at signalized intersections by fusing data from point and mobile sensors, Transport. Res. Rec.: J. Transport. Res. Board, 2422, 79, 10.3141/2422-09 Camponogara, 2002, Distributed model predictive control, IEEE Control Systems, 22, 44, 10.1109/37.980246 Cao, 2013, An overview of recent progress in the study of distributed multi-agent coordination, IEEE Trans. Ind. Inform., 9, 427, 10.1109/TII.2012.2219061 Cavoukian, A., 2009. Privacy by Design, Take the Challenge. Information and Privacy Commissioner of Ontario, Toronto, Ont.. Chaudhary, N.A., Kovvali, V.G., Alam, S.M., 2002. Guidelines for selecting signal timing software (No. FHWA/TX-03/0-4020-P2,). Texas Transportation Institute, Texas A & M University System. Chen, 2016, Cooperative intersection management: a survey, IEEE Trans. Intell. Transport. Syst., 17, 570, 10.1109/TITS.2015.2471812 Chen, 2016, An improved adaptive signal control method for isolated signalized intersection, IEEE Intell. Transport. Syst. Mag., 8, 4, 10.1109/MITS.2016.2605318 Chen, Q.A., Yin, Y., Feng, Y., Mao, Z.M., Liu, H.X., 2018, February. Exposing congestion attack on emerging connected vehicle based traffic signal control. In: Network and Distributed Systems Security (NDSS) Symposium 2018. Cheng, 2012, An exploratory shockwave approach to estimating queue length using probe trajectories, J. Intell. Transport. Syst., 16, 12, 10.1080/15472450.2012.639637 Chuxing, D., 2018. GAIA initiative, accessed on Apr. 20, 2018. https://outreach.didichuxing.com/research/opendata/en/. Comert, 2013, Simple analytical models for estimating the queue lengths from probe vehicles at traffic signals, Transport. Res. Part B: Methodol., 55, 59, 10.1016/j.trb.2013.05.001 Comert, 2009, Queue length estimation from probe vehicle location and the impacts of sample size, Eur. J. Oper. Res., 197, 196, 10.1016/j.ejor.2008.06.024 Comert, 2011, Analytical evaluation of the error in queue length estimation at traffic signals from probe vehicle data, IEEE Trans. Intell. Transport. Syst., 12, 563, 10.1109/TITS.2011.2113375 Connected Vehicle Pilot Deployment Program: https://www.its.dot.gov/pilots/. Daganzo, 2012, The potential of parsimonious models for understanding large scale transportation systems and answering big picture questions, EURO J. Transport. Logist., 1, 47, 10.1007/s13676-012-0003-z Day, 2016, Detector-free signal offset optimization with limited connected vehicle market penetration: proof-of-concept study, Transport. Res. Rec.: J. Transport. Res. Board, 2558, 54, 10.3141/2558-06 Day, 2017, Detector-free optimization of traffic signal offsets with connected vehicle data, Transport. Res. Rec.: J. Transport. Res. Board, 2620, 54, 10.3141/2620-06 Diakaki, 2014, State-of-the-art and-practice review of public transport priority strategies, IET Intell. Transp. Syst., 9, 391, 10.1049/iet-its.2014.0112 Ding, 2018, Accessibility measure of bus transit networks, IET Intell. Transp. Syst., 10.1049/iet-its.2017.0286 Dong, 2018, An empirical study on travel patterns of internet based ride-sharing, Transport. Res. Part C: Emerg. Technol., 86, 1, 10.1016/j.trc.2017.10.022 D'Andrea, 2003, Distributed control design for spatially interconnected systems, IEEE Trans. Autom. Control, 48, 1478, 10.1109/TAC.2003.816954 Ekeila, 2009, Development of dynamic transit signal priority strategy, Transport. Res. Rec.: J. Transport. Res. Board, 2111, 1, 10.3141/2111-01 Ernst, 2014, Estimating required probe vehicle re-identification requirements for characterizing link travel times, IEEE Intell. Transport. Syst. Mag., 6, 50, 10.1109/MITS.2013.2288648 Feng, 2015, A real-time adaptive signal control in a connected vehicle environment, Transport. Res. Part C: Emerg. Technol., 55, 460, 10.1016/j.trc.2015.01.007 Feng, Y., Huang, S., Chen, Q.A., Liu, H.X., Mao, Z.M., 2018. Vulnerability