ZTE

ZTE Communications ›› 2014, Vol. 12 ›› Issue (1): 11-16.doi: 10.3969/j.issn.1673-5188.2014.01.002

• Special Topic • Previous Articles     Next Articles

Advanced Leader Election for Virtual Traffic Lights

Florian Hagenauer, Patrick Baldemaier, Falko Dressler, Christoph Sommer   

  1. Institute of Computer Science, University of Innsbruck, Technikerstr.21a, 6020 Innsbruck, Austria
  • Received:2014-02-17 Online:2014-03-25 Published:2014-03-25
  • About author:Florian Hagenauer (hagenauer@ccs-labs.org) received his BSc and MSc degrees in computer science from the University of Innsbruck, Austria, in 2011 and 2013, respectively. In October 2013, he joined the Computer and Communication Systems Group to work on problems in Car-to-X communication.
    Patrick Baldemaier (patrick.baldemaier@ccs-labs.org) received his BSc in computer science from the University of Innsbruck, Austria, in 2012. Since October 2013, he has been working on his master thesis "Simulation of Self-Organizing Intersection Management" at the Computer and Communication Systems Group.
    Falko Dressler (dressler@ccs-labs.org) is a full professor of computer science and head of the Computer and Communication Systems Group at the Institute of Computer Science, University of Innsbruck. Dr. Dressler received his MSc and PhD degrees in computer science from the Department of Computer Science, University of Erlangen, in 1998 and 2003. He is an editor for IEEE Trans. on Mobile Computing, Elsevier Ad Hoc Networks, ACM/Springer Wireless Networks (WINET), and Elsevier Nano Communication Networks. He regularly serves in the TPC of networking conferences such as IEEE INFOCOM, IEEE ICC, IEEE GLOBECOM, and IEEE WCNC. Dr. Dressler has written textbooks, including "Self-Organization in Sensor and Actor Networks," which was published by Wiley in 2007. Dr. Dressler is an IEEE Distinguished Lecturer in the fields of inter-vehicular communication, self-organization, and bio-inspired and nano-networking. Dr. Dressler is a Senior Member of the IEEE (COMSOC, CS, VTS) as well as a senior member of ACM (SIGMOBILE), and member of GI (KuVS). His research activities are focused on adaptive wireless networking and self-organization methods with applications in wireless ad hoc and sensor networks, inter-vehicular communication, bio-inspired and nano-networking, and network security.
    Christoph Sommer (sommer@ccs-labs.org) received his PhD degree in engineering (Dr. - Ing., with distinction) and his MSc degree in computer science (Dipl. - Inf. Univ.) from the University of Erlangen in 2011 and 2006, respectively. In 2010, he was a visiting scholar with the research group of Ozan K. Tonguz at the Electrical and Computer Engineering Department of Carnegie Mellon University (CMU). In 2012, he was a visiting scholar with the research group of Mario Gerla at the Computer Science Department of the University of California, Los Angeles (UCLA). He is currently a postdoctoral researcher with the Computer and Communication Systems group at the University of Innsbruck. Since 2011, he has been a member of the ACM/Springer Wireless Networks (WINET) editorial board. His research is focused on questions regarding traffic efficiency and safety, as well as on security aspects of Car-to-X communication in heterogeneous environments.

PDF (PC)

Abstract: We examine the network performance of algorithms for self-organized traffic management. In particular, we focus on wireless networking between cars. One of many technologies that make road traffic safer and more efficient is the Virtual Traffic Light (VTL) system, which is able to coordinate the traffic flow at intersections without the need for physical lights. VTL takes a leading vehicle at an intersection and uses it to control the traffic lights. We developed algorithms for leader election and traffic light computation in realistic vehicular networking scenarios. Our key contribution is the extension of this algorithm to support arbitrary intersection layouts. We investigated the proposal in synthetic and realistic scenarios. The results show that, overall, VTLs use network resources efficiently and positively influences driving experience. It performs better than stationary traffic lights for a low to medium network load. We also identify potential optimizations to deal with high network load and to improve fairness.

Key words: virtual traffic lights, self-organization, vehicular networks