Automated Vehicle Traffic Control Tower: A Solution to Support the Next Level Automation
Automated vehicles (AVs) have the potential to enhance road capacity, improving road safety and traffic efficiency. Research and development on AVs have been going on for many years. However, when the complicated traffic rules and real situations interacted, AVs fail to make decisions on contradicting situations, and are not able to have control in all conditions due to highly dynamic driving scenarios. This limits AVs’ usage and restricts the full potential benefits that they can bring. Furthermore, regulations, infrastructure development, and public acceptance cannot keep up at the same pace as technology breakthroughs. Facing these challenges, this paper proposes automated vehicle traffic control tower (AVTCT) acting as a safe, efficient and integrated solution for AV control. It introduces a concept of AVTCT for control, management, decision-making, communication and interaction with various aspects in transportation. With the prototype demonstrations and simulations, AVTCT has the potential to overcome the control challenges with AVs and can facilitate AV reaching their full potential. Possible functionalities, benefits as well as challenges of AVTCT are discussed, which set the foundation for the conceptual model, simulation and real application of AVTCT.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 322
 Ahmad, S., & Saxena, V. (2008). Design of formal air traffic control system through UML. Ubiquitous computing and communication journal, 3(6), 11-20.
 Amer, N. H., Zamzuri, H., Hudha, K., & Kadir, Z. A. (2017). Modelling and control strategies in path tracking control for autonomous ground vehicles: a review of state of the art and challenges. Journal of Intelligent & Robotic Systems, 86(2), 225-254.
 Andersen, H., Shen, X., Eng, Y. H., Rus, D., & Ang, M. H. (2017). Connected Cooperative Control of Autonomous Vehicles During Unexpected Road Situations. Mechanical Engineering Magazine Select Articles, 139(12), S3-S7.
 Bagloee, S. A., Tavana, M., Asadi, M., & Oliver, T. (2016). Autonomous vehicles: challenges, opportunities, and future implications for transportation policies. Journal of Modern Transportation, 24(4), 284-303.
 Bierstedt, J., Gooze, A., Gray, C., Peterman, J., Raykin, L., & Walters, J. (2014). Effects of next-generation vehicles on travel demand and highway capacity. FP Think Working Group, 10-11.
 Campbell, M., Egerstedt, M., How, J. P., & Murray, R. M. (2010). Autonomous driving in urban environments: approaches, lessons and challenges. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 368(1928), 4649-4672.
 Campbell, S., Naeem, W., & Irwin, G. W. (2012). A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance manoeuvres. Annual Reviews in Control, 36(2), 267-283.
 Campolo, C., Molinaro, A., Araniti, G., & Berthet, A. O. (2017). Better platooning control toward autonomous driving: An LTE Device-to-Device communications strategy that meets ultralow latency requirements. IEEE Vehicular Technology Magazine, 12(1), 30-38.
 Casner, S. M., Hutchins, E. L., & Norman, D. (2016). The challenges of partially automated driving. Communications of the ACM, 59(5), 70-77.
 Coppola, R., & Morisio, M. (2016). Connected car: technologies, issues, future trends. ACM Computing Surveys (CSUR), 49(3), 46.
 D'Ariano, A. (2009). Innovative decision support system for railway traffic control. IEEE Intelligent Transportation Systems Magazine, 1(4), 8-16.
 Dadashi, N., Wilson, J. R., Golightly, D., & Sharples, S. (2014). A framework to support human factors of automation in railway intelligent infrastructure. Ergonomics, 57(3), 387-402.
 Dickmanns, E. D., & Graefe, V. (1988). Dynamic monocular machine vision. Machine vision and applications, 1(4), 223-240.¨
 De Winter, J. C., Happee, R., Martens, M. H., & Stanton, N. A. (2014). Effects of adaptive cruise control and highly automated driving on workload and situation awareness: A review of the empirical evidence. Transportation research part F: traffic psychology and behaviour, 27, 196-217.
