3 research outputs found
Traffic-light control in urban environment exploiting drivers’ reaction to the expected red lights duration
Traffic congestion in urban environment is one of the most critical issue for drivers and city planners for both environment and efficiency reasons. Traffic lights are one of the main tools used to regulate traffic by diverting the drivers between different paths. Rational drivers, in turn, react to the traffic light duration by evaluating their options and, if necessary, by changing direction in order to reach their destination quicker. In this paper, we introduce a macroscopic traffic model for urban intersections that incorporates this rational behavior of the drivers. Then, we exploit it to show that, by providing additional information about the expected red-time duration to the drivers, one can decrease the amount of congestion in the network and the overall length of the queues at the intersections. Additionally, we develop a control policy for the traffic lights that exploits the reaction of the drivers in order to divert them to a different route to further increase the performances. These claims are supported by extensive numerical simulations
Traffic-light control in urban environment exploiting drivers' reaction to the expected red lights duration
Traffic congestion in urban environment is one of the most critical issue for drivers and city
planners for both environment and efficiency reasons. Traffic lights are one of the main tools
used to regulate traffic by diverting the drivers between different paths. Rational drivers, in
turn, react to the traffic light duration by evaluating their options and, if necessary, by changing
direction in order to reach their destination quicker. In this paper, we introduce a macroscopic
traffic model for urban intersections that incorporates this rational behavior of the drivers.
Then, we exploit it to show that, by providing additional information about the expected redtime
duration to the drivers, one can decrease the amount of congestion in the network and the
overall length of the queues at the intersections. Additionally, we develop a control policy for
the traffic lights that exploits the reaction of the drivers in order to divert them to a different
route to further increase the performances. These claims are supported by extensive numerical
simulations