1. The study examines the effects of reducing speed limits from 50 km/h to 30 km/h in a residential area of Antwerp, Belgium and implementing coordinated traffic signals along a major road using microscopic traffic simulation and an emissions model.
2. Reducing speed limits in the residential area was found to reduce CO2 and NOx emissions by about 25%. Implementing coordinated traffic signals was found to reduce emissions by about 10%.
3. The integrated model combines microscopic traffic simulation to model vehicle behavior with an emissions model to estimate pollutants based on vehicle speeds and accelerations from the simulation. This allows assessment of traffic management measures on local air pollution.
This study used micro-simulation traffic modeling (Paramics) coupled with an emissions prediction model (Versit+) to examine the impact of two traffic management schemes on vehicle emissions in Antwerp, Belgium. Reducing the network speed limit was found to decrease CO2 emissions by 23-41% and NOx and PM by 27-45%, while removing green wave traffic signal coordination increased emissions by around 10%. The models provided an effective way to evaluate potential traffic and air quality impacts of management strategies at a network level.
This document summarizes a study that developed a model to assess the combined impacts of road traffic on noise and air pollution. The model combines microscopic traffic simulation with emission models for noise and air pollutants. The model was applied to a case study area in Belgium. Three scenarios were examined: the current situation with synchronized traffic lights, an unsynchronized light scenario, and a reduced speed limit scenario with synchronized lights. The results allow investigation of how traffic management measures influence emissions and provide guidance for urban planning.
Quantitative Analysis of Pollutant Emissions in the Context of Demand Respons...Beniamino Murgante
Quantitative Analysis of Pollutant Emissions in the Context of Demand Responsive Transport
Julie Prud'homme, Didier Josselin, Jagannath Aryal - University of Avignon
At the 2014 annual Dispersion Modellers user group meeting guest speaker James Tate spoke the topic: 'Making better use of microsimulation models for estimating vehicle emissions'
At the 2014 annual Dispersion Modellers user group meeting guest speaker Sean Beevers spoke on the topic: 'Update on progress with the development of a hybrid personal exposure model'
At the 2014 annual Dispersion Modellers user group meeting guest speaker Christine McHugh spoke on the topic: 'Comparison of Air Quality in World Cities'
This study used micro-simulation traffic modeling (Paramics) coupled with an emissions prediction model (Versit+) to examine the impact of two traffic management schemes on vehicle emissions in Antwerp, Belgium. Reducing the network speed limit was found to decrease CO2 emissions by 23-41% and NOx and PM by 27-45%, while removing green wave traffic signal coordination increased emissions by around 10%. The models provided an effective way to evaluate potential traffic and air quality impacts of management strategies at a network level.
This document summarizes a study that developed a model to assess the combined impacts of road traffic on noise and air pollution. The model combines microscopic traffic simulation with emission models for noise and air pollutants. The model was applied to a case study area in Belgium. Three scenarios were examined: the current situation with synchronized traffic lights, an unsynchronized light scenario, and a reduced speed limit scenario with synchronized lights. The results allow investigation of how traffic management measures influence emissions and provide guidance for urban planning.
Quantitative Analysis of Pollutant Emissions in the Context of Demand Respons...Beniamino Murgante
Quantitative Analysis of Pollutant Emissions in the Context of Demand Responsive Transport
Julie Prud'homme, Didier Josselin, Jagannath Aryal - University of Avignon
At the 2014 annual Dispersion Modellers user group meeting guest speaker James Tate spoke the topic: 'Making better use of microsimulation models for estimating vehicle emissions'
At the 2014 annual Dispersion Modellers user group meeting guest speaker Sean Beevers spoke on the topic: 'Update on progress with the development of a hybrid personal exposure model'
At the 2014 annual Dispersion Modellers user group meeting guest speaker Christine McHugh spoke on the topic: 'Comparison of Air Quality in World Cities'
This document summarizes research on integrating traffic and emission models to simulate the impacts of traffic on emissions. It describes:
1) Developing an approach to combine traffic simulation and emission models in a distributed way.
2) Proposing a method to calibrate microscopic emission models using aggregate emission measures.
3) Applying the integrated models to evaluate how different traffic demands and signal controls impact emissions.