of traffic control system under cyberattacks with falsified data. Transport. Res. Rec. p. 0361198118756885. Ferman, 2005, An analytical evaluation of a real-time traffic information system using probe vehicles, Intell. Transport. Syst., 23, 10.1080/15472450590912547 Florin, 2015, A survey of vehicular communications for traffic signal optimization, Veh. Commun., 2, 70 Gan, 2017, Estimation of performance metrics at signalized intersections using loop detector data and probe travel times, IEEE Trans. Intell. Transport. Syst., 18, 2939, 10.1109/TITS.2017.2666143 Geroliminis, 2008, Existence of urban-scale macroscopic fundamental diagrams: some experimental findings, Transport. Res. Part B: Methodol., 42, 759, 10.1016/j.trb.2008.02.002 Geroliminis, 2013, Optimal perimeter control for two urban regions with macroscopic fundamental diagrams: a model predictive approach, IEEE Trans. Intell. Transport. Syst., 14, 348, 10.1109/TITS.2012.2216877 Goodall, 2013, Traffic signal control with connected vehicles, Transport. Res. Rec.: J. Transport. Res. Board, 2381, 65, 10.3141/2381-08 Gradinescu, 2007, Adaptive traffic lights using car-to-car communication, 21 Gregoire, 2014, Back-pressure traffic signal control with unknown routing rates, IFAC Proc. Volumes, 47, 11332, 10.3182/20140824-6-ZA-1003.01585 Gregoire, 2015, Capacity-aware backpressure traffic signal control, IEEE Trans. Control Network Syst., 2, 164, 10.1109/TCNS.2014.2378871 Guler, 2014, Using connected vehicle technology to improve the efficiency of intersections, Transport. Res. Part C: Emerg. Technol., 46, 121, 10.1016/j.trc.2014.05.008 Guo, 2014, Adaptive Kalman filter approach for stochastic short-term traffic flow rate prediction and uncertainty quantification, Transport. Res. Part C: Emerg. Technol., 43, 50, 10.1016/j.trc.2014.02.006 Gustafsson, 2002, Particle filters for positioning, navigation, and tracking, IEEE Trans. Signal Process., 50, 425, 10.1109/78.978396 Haddad, 2013, Cooperative traffic control of a mixed network with two urban regions and a freeway, Transport. Res. Part B: Methodol., 54, 17, 10.1016/j.trb.2013.03.007 Haghani, 2010, Data collection of freeway travel time ground truth with bluetooth sensors, Transport. Res. Rec.: J. Transport. Res. Board, 2160, 60, 10.3141/2160-07 Hamilton, 2013, The evolution of urban traffic control: changing policy and technology, Transport. Plann. Technol., 36, 24, 10.1080/03081060.2012.745318 Han, 2014, Development and evaluation of adaptive transit signal priority control with updated transit delay model, Transport. Res. Rec.: J. Transport. Res. Board, 2438, 45, 10.3141/2438-05 Hao, 2015, Long queue estimation for signalized intersections using mobile data, Transport. Res. Part B: Methodol., 82, 54, 10.1016/j.trb.2015.10.002 Hao, 2012, Signal timing estimation using sample intersection travel times, IEEE Trans. Intell. Transport. Syst., 13, 792, 10.1109/TITS.2012.2187895 Hao, 2014, Cycle-by-cycle intersection queue length distribution estimation using sample travel times, Transport. Res. Part B: Methodol., 68, 185, 10.1016/j.trb.2014.06.004 Hao, 2015, Kinematic equation-based vehicle queue location estimation method for signalized intersections using mobile sensor data, J. Intell. Transport. Syst., 19, 256, 10.1080/15472450.2013.857197 Hao, 2013, Vehicle index estimation for signalized intersections using sample travel times, Transport. Res. Part C: Emerg. Technol., 36, 513, 10.1016/j.trc.2013.06.018 He, 2012, PAMSCOD: Platoon-based arterial multi-modal signal control with online data, Transport. Res. Part C: Emerg. Technol., 20, 164, 10.1016/j.trc.2011.05.007 He, 2014, Multi-modal traffic signal control with priority, signal actuation and coordination, Transport. Res. Part C: Emerg. Technol., 46, 65, 10.1016/j.trc.2014.05.001 He, 2017, Mapping to cells: a simple method to extract traffic dynamics from probe vehicle data, Comput.