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• W175367462 abstract "Bad air quality is an increasing problem in most European countries and also in the Netherlands. A growing awareness of the effects of bad air quality on the environment and health has put the air quality issue high on the political agenda. Road traffic is one of the major air polluters in Europe. Especially near main arteries and in dense areas European air quality standards are being transgressed due the presence of lively and much road traffic. Especially excessive concentrations of Nitro Oxides (NOx) and Particulate IVIatter (PM) cause problems. Dynamic Traffic Management (DTM) is often mentioned as one of the possibilities reduce the polluting character of road traffic. These observations lead the main research question for this study: To what can DTM measures contribute an improvement of air quality? The goal set for this study is investigate the possibilities calculate the effects of DTM measures on air quality using microscopic traffic modelling. A calculation model can then be used answer the main research question. Polluting character of road traffic Initially the characteristics of road traffic are investigated that cause its polluting character. Here fore, road traffic characteristics are subdivided into two groups: vehicle characteristics and operational characteristics. Literature study has lead the conclusion that both vehicle characteristics and operational characteristics contribute significantly the polluting character of road traffic. Vehicle characteristics that increase the polluting character are: Large vehicle weights, large engine sizes, diesel engines (PM and NOx), old vehicles (outdated environmental class) and poor vehicle maintenance. Furthermore the use of exhaust after treatment devices (catalyst converter and soot filter) has a large reducing effect off vehicle emissions. Operational characteristics that increase the polluting character are: highly dynamic driving with many acceleration and deceleration activities (transient state driving), extreme high and extreme low average speeds and many stops. Driving profile description In order be able investigate the quantitative impact of driving profile differences on emission rates, a driving profile should be described by characteristics that can be quantified. Each describing characteristic should comply with two boundary conditions; it should have a direct relation with emission rates and it should be measurable or calculable from a microscopic traffic model. All mechanical characteristics of vehicle operation lil<e engine speed and throttle position can therefore not be included. The following 8 characteristics have been selected: Average speed, speed deviation, average acceleration rate, number of stops per minute and the four driving mode proportions (acceleration time, deceleration time, constant speed time and idling time). Measured driving profiles and emission rates from the German HBEFA model have indicated the direct relations of the characteristics with vehicle emission rates. State of the art emission modelling Literature study of emission modelling in Europe has resulted in an overview of state of the art emission models that nowadays are used for emission calculations. The Dutch traffic situation model VERSIT+ is assessed as one of the best state of the art emission models at this moment. This model uses an extensive set of parameters describe a driving profile. Multiple regression (using an extensive database of measured driving profiles) is use d determine the emission rates that match a driving profile. Microscopic traffic modelling and emission calculation The microscopic traffic model VISSIM is used as tool assess the effects of DTM measures in a case study. VISSIM was developed as a simulation tool for capacity and travel time calculations. The experience with VISSIM in accurate emission modelling is few. The value of driving profiles that are generated during a VISSIM simulation is uncertain. However, for this study, the VISSIM model is the only model available. The effect of DTM measures on vehicle emissions In order select DTM measures that have the maximal positive effect on vehicle emissions, initially a short list is made of all DTM measures stated in the Handbook for sustainable traffic management (Rijkswaterstaat, 2003). This short list has been assessed using the knowledge from previous literature studies. The impact of the DTM measures has been assessed based on the expected impact on the 8 characteristics of a driving profile. Two DTM measured have been selected because their effects on driving profiles are considered be very positive: Coordinated control and Truck priority. Case study The two DTM measures have been translated into 5 simulation scenarios for testing in a VISSIM environment. The selected case study is the ring road of Almere; this is a urban string or 14 controlled intersections. The 5 DTM scenarios are compared with a Reference Situation for which no special DTM measures are implemented. The 5 DTM scenarios are: • Coordinated Control, in the main directions all intersection controllers interchange information • on approaching vehicle platoons. • Truck Priority, in the main directions all intersection controllers detect trucks at long distances • in order guarantee a delay less intersection crossing • Truck Advantage, in the main directions green times are extended when a truck is detected • within the detection field at distance from the intersection. • Coordinated control with Truck priority, a combination. • Coordinated control with Truck advantage, a combination. Considering the driving profile characteristics from Personal Cars (PC) and Heavy Duty Vehicles (HDV) that were recorded from the simulations, the coordinated control with truck priority alternative shows the best improvements w.r.t. the reference situation. Although mainly the driving profiles of traffic on the ring road (main directions) improve, also the entire network performance increases. However, maximum stopped delay times on the side roads frequently exceed the 90 second limit. In general, a DTM measure is able reduce vehicle emission rates. The question to what extend can not be answered accurately based on the used calculation and simulation models." @default.
• W175367462 created "2016-06-24" @default.
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• W175367462 date "2007-04-05" @default.
• W175367462 modified "2023-09-26" @default.
• W175367462 title "Cruising towards better air quality: The influence of Dynamic Traffic Management on vehicle emissions through driving profile improvements" @default.
• W175367462 hasPublicationYear "2007" @default.
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