This document discusses route choice theories taught in a winter 2006 transportation engineering course. It covers user equilibrium, where all used routes have equal travel times, and system optimization, which minimizes total travel time. An example problem compares the two approaches for two routes between a city and suburb. Under user equilibrium, travel times are 12.4 minutes on both routes and total delay is 55,800 vehicle-minutes. Under system optimization, travel times are 14.3 and 10.08 minutes and total delay is reduced to 53,592 vehicle-minutes.
Presentation by Dr James Tate at Institute of Air Quality Management (IAQM) Dispersion Modellers User Group December 2014.
www.its.leeds.ac.uk/people/j.tate
http://iaqm.co.uk/event/dmug-2014/
The ERMES Group coordinates research on mobile emission sources in Europe. It brings together transport emission modellers, researchers, funding agencies, and industry representatives. ERMES aims to become a permanent network that coordinates research programs to improve transport emission inventories in Europe. Key activities include harmonizing emission measurement procedures, sharing emission data, overseeing leading vehicle emission models like COPERT and HBEFA, and prioritizing future research issues.
DYNAMIC TRAFFIC LIGHT CONTROL SCHEME FOR REDUCING CO2EMISSIONS EMPLOYING ETC ...ijmpict
With the increasing growth of vehicle numbers in the world, Global warming is becoming a serious issue. Vehicle CO2 emissions are considered to be one of the main sources of global warming. In order to reduce vehicles CO2 emissions, a dynamic traffic light control scheme is proposed. In the proposed scheme, we are the first to use Electronic Toll Collection (ETC) devices to obtain real time traffic flow information for a traffic control centre. By the proposed scheme, vehicles can pass through intersections with less waiting time and fewer numbers of stops. By smoothing vehicle travel, CO2 emissions can be reduced. Compared with fixed time control, the simulation results indicate that the proposed scheme has much better performance: vehicle average waiting time is greatly reduced and CO2 emissions can also be
reduced.
Exhaust System Muffler Volume Optimization of Light Commercial passenger Car ...Barhm Mohamad
Nowadays, the automotive industry is focused on weight and size reduction. Main advantage of this weight and size reduction are improving the fuel economy. The specific fuel consumption of a vehicle can be improved through e.g. downsizing area of heat loss, if we focus on vehicle with weight reduction. Weight reduction can be done by replacing material or by changing the size (dimensions) of components. In the present work we have focused on Audi A6 muffler, troubleshooting and optimizing the muffler by changing pipe length of inlet and outlet, also by replacing the original mesh plate to porous pipe. Based on optimization, prototype has been built with the help of 3D design tool CATIA V5 and the calculations of transmission loss (TL) have been performed by MATLAB. Plane wave-based models such as the transfer matrix method (TMM) can offer fast initial prototype solutions for muffler designers. The principles of TMM for predicting the transmission loss of a muffler was used. Result of this present study of an existing muffler has been analysed and then compared with vehicle level test observation data. Noise level have been optimized for new muffler design. Other literatures were played significant rule for validate our results.
The study found that tramway systems have a lower carbon footprint over their 30-year lifetimes compared to all types of bus rapid transit (BRT) systems. While BRTs have some initial construction and manufacturing advantages, tramways produce significantly less greenhouse gas emissions during the operation and maintenance phase due to their improved energy efficiency. Even when accounting for variations in electricity sources, the tramway systems studied still emitted less carbon over their lifecycles. An optimized tramway system called Attractis developed by Alstom performed best of all, cutting construction phase emissions by over 20% compared to standard tramway systems.
This document summarizes a study that monitored traffic levels of service on urban highways by evaluating noise levels. The study developed an acoustic sensing model to monitor traffic flow by measuring roadside noise levels, rather than using traditional traffic counting methods. Noise measurements were taken simultaneously with traffic parameters like volume and speed. Statistical regression analysis showed strong correlations between noise levels and traffic density or level of service. The noise measurement technique allows for continuous monitoring of traffic conditions and variations in level of service over time.
Chapter 6 Fundamentals of traffic flowFayaz Rashid
The document discusses fundamental principles of traffic flow, including the primary elements of traffic flow such as flow, density, speed, and headway. It describes flow-density relationships and the fundamental diagram of traffic flow. Mathematical models for describing macroscopic traffic flow relationships are presented, including the Greenshields model relating traffic density to speed. The primary elements, flow-density relationships, and Greenshields traffic flow model are summarized for understanding traffic flow characteristics.