-Aided Civil Infrastruct. Eng., 32, 252, 10.1111/mice.12251 Henclewood, D., Abramovich, M., Yelchuru, B., 2014. Safety pilot model deployment–one day sample data environment data handbook. Research and Technology Innovation Administration. Research and Technology Innovation Administration, US Department of Transportation, McLean, VA. Herrera, 2010, Evaluation of traffic data obtained via GPS-enabled mobile phones: the Mobile Century field experiment, Transport. Res. Part C, 18, 568, 10.1016/j.trc.2009.10.006 Highway Capacity Manual (HCM), Transportation Research Board, 2010. Hiribarren, 2014, Real time traffic states estimation on arterials based on trajectory data, Transport. Res. Part B: Methodol., 69, 19, 10.1016/j.trb.2014.07.003 Hofleitner, 2012, Arterial travel time forecast with streaming data: a hybrid approach of flow modeling and machine learning, Transport. Res. Part B: Methodol., 46, 1097, 10.1016/j.trb.2012.03.006 Hoh, 2008, Virtual trip lines for distributed privacy-preserving traffic monitoring, 15 Hoh, 2012, Enhancing privacy and accuracy in probe vehicle based traffic monitoring via virtual trip lines, IEEE Trans. Mobile Comput., 11, 849, 10.1109/TMC.2011.116 Hu, 2015, Coordinated transit signal priority supporting transit progression under connected vehicle technology, Transport. Res. Part C: Emerg. Technol., 55, 393, 10.1016/j.trc.2014.12.005 Hu, 2016, Transit signal priority accommodating conflicting requests under Connected Vehicles technology, Transport. Res. Part C: Emerg. Technol., 69, 173, 10.1016/j.trc.2016.06.001 Hunter, 2012, A probe-vehicle-based evaluation of adaptive traffic signal control, IEEE Trans. Intell. Transport. Syst., 13, 704, 10.1109/TITS.2011.2178404 Islam, 2017, Distributed coordinated signal timing optimization in connected transportation networks, Transport. Res. Part C: Emerg. Technol., 80, 10.1016/j.trc.2017.04.017 Jenelius, 2015, Probe vehicle data sampled by time or space: consistent travel time allocation and estimation, Transport. Res. Part B: Methodol., 71, 120, 10.1016/j.trb.2014.10.008 Jiang, 2017, Traffic state and emission estimation for urban expressways based on heterogeneous data, Transport. Res. Part D: Transp. Environ., 53, 440, 10.1016/j.trd.2017.04.042 Jiang, 2017, Eco approach at an isolated signalized intersection under partially connected and automated vehicle environment, Transport. Res. Part C: Emerg. Technol., 79, 290, 10.1016/j.trc.2017.04.001 Kari, 2014, Development of an agent-based online adaptive signal control strategy using connected vehicle technology, 1802 Katsaros, 2011, Performance study of a Green Light Optimized Speed Advisory (GLOSA) application using an integrated cooperative ITS simulation platform, 918 Kurzhanskiy, 2015, Traffic management: an outlook, Econ. Transport., 4, 135, 10.1016/j.ecotra.2015.03.002 Le, 2015, Decentralized signal control for urban road networks, Transport. Res. Part C: Emerg. Technol., 58, 431, 10.1016/j.trc.2014.11.009 Lee, 2017, Deployment and field evaluation of in-vehicle traffic signal advisory system (ITSAS), Information, 8, 72, 10.3390/info8030072 Lee, 2012, Development and evaluation of a cooperative vehicle intersection control algorithm under the connected vehicles environment, IEEE Trans. Intell. Transport. Syst., 13, 81, 10.1109/TITS.2011.2178836 Lee, 2013, Cumulative travel-time responsive real-time intersection control algorithm in the connected vehicle environment, J. Transport. Eng., 139, 1020, 10.1061/(ASCE)TE.1943-5436.0000587 Li, 2017, Traffic signal timing optimization in connected vehicles environment, 1330 Li, 2018, Connected vehicle based traffic signal timing optimization, IEEE Trans. Intell. Transport. Syst., 10.1109/TITS.2018.2883572 