Towards intelligent transportation Cyber-Physical Systems: Real-time computing and communications perspectives

Traffic accidents and congestion problems continue to worsen worldwide. Because of vast number of vehicles manufactured and sold every year transportation sector is significantly stressed, leading to more accidents and fatalities, and adverse environmental and economic impact. Efforts across the world for Smart Transportation Cyber Physical Systems (CPS) are aimed at addressing a range of problems including reducing traffic accidents, decreasing congestion, reducing fuel consumption, reducing time spent on traffic jams, and improve transportation safety. Thus, smart transportation CPS is expected to contribute a main role in the design and development of intelligent transportation systems. The advances in embedded systems, wireless communications and sensor networks provides the opportunities to bridge the physical components and processes with the cyber world that leading to a Cyber Physical Systems (CPS). Feedback for control through wireless communication in transportation CPS is one of the major components for both safety and infotainment applications where vehicles exchange information using vehicle-to-vehicle (V2V) through vehicular ad hoc network (VANET) and/or vehicle-to-roadside (V2R) communications. For wireless communication IEEE has 802.11p standard for Dedicated Short Range Communication (DSRC) for Wireless Access for Vehicular Environment (WAVE). In this paper, we present how different parameters (e.g., sensing time, association time, number for vehicles, relative speed of vehicles, overlap transmission range, etc.) affect communication in smart transportation CPS. Furthermore, we also present driving components, current trends, challenges, and future directions for transportation CPS.

[1]  Sachin Shetty,et al.  Enhancing connectivity for spectrum-agile Vehicular Ad hoc NETworks in fading channels , 2014, 2014 IEEE Intelligent Vehicles Symposium Proceedings.

[2]  Sachin Shetty,et al.  Dynamic Spectrum Access for Wireless Networks , 2015, SpringerBriefs in Electrical and Computer Engineering.

[3]  Gongjun Yan,et al.  Enhancing VANET Performance by Joint Adaptation of Transmission Power and Contention Window Size , 2011, IEEE Transactions on Parallel and Distributed Systems.

[4]  R. A. Grant,et al.  Building and testing a causal model of an information technology's impact , 1989, ICIS '89.

[5]  D. Rawat,et al.  Security, Privacy, Trust, and Resource Management in Mobile and Wireless Communications , 2013 .

[6]  A.F. Gomez-Skarmeta,et al.  Experimental evaluation of a novel vehicular communication paradigm based on cellular networks , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[7]  Gongjun Yan,et al.  Towards Secure Vehicular Clouds , 2012, 2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems.

[8]  Adib Kanafani,et al.  Local Air Service and Economic Impact of Small Airports , 1987 .

[9]  Danda B. Rawat,et al.  Cyber-Physical Systems: From Theory to Practice , 2015 .

[10]  Stephan Olariu,et al.  Towards Autonomous Vehicular Clouds - A Position Paper (Invited Paper) , 2011, ADHOCNETS.

[11]  Chris Nash INTEGRATION OF PUBLIC TRANSPORT: AN ECONOMIC ASSESSMENT , 1988 .

[12]  Stephan Olariu,et al.  Towards autonomous vehicular clouds , 2011, EAI Endorsed Trans. Mob. Commun. Appl..