GreenSwirl: Combining Traffic Signal Control and Route Guidance for Reducing ...Naoki Shibata
Jiaxing Xu, Weihua Sun, Naoki Shibata and Minoru Ito : "GreenSwirl: Combining Traffic Signal Control and Route Guidance for Reducing Traffic Congestion," in Proc. of IEEE Vehicular Networking Conference 2014 (IEEE VNC 2014), pp. 179-186.
Serious traffic congestion is a major social problem in large cities. Inefficient setting of traffic signal cycles, especially, is one of the main causes of congestion. GreenWave is a method for controlling traffic signals which allows one-way traffic to pass through a series of intersections without being stopped by a red light. GreenWave was tested in several cities around the world, but the results were not satisfactory. Two of the problems with GreenWave are that it still stops the crossing traffic, and it forms congestion in the traffic turning into or out of the crossing streets. To solve these problems, we propose a method of controlling traffic signals, GreenSwirl, in combination with a route guidance method, GreenDrive. GreenSwirl controls traffic signals to enable a smooth flow of traffic through signals times to turn green in succession and through non-stop circular routes through the city. The GreenWave technology is extended thereby. We also use navigation systems to optimize the overall control of the city's traffic. We did a simulation using the traffic simulator SUMO and the road network of Manhattan Island in New York. We confirmed that our method shortens the average travel time by 10%-60%, even when not all cars on the road are equipped to use this system.
Seig seminar 2014 - A Smarter Way to Lower Emissions - Kenny BissettSTEP_scotland
Fife Council's air quality strategy involves managing local traffic to improve air quality in two areas. Monitoring found exceedances of NO2 and PM10 standards in Cupar's Bonnygate and Dunfermline's Appin Crescent due to traffic. Action plans for these areas focus on traffic management measures like queue relocation in Bonnygate and lane markings in Appin Crescent, which modeling shows can reduce pollutant levels. The council also partners with organizations and engages communities to integrate air quality into policies and strategies.
This document summarizes different techniques for assigning routes in transportation network modeling. It describes the all-or-nothing assignment method, direction curve method, capacity restraint assignment techniques, and multi-route assignment technique. For each method, it provides details on the approach, limitations, and examples of models that use the technique. The document is presented by five students as part of their course on urban transportation systems.
Transportation Planning & Travel Demand Forecasting (Transportation Engineering)Hossam Shafiq I
This document provides an overview of transportation planning and travel demand forecasting. It discusses long-term and short-term transportation planning, including examples. It also explains the four-step travel demand forecasting process of trip generation, trip distribution, mode split, and trip assignment. Key models used include Poisson models for trip generation, gravity models for trip distribution, and logit models for mode split.
ETC ASSISTED TRAFFIC LIGHT CONTROL SCHEME FOR REDUCING VEHICLES’ CO2 EMISSIONSIJMIT JOURNAL
This paper presents a vehicle’s CO2 emission reduction scheme by an ETC-assisted real-time traffic light
control scheme in vehicular networks. Using Electronic Toll Collection (ETC) devices, real-time road
conditions can be obtained by wireless communication between the ETC devices and the traffic lights. A
decision tree classification algorithm is used to assign the changing policy for the traffic lights, and then
the optimal average waiting time can be calculated. Less waiting time will result in less fuel consumption
and fewer CO2 emissions. Compared with the most widely used fixed time control, the ETC-assisted real-
time traffic light control scheme has much better performances in reducing the average waiting time,
improving non-stop passing rate, and reducing CO2 emission.
10 Capacity and LOS Analysis for Freeway (Traffic Engineering هندسة المرور & ...Hossam Shafiq I
This document discusses capacity and level of service analysis for freeways. It covers topics such as capacity under ideal conditions, measures of effectiveness, levels of service criteria, operational analysis including calculating speed and level of service, and planning and design analysis including calculating service flow rates, service volumes, and number of lanes needed. Examples are provided for calculating free-flow speed, passenger car equivalents, operational analysis, service flow rates and volumes, and design analysis. Homework problems are also assigned from Chapter 14.