Li, W., Ban, X., 2019. Connected vehicle based traffic signal coordination. Engineering (under review). Li, 2018, Connected vehicle-based red-light running prediction for adaptive signalized intersections, J. Intell. Transport. Syst., 22, 229, 10.1080/15472450.2016.1215921 Li, 2014, Signal control optimization for automated vehicles at isolated signalized intersections, Transport. Res. Part C: Emerg. Technol., 49, 1, 10.1016/j.trc.2014.10.001 Li, 2016, Intelligence testing for autonomous vehicles: a new approach, IEEE Trans. Intell. Veh., 1, 158, 10.1109/TIV.2016.2608003 Li, 2015, Use of both travel time and travel time reliability measures to quantify benefits of signal timing maintenance and optimization, Transport. Res. Rec.: J. Transport. Res. Board, 2487, 55, 10.3141/2487-05 Li, 2018, Artificial intelligence test: a case study of intelligent vehicles, Artificial Intelligence Review, 50, 441, 10.1007/s10462-018-9631-5 Li, 2014, Diagnosing and interpolating loop detector data errors with probe vehicle data, Transport. Res. Rec.: J. Transport. Res. Board, 2423, 61, 10.3141/2423-08 Li, 2018, A review of past 100-yera and perspective of next 50-year development of ground traffic control, Autom. Sin., 44, 577 Li, 2014, A survey of traffic control with vehicular communications, IEEE Trans. Intell. Transport. Syst., 15, 425, 10.1109/TITS.2013.2277737 Li, 2012, Cognitive cars: a new frontier for ADAS research, IEEE Trans. Intell. Transport. Syst., 13, 395, 10.1109/TITS.2011.2159493 Liang, 2018, Signal timing optimization with Connected Vehicle technology: Platooning to improve computational efficiency, Transport. Res. Rec., 10.1177/0361198118786842 Liao, 2007, Simulation study of bus signal priority strategy: taking advantage of global positioning system, automated vehicle location system, and wireless communications, Transport. Res. Rec.: J. Transport. Res. Board, 2034, 82, 10.3141/2034-10 Lioris, 2017, Platoons of connected vehicles can double throughput in urban roads, Transport. Res. Part C: Emerg. Technol., 77, 292, 10.1016/j.trc.2017.01.023 Liu, 2009, A virtual vehicle probe model for time-dependent travel time estimation on signalized arterials, Transport. Res. Part C: Emerg. Technol., 17, 11, 10.1016/j.trc.2008.05.002 Lv, 2015, Traffic flow prediction with big data: a deep learning approach, IEEE Trans. Intell. Transport. Syst., 16, 865 Ma, 2017, Learning traffic as images: a deep convolutional neural network for large-scale transportation network speed prediction, Sensors, 17, 818, 10.3390/s17040818 Ma, 2015, Large-scale transportation network congestion evolution prediction using deep learning theory, PloS One, 10, e0119044, 10.1371/journal.pone.0119044 Mahmassani, 2016, 50th anniversary invited article—autonomous vehicles and connected vehicle systems: flow and operations considerations, Transport. Sci., 50, 1140, 10.1287/trsc.2016.0712 Marinica, 2013, Distributed particle filter for urban traffic networks using a platoon-based model, IEEE Trans. Intell. Transport. Syst., 14, 1918, 10.1109/TITS.2013.2271326 Massaro, 2017, The car as an ambient sensing platform [point of view], Proc. IEEE, 105, 3, 10.1109/JPROC.2016.2634938 Massioni, 2009, Distributed control for identical dynamically coupled systems: a decomposition approach, IEEE Trans. Autom. Control, 54, 124, 10.1109/TAC.2008.2009574 Mckenney, 2013, Distributed and adaptive traffic signal control within a realistic traffic simulation, Eng. Appl. Artif. Intell., 26, 574, 10.1016/j.engappai.2012.04.008 Mehrabipour, 2017, A cell-based distributed-coordinated approach for network-level signal timing optimization, Comput.