TY  - JOUR
PY  - 2019//
TI  - A neuroevolutionary approach to controlling traffic signals based on data from sensor network
JO  - Sensors (Basel)
A1  - Bernaś, Marcin
A1  - Płaczek, Bartłomiej
A1  - Smyła, Jarosław
SP  - s19081776
EP  - s19081776
VL  - 19
IS  - 8
N2  - The paper introduces an artificial neural network ensemble for decentralized control of traffic signals based on data from sensor network. According to the decentralized approach, traffic signals at each intersection are controlled independently using real-time data obtained from sensor nodes installed along traffic lanes. In the proposed ensemble, a neural network, which reflects design of signalized intersection, is combined with fully connected neural networks to enable evaluation of signal group priorities. Based on the evaluated priorities, control decisions are taken about switching traffic signals. A neuroevolution strategy is used to optimize configuration of the introduced neural network ensemble. The proposed solution was compared against state-of-the-art decentralized traffic control algorithms during extensive simulation experiments. The experiments confirmed that the proposed solution provides better results in terms of reduced vehicle delay, shorter travel time, and increased average velocity of vehicles.<p />  <p>Language: en</p>
LA  - en
SN  - 1424-8220
UR  - http://dx.doi.org/10.3390/s19081776
ID  - ref1
ER  -