The document discusses modal split and trip distribution models in transportation planning. It describes the factors that influence mode choice such as trip characteristics, transportation facilities, and traveler attributes. Two main types of modal split models are discussed: trip-end models which are sensitive to short-term changes, and trip-interchange models which can incorporate long-term policy decisions. Trip distribution is the second stage of travel demand modeling and involves distributing trips from origins to destinations using methods like the growth factor model and gravity model.
This document provides an overview of using Highway Capacity Software (HCS) 2010 to analyze signalized intersections. HCS 2010 implements procedures from the Highway Capacity Manual to evaluate traffic conditions, roadway characteristics, signal phasing and timing, and determine levels of service. The analysis involves inputting data, adjusting volumes, computing capacities and delays, and optimizing signal timing to minimize delays. The tutorial demonstrates completing inputs, running analyses, and interpreting output reports to evaluate intersection performance.
This document summarizes 13 proposed public transport measures in Lviv, Ukraine. It provides details on the type of transport (tramway or trolleybus), length, expected traffic volumes, estimated costs and benefits for each measure. Key information included are traffic performance increases expected to range from 1 to 33 million passenger-km per year, cost estimates ranging from 4.5 to 261 million UAH, and estimated CO2 emission reductions. The proposed measures aim to expand and improve the tramway and trolleybus networks in Lviv according to an optimistic development scenario for 2030.
Accessibility Analysis and Modeling in Public Transport Networks - A Raster b...Beniamino Murgante
The document summarizes research on modeling accessibility in public transportation networks using a raster-based approach. The research aimed to create an accessibility indicator for jobs via public transit that had low data requirements to allow transfer to other regions. The study area was the capital region of Denmark. Accessibility was modeled using land use, transportation, and temporal components. The model calculated cost distances from population and job centers using rasterized transportation network data. Results showed variability in accessibility scores and generally aligned with commuting statistics. The raster approach allowed fast calculation with low data needs but did not fully account for travel time or mode changes.
This document discusses applications of headway models in traffic analysis. Headway data was collected for traffic flows ranging from 170 to 750 vehicles per hour on a two-lane roadway. The hyperlang model and shifted negative exponential model were fitted to the observed headway distributions. The composite exponential model provided a good fit for flows from 170-750 vph. The shifted negative exponential model fit lower flows where most vehicles were free-moving. The parameters of the composite exponential model trended with traffic flow, allowing estimation of parameters for unmonitored flows. Applications demonstrated include justifying pedestrian crossing needs, predicting vehicle arrival patterns, testing flow randomness, and timing traffic signals.
The document discusses two traffic management schemes investigated using Paramics, a traffic simulation model, and VERSIT+, an emissions model. The first scheme reduced speed limits throughout the network, which decreased emissions, especially on freeways where emissions are lower at 70 km/h than 100 km/h. The second scheme examined the impact of a "green wave" traffic light synchronization along a major road, finding it reduced emissions by about 10% by limiting unnecessary acceleration at intersections.
This document proposes integrating a macroscopic traffic flow model (METANET) with a microscopic dynamic emission and fuel consumption model (VT-Micro) to enable model-based dynamic traffic control. The control aims to reduce emissions, fuel consumption, and travel time using dynamic speed limit control. Simulation results indicate this approach can balance the conflicting objectives of reducing environmental impacts while improving traffic flow.
This document summarizes research on integrating traffic and emission models to simulate the impacts of traffic on emissions. It describes:
1) Developing an approach to combine traffic simulation and emission models in a distributed way.
2) Proposing a method to calibrate microscopic emission models using aggregate emission measures.
3) Applying the integrated models to evaluate how different traffic demands and signal controls impact emissions.
This document discusses route choice theories taught in a winter 2006 transportation engineering course. It covers user equilibrium, where all used routes have equal travel times, and system optimization, which minimizes total travel time. An example problem compares the two approaches for two routes between a city and suburb. Under user equilibrium, travel times are 12.4 minutes on both routes and total delay is 55,800 vehicle-minutes. Under system optimization, travel times are 14.3 and 10.08 minutes and total delay is reduced to 53,592 vehicle-minutes.