-Aided Civil Infrastruct. Eng., 32, 599, 10.1111/mice.12272 Meng, 2018, Analysis of cooperative driving strategies for nonsignalized intersections, IEEE Trans. Veh. Technol., 67, 2900, 10.1109/TVT.2017.2780269 Mirchandani, 2001, A real-time traffic signal control system: architecture, algorithms, and analysis, Transport. Res. Part C: Emerg. Technol., 9, 415, 10.1016/S0968-090X(00)00047-4 Montanino, 2015, Trajectory data reconstruction and simulation-based validation against macroscopic traffic patterns, Transport. Res. Part B: Methodol., 80, 82, 10.1016/j.trb.2015.06.010 NHTSA, Automated Vehicles for Safety, 2016. https://www.nhtsa.gov/technology-innovation/automated-vehicles-safety#issue-road-self-driving. Nie, 2017, How can the taxi industry survive the tide of ridesourcing? Evidence from Shenzhen, China, Transport. Res. Part C: Emerg. Technol., 79, 242, 10.1016/j.trc.2017.03.017 Nuzzolo, 2016, Advanced public transport and intelligent transport systems: new modelling challenges, Transportm. A: Transp. Sci., 12, 674 Olia, 2016, Assessing the potential impacts of connected vehicles: mobility, environmental, and safety perspectives, J. Intell. Transport. Syst., 20, 229, 10.1080/15472450.2015.1062728 Ou, 2011, A theoretical framework for traffic speed estimation by fusing low-resolution probe vehicle data, IEEE Trans. Intell. Transport. Syst., 12, 747, 10.1109/TITS.2011.2157688 Pandit, 2013, Adaptive traffic signal control with vehicular ad hoc networks, IEEE Trans. Veh. Technol., 62, 1459, 10.1109/TVT.2013.2241460 Polson, 2017, Deep learning for short-term traffic flow prediction, Transport. Res. Part C: Emerg. Technol., 79, 1, 10.1016/j.trc.2017.02.024 Qian, 2017, Autonomous intersection management systems: criteria, implementation and evaluation, IET Intell. Transp. Syst., 11, 182, 10.1049/iet-its.2016.0043 Rakha, 2011, Eco-driving at signalized intersections using V2I communication, 341 Ramezani, 2012, On the estimation of arterial route travel time distribution with Markov chains, Transport. Res. Part B: Methodol., 46, 1576, 10.1016/j.trb.2012.08.004 Ramezani, 2013, Exploiting probe data to estimate the queue profile in urban networks, 1817 Ramezani, 2015, Queue profile estimation in congested urban networks with probe data, Comput.-Aided Civil Infrastruct. Eng., 30, 414, 10.1111/mice.12095 Ran, 2016, Using tensor completion method to achieving better coverage of traffic state estimation from sparse floating car data, PloS One, 11, e0157420, 10.1371/journal.pone.0157420 Rios-Torres, 2018, Impact of partial penetrations of connected and automated vehicles on fuel consumption and traffic flow, IEEE Trans. Intell. Veh., 3, 453, 10.1109/TIV.2018.2873899 Roess, 2004 Rompis, 2018, Probe vehicle lane identification for queue length estimation at intersections, J. Intell. Transport. Syst., 22, 10, 10.1080/15472450.2017.1300887 Rosenberg, Matthew; Confessore, Nicholas; Cadwalladr, Carole, 2018. How Trump Consultants Exploited the Facebook Data of Millions. The New York Times. Archived from the original on March 17, 2018. Schuricht, 2011, Efficiency-increasing driver assistance at signalized intersections using predictive traffic state estimation, 347 Sen, 1997, Controlled optimization of phases at an intersection, Transport. Sci., 31, 5, 10.1287/trsc.31.1.5 Seo, 2015, Probe vehicle-based traffic state estimation method with spacing information and conservation law, Transport. Res. Part C: Emerg. Technol., 59, 391, 10.1016/j.trc.2015.05.019 Seredynski, 2014, Complementing transit signal priority with speed and dwell time extension advisories, 1009 Seredynski, M., Khadraoui, D., Viti, F., 2015, October. Signal phase and timing (SPaT) for cooperative public transport priority measures. In: Proc. 22nd ITS World Congress. Sharifi, 2017, Outsourced probe data effectiveness on signalized arterials, J. Intell. Transport. Syst., 21, 478, 10.1080/15472450.2017.1359093 Shen, 2014, Review of GPS travel survey and GPS data-processing methods, Transp. Rev., 34, 