Applying Intelligent Transport Systems to manage noise impacts
Invited paper
TNO
Tuesday 2 june, 2015, 11:20 - 11:40
0.3 Copenhagen (49)
Abstract:
This contribution discusses how traffic management, and many other measures that can be categorised as Intelligent Transport Systems (ITS, i.e. all traffic and transport measures that use ICT) can help reduce noise levels by influencing mobility choices and driving behaviour. Several examples of such measures and how they impact noise levels will be given, ranging from giving travel, route or departure time advice to automated driving (“self-driving vehicles”).
Cities are growing and urban congestion levels are expected to rise as well, as there is not much room, or budget, to add infrastructure. Thus, the emphasis is on better use of the existing infrastructure through many different ITS measures – fitting with the idea of Smart Cities. Information about what are the most promising ITS measures is becoming available, using results from field tests and widespread implementations of some more mature measures. If we can inform travellers of the alternatives they have for their trips (pre-trip and on-trip), they can make better choices (or their in-car systems can do that for them). Impacts on noise will need to be compared to impacts related to other policy goals cities have (e.g. accessibility/travel times, traffic safety, air quality). Decision support models that enable multi-criteria optimisation can be deployed to make it easier for road authorities, traffic operators and service providers (e.g. of travel advice apps) to decide how and when a measure should be applied. Traffic simulation models can be used, off-line or real-time, to evaluate what order of magnitude of traffic effects measures will have. Depending on the type of measure, and what travel choices are influenced, a microscopic (modelling individual vehicles and drivers) or macroscopic (model traffic flows at the link level) is used.