 Di Taranto, R., Muppirisetty, S., Raulefs, R., Slock, D., Svensson, T., & Wymeersch, H. (2014). Location-aware communications for 5G networks: How location information can improve scalability, latency, and robustness of 5G. IEEE Signal Processing Magazine, 31(6), 102-112.
 Drive Sweden (2017) Autonomous Driving Aware Traffic Control - Final Report Accessed 2020-04-02
 Endsley, M. R. (2017). From here to autonomy: lessons learned from human–automation research. Human factors, 59(1), 5-27.
 Ericsson (2018) Ericsson Mobility Report June 2018, The Industry Impact OF 5G - Ericsson
 EBN(2016), Autopilot: Flying vs. Driving Accessed 2020-04-02
 Fagnant, D. J., Kockelman, K. M., & Bansal, P. (2015). Operations of shared autonomous vehicle fleet for austin, texas, market. Transportation Research Record: Journal of the Transportation Research Board, (2536), 98-106.
 Fürstenau, N., Schmidt, M., Rudolph, M., Möhlenbrink, C., Papenfuß, A., & Kaltenhäuser, S. (2009). Steps towards the virtual tower: remote airport traffic control center (RAiCe). Reconstruction, 1(2), 14.
 Gawade, M., & Zhang, Y. (2016). Synthesis of Remote Air Traffic Control System and Air Traffic Controllers’ Perceptions. Transportation Research Record: Journal of the Transportation Research Board, (2600), 49-60.
 Gerla, M., Lee, E. K., Pau, G., & Lee, U. (2014, March). Internet of vehicles: From intelligent grid to autonomous cars and vehicular clouds. In Internet of Things (WF-IoT), 2014 IEEE World Forum on (pp. 241-246). IEEE.
 Goodall, N. J. (2014, September). Vehicle automation and the duty to act. In Proceedings of the 21st world congress on intelligent transport systems (pp. 7-11).
 Hancock, P. A., Jagacinski, R. J., Parasuraman, R., Wickens, C. D., Wilson, G. F., & Kaber, D. B. (2013). Human-automation interaction research: Past, present, and future. ergonomics in design, 21(2), 9-14.
 Heape S. (2012) The changing role of the control room operator in metro rail: automation and the challenge of maintaining situation awareness.
 Higgins, T. (2016). Google’s Self-Driving Car Program Odometer Reaches 2 Million Miles. The Wall Street Journal, 18.
 Huang, J., Qian, F., Guo, Y., Zhou, Y., Xu, Q., Mao, Z. M., ... & Spatscheck, O. (2013). An in-depth study of LTE: effect of network protocol and application behavior on performance. ACM SIGCOMM Computer Communication Review, 43(4), 363-374.
 Kaber, D. B., & Endsley, M. R. (2004). The effects of level of automation and adaptive automation on human performance, situation awareness and workload in a dynamic control task. Theoretical Issues in Ergonomics Science, 5(2), 113-153.
 Kang, L., Zhao, W., Qi, B., & Banerjee, S. (2018, February). Augmenting Self-Driving with Remote Control: Challenges and Directions. In Proceedings of the 19th International Workshop on Mobile Computing Systems & Applications (pp. 19-24). ACM.
 Kong, L., Khan, M. K., Wu, F., Chen, G., & Zeng, P. (2017). Millimeter-wave wireless communications for IoT-cloud supported autonomous vehicles: Overview, design, and challenges. IEEE Communications Magazine, 55(1), 62-68.
 Kumar, V., Mishra, S. and Chand, N. (2013) Applications of VANETs: Present & Future. Communications and Network, 5, 12-15.
 Kyriakidis, M., Happee, R., & de Winter, J. C. (2015). Public opinion on automated driving: Results of an international questionnaire among 5000 respondents. Transportation research part F: traffic psychology and behaviour, 32, 127-140.
