Virtual Traffic Lights: System Design and Implementation
July 04, 2018 Β· Declared Dead Β· π IEEE Vehicular Technology Conference
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Rusheng Zhang, Frank Schmutz, Kyle Gerard, AurΓ©lien Pomini, Louis Basseto, Sami Ben Hassen, Akihiro Ishikawa, Inci Ozgunes, Ozan Tonguz
arXiv ID
1807.01633
Category
cs.NI: Networking & Internet
Citations
32
Venue
IEEE Vehicular Technology Conference
Last Checked
6 months ago
Abstract
Traffic congestion is a daunting problem that is affecting the daily lives of billions of people across the world. Recently, a promising new traffic control scheme known as Virtual Traffic Lights (VTL) has been proposed for mitigating traffic congestion. VTL is an infrastructure free traffic control scheme that leverages the presence of Vehicle-to-Vehicle (V2V) communications. Such infrastructure free scheme has several benefits, such as alleviating traffic congestion; reducing the large cost of traffic lights and traffic control systems; reducing carbon emission, etc. This paper reports a DSRC-based prototype design effort on VTL using Dedicated Short Range Communications (DSRC) technology. The experiments performed show the feasibility of implementing VTL with DSRC technology. Preliminary results of the field tests conducted in Pittsburgh with vehicles using VTL equipment indicate that VTL is capable of coordinating traffic at intersections and reducing the commute time of people.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Networking & Internet
R.I.P.
π»
Ghosted
π
π
The Cartographer
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
π
π
The Cartographer
A Survey of Indoor Localization Systems and Technologies
R.I.P.
π»
Ghosted
Survey of Important Issues in UAV Communication Networks
π
π
The Cartographer
Network Function Virtualization: State-of-the-art and Research Challenges
π
π
The Cartographer
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted