Improving noise assessment at intersections by modeling traffic dynamics

نویسنده

  • E. Chevallier
چکیده

Three families of road noise prediction models can be distinguished depending on the way they account for traffic flow. Static noise models only consider free-flow constant-speed traffic with uniformly distributed vehicles. Analytic noise models assume that all vehicles are isolated from one another but account for their mean kinematic profile over the network. Micro-simulation noise models relax the hypothesis of no interaction between vehicles and fully capture traffic flow dynamic effects such as queue evolution. This study compares the noise levels obtained by these three methodologies at signalized intersections and roundabouts. It reveals that micro-simulation noise models outperform the other approaches. Particularly, they are able to capture the effects of stochastic transient queues in undersaturated conditions as well as stop-and-go behaviors in oversaturated regime. Accounting for traffic dynamics is also shown to improve predictions of noise variations due to different junction layouts. In this paper, a roundabout is found to induce a 2.5dB(A) noise abatement compared to a signalized intersection in undersaturated conditions while the acoustic contributions of both kinds of junctions balance in oversaturated regime.

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تاریخ انتشار 2008