Microsimulation Based Corrections on the Road Traffic Noise Emission Near intersections

摘要

Urban noise mapping traditionally involves the use of a traffic simulation model, which is often based on the estimation of macroscopic traffic flows. However, intersections and other local traffic management measures are not always modeled correctly. It is well known that the specific deceleration and acceleration dynamics of traffic at junctions can influence local noise emission. Finding the best strategy for using traffic modeling results in noise mapping is a current topic of research in the IMAGINE project. In this paper, a case study is presented, consisting of a large set of microscopic traffic simulations and associated noise emission calculations, which provides some insight into the specific dynamics of the noise emission near different types of intersections. It will be shown that it is possible to refine current traffic noise prediction models, based on macroscopic traffic simulation, using a correction on the average vehicle emission, aggregated in lane segments. A spatial approach should be used, in which inbound and outbound lanes are divided into deceleration, queuing, stopline and acceleration zones. Results from regression analysis on the numerical simulations indicate that meaningful relations between noise corrections and traffic flow parameters such as traffic intensity and composition can be deduced.