316, 10.1080/01441647.2014.903530 Smith, 2004, Wireless location technology-based traffic monitoring: critical assessment and evaluation of an early-generation system, J. Transport. Eng., 130, 576, 10.1061/(ASCE)0733-947X(2004)130:5(576) Sun, 2013, Vehicle trajectory reconstruction for signalized intersections using mobile traffic sensors, Transport. Res. Part C: Emerg. Technol., 36, 268, 10.1016/j.trc.2013.09.002 Sun, 2013, Privacy protection method for fine-grained urban traffic modeling using mobile sensors, Transport. Res. Part B: Methodol., 56, 50, 10.1016/j.trb.2013.07.010 Sun, 2017, A capacity maximization scheme for intersection management with automated vehicles, Transport. Res. Proc., 23, 121, 10.1016/j.trpro.2017.05.008 Tampère, 2007, An extended Kalman filter application for traffic state estimation using CTM with implicit mode switching and dynamic parameters, 209 Tang, 2018, A speed guidance strategy for multiple signalized intersections based on car-following model, Physica A: Stat. Mech. Appl., 496, 399, 10.1016/j.physa.2018.01.005 The Verge, 2018. Uber’s fatal self-driving crash: all the news and updates. Internet Link (Accessed on March 31, 2018): https://www.theverge.com/2018/3/28/17174636/uber-self-driving-crash-fatal-arizona-update. Tong, 2015, Stochastic programming model for oversaturated intersection signal timing, Transport. Res. Part C: Emerg. Technol., 58, 474, 10.1016/j.trc.2015.01.019 Ubiergo, 2016, Mobility and environment improvement of signalized networks through Vehicle-to-Infrastructure (V2I) communications, Transport. Res. Part C: Emerg. Technol., 68, 70, 10.1016/j.trc.2016.03.010 Uhlemann, 2015, Active safety vehicles evolving toward automated driving [Connected Vehicles], IEEE Veh. Technol. Mag., 10, 20, 10.1109/MVT.2015.2481118 Validi, 2018, Examining the impact on road safety of different penetration rates of vehicle-to-vehicle communication and adaptive cruise control, IEEE Intell. Transport. Syst. Mag., 10, 10.1109/MITS.2018.2867534 Van Lint, 2010, Empirical evaluation of new robust travel time estimation algorithms. Transport, Res. Rec. J. Transport. Res. Board, 2160, 50, 10.3141/2160-06 Van Mierlo, 2004, Driving style and traffic measures-influence on vehicle emissions and fuel consumption, Proc. Inst. Mech. Eng., Part D: J. Automob. Eng., 218, 43, 10.1243/095440704322829155 VanMiddlesworth, 2008, Replacing the stop sign: unmanaged intersection control for autonomous vehicles, 1413 Wan, 2016, Reconstructing maximum likelihood trajectory of probe vehicles between sparse updates, Transport. Res. Part C: Emerg. Technol., 65, 16, 10.1016/j.trc.2016.01.010 Wang, 2010, Parallel control and management for intelligent transportation systems: concepts, architectures, and applications, IEEE Trans. Intell. Transport. Syst., 11, 630, 10.1109/TITS.2010.2060218 Wang, 2016, Estimating control delays at signalised intersections using low-resolution transit bus-based global positioning system data, IET Intell. Transport. Syst., 10, 73, 10.1049/iet-its.2014.0246 Waterson, 2012, Quantifying the impact of probe vehicle localisation data errors on signalised junction control, IET Intell. Transp. Syst., 6, 197, 10.1049/iet-its.2010.0113 Wongpiromsarn, 2012, Distributed traffic signal control for maximum network throughput, 588 Wu, 2010, Energy and emission benefit comparison of stationary and in-vehicle advanced driving alert systems, Transport. Res. Rec.: J. Transport. Res. Board, 2189, 98, 10.3141/2189-11 Wu, 2018, Development and evaluation of bus lanes with intermittent and dynamic priority in connected vehicle environment, J. Intell. Transport. Syst., 22, 301, 10.1080/15472450.2017.1313704 Wu, 2016, Integrated optimization of bus priority operations in connected vehicle environment, J. Adv. Transport., 50, 1853, 10.1002/atr.1433 