Scanning the Issue and Beyond: 

Merton's Laws and Mertionian Systems for ITS

THIS is my last editorial and I would like to take this opportunity to express my sincere thanks to those have devoted their time and efforts in helping me making this great publication more successful during my service. First of all, thanks to Dr. Simona Bertè, my only full-time staff member, who has worked extremely hard in keeping a smooth and timely operation, in making sure that we have followed all the rules and regulations set forth by IEEE, and that we have met our own professional norms and standards. To my three part-time assistants, Dr. Yanqing Gao of the University of Arizona for the first five years, and Dr. Xiao Wang of the Chinese Academy of Sciences and Ms. Stephanie Brown from IEEE for the last two years, many thanks for your dedication and support. During my seven-year term as the Editor in Chief, the number of manuscripts submitted and pages published annually have increased 317.4% (from 322 to 1022) and 500% (from 720 to 3600), respectively. This was achieved without any addition to our editorial team; therefore, much special appreciation and recognition must be given to the four of them!

The support and contribution from our reviewers, associate editors, and members of our advisory boardwere also extremely critical and important to the growth of this publication—my thanks for your hard work and apologies for pushing you hard in the process. To my colleagues on the Executive Committee and the Board of Governors, thanks for your support for many of my decisions, especially my initiative of establishing the new IEEE Transactions on Intelligent Vehicles, an important step for our future growth.

Last but not least, thanks to all who have submitted to our TRANSACTIONS, without your support and contribution, there will be no IEEE T-ITS!

My vision was to make our TRANSACTIONS a super highway for ITS publications: fast in motion, wide in capacity, and high in quality of services. Thank you all—our numbers have clearly demonstrated that IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS has made my dream a great reality today. I believe our new EiC, Professor Petros Ioannou, will lead the journal to a new level of success with your continued support.

Fig. 1. EiC Fei-Yue Wang and EiC Elect Petros Ioannou held the IEEE T-ITS at the IEEE ITSC 2015 in Las Palmas de Gran Canaria, Spain.

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MERTON'S LAWS AND MERTIONIAN SYSTEMS FOR ITS

Recently a group of physicists at Cornell University have demonstrated the control of quantum tunneling in an ultracold lattice gas by the measurement backaction imposed by an imaging process, a clear manifestation of the Quantum Zeno effect [1], [2]. By smoothly varying the rate at which atoms are imaged, they observed the continuous crossover from the “weak measurement regime” (in which position measurements have little influence on tunneling dynamics of the atomic ensemble) to the “strong measurement regime” (in which measurement-induced localization causes a dramatic suppression of tunneling). This investigation leads to an experimental demonstration of the paradigmatic Heisenberg microscope in a lattice gas and sheds light on the implication of quantum measurement on the coherent evolution of a mesoscopic quantum system. Their technique reveals a powerful tool for the control of an interacting many-body quantum system via spatially resolved measurement backaction.

Does this have anything to do with transportation research and application? Yes, very much to me. Why? If measurement-induced backaction can control interactingmany-body quantum systems, then message-induced influence would be an effective tool for control of interacting many-agent traffic systems. In other words, Merton’s laws can be powerful for transportation management and also for social transportation, an emerging field of research and development for intelligent transportation systems, which must be investigated and utilized along this direction.

As described in [1], in quantum mechanics, a measurement can be regarded as a dynamically tunable interaction between a quantum system and a “bath” whose intrinsic, spatial, and dynamical properties can be precisely engineered. As such, measurements can be used to guide or coax a quantum system into novel collective phases and nonequilibrium states that might otherwise be inaccessible through more conventional means of cooling or state preparation. While most of measurementinduced control schemes have hitherto been demonstrated in the context of single or weakly interacting quantum entities, the extension of these concepts to the arena of strongly interacting and correlated a tantalizing prospects.

If we replace terms “measurement” by “analysis,” “quantum” by “Mertonian,” and “bath” by “artificial system” in above description, the whole paragraph is equally valid for the control and management of complex social systems, such as transportation systems, called Mertonian systems, or simply Merton systems by ACP-based parallel mechanism [3]. In physics, a fundamental distinction between a classical (Newtonian) and a quantum system is its response to a measurement. While the act of measurement has no or negligible effect on the evolution of a classical system, it has a significant impact on the dynamics of a quantum system; thus, the call for Heisenberg’s Principle of Uncertainty. The difference between a Newton and a Merton system is similar: a Newton system can be measured or analyzed to arbitrary precision with negligible concomitant backaction, the act of measurement or analysis has profound consequences on the subsequent evolution of a Merton system. For example, weather prediction has no influence on future weather, but traffic or stock prediction might has a significant impact on future traffic or the stock market. Similarly, the parallel interaction between a quantum system and its “bath” can be applied for parallel control and management of Merton systems, particularly, complex transportation systems, and we hope the concomitant Quantum Zeno effect will lead to a dramatic suppression of traffic congestion.

Therefore, we need big data, Internet of things, cloud computing, machine learning, transportation games, total traffic control, social transportation, and many other new IT methods, i.e., Intelligent Techniques, to design various Merton’s laws for intelligent transportation control and management in smart societies. Yes, privacy will be a big issue here and, frankly, I do not see any perfect solution yet. However, I still recall what I had heard in my first driving course in Troy, New York: Driving is not a right, it is a privilege.

REFERENCES

[1] Y. S. Patil et al., “Quantum control by imaging: The Zeno effect in an ultracold lattice gas,” presented at the DAMOP15Meet. American Physical Society, Columbus, OH, USA, 2015, arXiv:1411.2678.

[2] Y. S. Patil et al., “Measurement-induced localization of an ultracold lattice gas,” Phys. Rev. Lett., vol. 115, no. 2, Oct. 2015, Art. ID 140 402, DOI: 10.1103/PhysRevLett.115.140402.

[3] F.-Y.Wang, “Parallel control and management for intelligent transportation systems: Concepts, architectures, and applications,” IEEE Trans. Intell. Transp. Syst., vol. 11, no. 3, pp. 630–638, Sep. 2010.

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Editor in Chief 

Fei-Yue Wang