A V2I communication-based pipeline model for adaptive urban traffic light scheduling

  • Libing WuEmail author
  • Lei Nie
  • Samee U. Khan
  • Osman Khalid
  • Dan Wu
Research Article


Adaptive traffic light scheduling based on realtime traffic information processing has proven effective for urban traffic congestion management. However, fine-grained information regarding individual vehicles is difficult to acquire through traditional data collection techniques and its accuracy cannot be guaranteed because of congestion and harsh environments. In this study, we first build a pipeline model based on vehicle-to-infrastructure communication, which is a salient technique in vehicular adhoc networks. This model enables the acquisition of fine-grained and accurate traffic information in real time via message exchange between vehicles and roadside units. We then propose an intelligent traffic light scheduling method (ITLM) based on a “demand assignment” principle by considering the types and turning intentions of vehicles. In the context of this principle, a signal phase with more vehicles will be assigned a longer green time. Furthermore, a green-way traffic light scheduling method (GTLM) is investigated for special vehicles (e.g., ambulances and fire engines) in emergency scenarios. Signal states will be adjusted or maintained by the traffic light control system to keep special vehicles moving along smoothly. Comparative experiments demonstrate that the ITLM reduces average wait time by 34%–78% and average stop frequency by 12%–34% in the context of traffic management. The GTLM reduces travel time by 22%–44% and 30%–55% under two types of traffic conditions and achieves optimal performance in congested scenarios.


traffic light scheduling vehicular ad hoc networks pipeline model vehicle-to-infrastructure communication intersection 


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This work is supported by the National Natural Science Foundation of China (Grant Nos. 61472287, 61572370), and the Science and Technology Support Program of Hubei Province (2015CFA068).

Supplementary material

11704_2017_7043_MOESM1_ESM.ppt (294 kb)
A V2I Communication Based Pipe Model for Adaptive Urban Traffic Light Scheduling


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Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Libing Wu
    • 1
    • 2
    Email author
  • Lei Nie
    • 2
    • 3
  • Samee U. Khan
    • 4
  • Osman Khalid
    • 5
  • Dan Wu
    • 6
  1. 1.State Key Laboratory of Software EngineeringWuhan UniversityWuhanChina
  2. 2.Computer SchoolWuhan UniversityWuhanChina
  3. 3.School of Computer Science and TechnologyWuhan University of Science and TechnologyWuhanChina
  4. 4.Department of Electrical and Computer EngineeringNorth Dakota State UniversityFargoUSA
  5. 5.COMSATS Institute of Information TechnologyIslamabadPakistan
  6. 6.School of Computer ScienceUniversity of WindsorWindsor, OntarioCanada

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