Wu, 2015, Distributed mutual exclusion algorithms for intersection traffic control, IEEE Trans. Parall. Distrib. Syst., 26, 65, 10.1109/TPDS.2013.2297097 Xie, 2011, Platoon-based self-scheduling for real-time traffic signal control, 879 Xie, 2012, Schedule-driven intersection control, Transport. Res. Part C: Emerg. Technol., 24, 168, 10.1016/j.trc.2012.03.004 Xie, 2018, A generic data assimilation framework for vehicle trajectory reconstruction on signalized urban arterials using particle filters, Transport. Res. Part C: Emerg. Technol., 92, 364, 10.1016/j.trc.2018.05.009 Xu, 2017, V2I based cooperation between traffic signal and approaching automated vehicles, 1658 Xu, 2018, Distributed conflict-free cooperation for multiple connected vehicles at unsignalized intersections, Transport. Res. Part C: Emerg. Technol., 93, 322, 10.1016/j.trc.2018.06.004 Yang, K., 2018. Real-time urban traffic control in a connected and automated vehicle environment. Ph.D. Thesis, ETH Zurich, CH. Yang, 2016, Isolated intersection control for various levels of vehicle technology: conventional, connected, and automated vehicles, Transport. Res. Part C: Emerg. Technol., 72, 109, 10.1016/j.trc.2016.08.009 Yang, 2018, Implementing transit signal priority in a connected vehicle environment with and without bus stops, Transport. B: Transp. Dynam., 1 Yang, 2017, Multi-scale perimeter control approach in a connected-vehicle environment, Transport. Res. Proc., 23, 101, 10.1016/j.trpro.2017.05.007 Yin, 2008, Robust optimal traffic signal timing, Transport. Res. Part B: Methodol., 42, 911, 10.1016/j.trb.2008.03.005 Yin, 2007, Offline offset refiner for coordinated actuated signal control systems, J. Transport. Eng., 133, 423, 10.1061/(ASCE)0733-947X(2007)133:7(423) Younes, 2016, Intelligent traffic light controlling algorithms using vehicular networks, IEEE Trans. Veh. Technol., 65, 5887, 10.1109/TVT.2015.2472367 Yu, 2018, Integrated optimization of traffic signals and vehicle trajectories at isolated urban intersections, Transport. Res. Part B: Methodol., 112, 89, 10.1016/j.trb.2018.04.007 Yun, 2012, Stochastic optimization for coordinated actuated traffic signal systems, J. Transport. Eng., 138, 819, 10.1061/(ASCE)TE.1943-5436.0000384 Zamanipour, 2016, Efficient priority control model for multimodal traffic signals, Transport. Res. Rec.: J. Transport. Res. Board, 2557, 86, 10.3141/2557-09 Zeng, 2015, Person-Based adaptive priority signal control with connected-vehicle information, Transport. Res. Rec.: J. Transport. Res. Board, 2487, 78, 10.3141/2487-07 Zhang, 2011, Optimizing minimum and maximum green time settings for traffic actuated control at isolated intersections, IEEE Trans. Intell. Transport. Syst., 12, 164, 10.1109/TITS.2010.2070795 Zhao, 2018, A platoon based cooperative eco-driving model for mixed automated and human-driven vehicles at a signalised intersection, Transport. Res. Part C: Emerg. Technol., 95, 802, 10.1016/j.trc.2018.05.025 Zheng, 2017, Estimating traffic volumes for signalized intersections using connected vehicle data, Transport. Res. Part C: Emerg. Technol., 79, 347, 10.1016/j.trc.2017.03.007 Zheng, 2010, Optimization of control parameters for adaptive traffic-actuated signal control, J. Intell. Transport. Syst., 14, 95, 10.1080/15472451003719756 Zheng, J., Sun, W., Huang, S., Shen, S., Yu, C., Zhu, J., Liu, B., Liu, H.X., 2018. Traffic Signal Optimization Using Crowdsourced Vehicle Trajectory Data (No. 18-05789). Zheng, 2013, Urban link travel time estimation based on sparse probe vehicle data, Transport. Res. Part C: Emerg. Technol., 31, 145, 10.1016/j.trc.2012.04.007 Zlatkovic, 2012, Development and evaluation of algorithm for resolution of conflicting transit signal priority requests, Transport. Res. Rec.: J. Transport. Res. Board, 2311, 167, 10.3141/2311-16