A distributed algorithm for multiple intersections adaptive traffic lights control using a wireless sensor networks

Smart Cities: Study and Comparison of Traffic Light Optimization in Modern Urban Areas Using Artificial Intelligence

“…Their algorithm uses a conflict matrix, which describes all possible cases of contradictory movements and results in the creation of phases, in order to manage the traffic light in an optimal and more efficient way. In [20,23] the authors presented and evaluated Distributed and Adaptive Intersections Control Algorithm (DAPIOCA). This algorithm uses a network of wireless sensors, which aims to collect information on vehicles located on the queue in order to calculate the duration of the green light, and to apply a traffic management strategy following the steps of the algorithm (Vehicles logging, Counting, Next phase definition, Information propagation, and Inter-intersection vehicles monitoring), which defines the sequence and duration of green lights in an intelligent transport system in the case of several intersections in order to reduce the time (AWT) of the users.…”

“…Tables 2 and 3) obviously leads to a clear advantage for researchers [19], [20] who have used the queue theory. In addition, they tested their models on a simple intersection as well as multiple intersections, so as to create green wave (synchronizing successive lights), which will have well on a positive point to reduce the length of the waiting queue and minimize the average waiting time.…”

Characterizing the Topology of an Urban Wireless Sensor Network for Road Traffic Management

“…(4) two sensors per lane (red dots on Fig. 1(d)): one recording the arrivals and the other capturing the departure process [3].…”

“…Intelligent Transportation Systems (ITS) are now able to control traffic lights, limit congestion, prevent accidents and reduce pollution or noise levels. In this context, the success of today's embedded systems allows deploying a dense network of detectors and actuators that communicate using wireless communications [1], [2], [3]. Tiny devices can be installed at traffic lights, or on urban lighting systems to measure carbon dioxide, micro-particle or noise levels, or to count vehicles using a magnetometer or a camera.…”

“…A decentralized system that works locally naturally alleviates this problem. Taking advantage of the distributed computing results, such devices can easily communicate together and rapidly adapt the traffic light plans to solve a situation [3]. This type of architecture can make intersections or urban areas totally autonomous and independent of any central entity, in addition to increase fault tolerance.…”