Adaptive traffic light control using a wireless sensor network

Speaker : Sebastien Faye
Telecom ParisTech
Date: 23/10/2013
Time: 2:00 pm - 2:30 pm
Location: LINCS Seminars room


We consider the problem of controlling traffic lights in an
urban environment composed of multiple adjacent intersections by using
an intelligent transportation system to reduce congestion and delays.
Traditionally, each intersection is managed statically: the order and
durations of the green lights are pre-determined and do not adapt
dynamically to the traffic conditions. Detectors are sometimes used to
count vehicles on each lane of an intersection but the data they
report is generally used only to select between a few static sequences
and timings setups. Here, we detail and study TAPIOCA, a distribuTed
and AdaPtIve intersectiOns Control Algorithm that decides of a traffic
light schedule. After a review of relevant related works, we first
expose and evaluate the TAPIOCA algorithm, using the SUMO simulator
and the TAPAS Cologne dataset. We then study the use of a hierarchical
wireless sensor network deployed at intersections and the consequences
of losses and delays it induces on TAPIOCA. Last but not least, we
propose a prediction mechanism that alleviates these issues and show,
using co-simulation between SUMO and OMNeT++, that such interpolation
mechanisms are effectively able to replace missing or outdated data.
Biography: Sébastien Faye obtained a master degree in computer
science from the university of Picardie Jules Verne (Amiens, France)
in 2011. He is currently a PhD student at the Computer Science and
Networking Department (INFRES) of Telecom ParisTech (Paris, France).
His research interests include Intelligent Transportation Systems and
sensor networks.