 Khodayari, A., Ghaffari, A., Ameli, S., & Flahatgar, J. (2010, September). A historical review on lateral and longitudinal control of autonomous vehicle motions. In Mechanical and Electrical Technology (ICMET), 2010 2nd International Conference on (pp. 421-429). IEEE.
 Latombe, J. C. (2012). Robot motion planning (Vol. 124). Springer Science & Business Media.
 Liu, Z., Zhang, Y., Yu, X., & Yuan, C. (2016). Unmanned surface vehicles: An overview of developments and challenges. Annual Reviews in Control, 41, 71-93.
 Lu, N., Cheng, N., Zhang, N., Shen, X., & Mark, J. W. (2014). Connected vehicles: Solutions and challenges. IEEE internet of things journal, 1(4), 289-299.
 Lu, Z., Happee, R., Cabrall, C. D., Kyriakidis, M., & de Winter, J. C. (2016). Human factors of transitions in automated driving: A general framework and literature survey. Transportation research part F: traffic psychology and behaviour, 43, 183-198.
 Manske, P. G., & Schier, S. L. (2015). Visual scanning in an air traffic control tower–A simulation study. Procedia Manufacturing, 3, 3274-3279.
 Melcher, V., Rauh, S., Diederichs, F., Widlroither, H., & Bauer, W. (2015). Take-over requests for automated driving. Procedia Manufacturing, 3, 2867-2873.
 Merat, N., Jamson, A. H., Lai, F. C., Daly, M., & Carsten, O. M. (2014). Transition to manual: Driver behaviour when resuming control from a highly automated vehicle. Transportation research part F: traffic psychology and behaviour, 27, 274-282.
 Merat, N., Jamson, A. H., Lai, F. C., & Carsten, O. (2012). Highly automated driving, secondary task performance, and driver state. Human factors, 54(5), 762-771.
 Merat, N., & Lee, J. D. (2012). Preface to the special section on human factors and automation in vehicles: Designing highly automated vehicles with the driver in mind. Human factors, 54(5), 681-686.
 Mir, Z. H., & Filali, F. (2014). LTE and IEEE 802.11 p for vehicular networking: a performance evaluation. EURASIP Journal on Wireless Communications and Networking, 2014(1), 89.
 NHTSA (2013) US department of transportation policy on automated vehicle development, p 4
 Nikitas, A., Kougias, I., Alyavina, E., & Njoya Tchouamou, E. (2017). How Can Autonomous and Connected Vehicles, Electromobility, BRT, Hyperloop, Shared Use Mobility and Mobility-As-A-Service Shape Transport Futures for the Context of Smart Cities? Urban Science, 1(4), 36.
 Ohnemus, M., & Perl, A. (2016). Shared Autonomous Vehicles: Catalyst of New Mobility for the Last Mile? Built Environment, 42(4), 589-602.
 Parasuraman, R., & Manzey, D. H. (2010). Complacency and bias in human use of automation: An attentional integration. Human Factors: The Journal of the Human Factors and Ergonomics Society, 52(3), 381–410.
 Pendleton, S. D., Andersen, H., Du, X., Shen, X., Meghjani, M., Eng, Y. H., ... & Ang, M. H. (2017). Perception, planning, control, and coordination for autonomous vehicles. Machines, 5(1), 6.
 Payre, W., Cestac, J., & Delhomme, P. (2014). Intention to use a fully automated car: Attitudes and a priori acceptability. Transportation research part F: traffic psychology and behaviour, 27, 252-263. Pollard, E., Nashashibi, F., & Resende, P. (2013). ABV-A Low Speed Automation Project to Study the Technical Feasibility of Fully Automated Driving. ERCIM News, (94), 8-9.
 Piao, J., McDonald, M., Hounsell, N., Graindorge, M., Graindorge, T., & Malhene, N. (2016). Public views towards implementation of automated vehicles in urban areas. Transportation Research Procedia, 14, 2168-2177.
 Ray, S., Chen, W., Bhadra, J., & Al Faruque, M. A. (2017, June). Extensibility in automotive security: Current practice and challenges. In Design Automation Conference (DAC), 2017 54th ACM/EDAC/IEEE (pp. 1-6). IEEE.
 SAE J3016 Standard. http://standards.sae.org/j3016_201609/. (September 2016).
 Schoettle, B., & Sivak, M. (2015). A preliminary analysis of real-world crashes involving self-driving vehicles. University of Michigan Transportation Research Institute.
 Schmidt, M., Rudolph, M., Papenfuss, A., Friedrich, M., Möhlenbrink, C., Kaltenhäuser, S., & Fürstenau, N. (2009, October). Remote airport traffic control center with augmented vision video panorama. In Digital Avionics Systems Conference, 2009. DASC'09. IEEE/AIAA 28th (pp. 4-E). IEEE.
 Seppelt, B. D., & Victor, T. W. (2016). Potential solutions to human factors challenges in road vehicle automation. In Road Vehicle Automation 3 (pp. 131-148). Springer, Cham.
 Strand, N., Nilsson, J., Karlsson, I. M., & Nilsson, L. (2014). Semi-automated versus highly automated driving in critical situations caused by automation failures. Transportation research part F: traffic psychology and behaviour, 27, 218-228.
 Talebpour, A., & Mahmassani, H. S. (2016). Influence of connected and autonomous vehicles on traffic flow stability and throughput. Transportation Research Part C: Emerging Technologies, 71, 143-163.
 Tummala, R., Wolter, K. J., Sundaram, V., Smet, V., & Raj, P. M. (2016, January). New era in automotive electronics, a co-development by Georgia tech and its automotive partners. In Pan Pacific Microelectronics Symposium (Pan Pacific), 2016(pp. 1-4). IEEE.
 Tuohy, S., Glavin, M., Hughes, C., Jones, E., Trivedi, M., & Kilmartin, L. (2015). Intra-vehicle networks: A review. IEEE Transactions on Intelligent Transportation Systems, 16(2), 534-545.
 Vahidi, A., & Eskandarian, A. (2003). Research advances in intelligent collision avoidance and adaptive cruise control. IEEE transactions on intelligent transportation systems, 4(3), 143-153.
 Vlachos, E., Lalos, A. S., Berberidis, K., & Tselios, C. (2017, June). Autonomous driving in 5G: Mitigating interference in OFDM-based vehicular communications. In Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), 2017 IEEE 22nd International Workshop on (pp. 1-6). IEEE.
 Watts, J. M. (2016). World’s First Self-Driving Taxis Hit the Road in Singapore. The Wall Street Journal.
 Waymo. (2017). On the road to fully self-driving, Waymo safety report. Accessed 2020-04-02
 Wired, (2017) Nissan's Path to Self-Driving Cars? Humans in Call Centers Accessed 2020-04-02
 Wired, (2018) Self-Driving Cars Have a Secret Weapon: Remote Control Accessed 2020-04-02
 Young, M. S., & Stanton, N. A. (2007). What's skill got to do with it? Vehicle automation and driver mental workload. Ergonomics, 50(8), 1324-1339.
 Zeeb, K., Buchner, A., & Schrauf, M. (2015). What determines the take-over time? An integrated model approach of driver take-over after automated driving. Accident Analysis & Prevention, 78, 212-221.
 Zheng, K., Zheng, Q., Yang, H., Zhao, L., Hou, L., & Chatzimisios, P. (2015). Reliable and efficient autonomous driving: the need for heterogeneous vehicular networks. IEEE Communications Magazine, 53(12), 72-79.
 Zhu, H., Yuen, K. V., Mihaylova, L., & Leung, H. (2017). Overview of environment perception for intelligent vehicles. IEEE Transactions on Intelligent Transportation Systems, 18(10), 2584-2601.
 https://phantom.auto/media/ accessed 2020-07-02
 https://starsky.io/ accessed 2020-07-02