Presentation by Dr James Tate at Institute of Air Quality Management (IAQM) Dispersion Modellers User Group December 2014.
www.its.leeds.ac.uk/people/j.tate
http://iaqm.co.uk/event/dmug-2014/
The ERMES Group coordinates research on mobile emission sources in Europe. It brings together transport emission modellers, researchers, funding agencies, and industry representatives. ERMES aims to become a permanent network that coordinates research programs to improve transport emission inventories in Europe. Key activities include harmonizing emission measurement procedures, sharing emission data, overseeing leading vehicle emission models like COPERT and HBEFA, and prioritizing future research issues.
DYNAMIC TRAFFIC LIGHT CONTROL SCHEME FOR REDUCING CO2EMISSIONS EMPLOYING ETC ...ijmpict
With the increasing growth of vehicle numbers in the world, Global warming is becoming a serious issue. Vehicle CO2 emissions are considered to be one of the main sources of global warming. In order to reduce vehicles CO2 emissions, a dynamic traffic light control scheme is proposed. In the proposed scheme, we are the first to use Electronic Toll Collection (ETC) devices to obtain real time traffic flow information for a traffic control centre. By the proposed scheme, vehicles can pass through intersections with less waiting time and fewer numbers of stops. By smoothing vehicle travel, CO2 emissions can be reduced. Compared with fixed time control, the simulation results indicate that the proposed scheme has much better performance: vehicle average waiting time is greatly reduced and CO2 emissions can also be
reduced.
Exhaust System Muffler Volume Optimization of Light Commercial passenger Car ...Barhm Mohamad
Nowadays, the automotive industry is focused on weight and size reduction. Main advantage of this weight and size reduction are improving the fuel economy. The specific fuel consumption of a vehicle can be improved through e.g. downsizing area of heat loss, if we focus on vehicle with weight reduction. Weight reduction can be done by replacing material or by changing the size (dimensions) of components. In the present work we have focused on Audi A6 muffler, troubleshooting and optimizing the muffler by changing pipe length of inlet and outlet, also by replacing the original mesh plate to porous pipe. Based on optimization, prototype has been built with the help of 3D design tool CATIA V5 and the calculations of transmission loss (TL) have been performed by MATLAB. Plane wave-based models such as the transfer matrix method (TMM) can offer fast initial prototype solutions for muffler designers. The principles of TMM for predicting the transmission loss of a muffler was used. Result of this present study of an existing muffler has been analysed and then compared with vehicle level test observation data. Noise level have been optimized for new muffler design. Other literatures were played significant rule for validate our results.
The study found that tramway systems have a lower carbon footprint over their 30-year lifetimes compared to all types of bus rapid transit (BRT) systems. While BRTs have some initial construction and manufacturing advantages, tramways produce significantly less greenhouse gas emissions during the operation and maintenance phase due to their improved energy efficiency. Even when accounting for variations in electricity sources, the tramway systems studied still emitted less carbon over their lifecycles. An optimized tramway system called Attractis developed by Alstom performed best of all, cutting construction phase emissions by over 20% compared to standard tramway systems.
This document summarizes a study that monitored traffic levels of service on urban highways by evaluating noise levels. The study developed an acoustic sensing model to monitor traffic flow by measuring roadside noise levels, rather than using traditional traffic counting methods. Noise measurements were taken simultaneously with traffic parameters like volume and speed. Statistical regression analysis showed strong correlations between noise levels and traffic density or level of service. The noise measurement technique allows for continuous monitoring of traffic conditions and variations in level of service over time.
Chapter 6 Fundamentals of traffic flowFayaz Rashid
The document discusses fundamental principles of traffic flow, including the primary elements of traffic flow such as flow, density, speed, and headway. It describes flow-density relationships and the fundamental diagram of traffic flow. Mathematical models for describing macroscopic traffic flow relationships are presented, including the Greenshields model relating traffic density to speed. The primary elements, flow-density relationships, and Greenshields traffic flow model are summarized for understanding traffic flow characteristics.
GreenSwirl: Combining Traffic Signal Control and Route Guidance for Reducing ...Naoki Shibata
Jiaxing Xu, Weihua Sun, Naoki Shibata and Minoru Ito : "GreenSwirl: Combining Traffic Signal Control and Route Guidance for Reducing Traffic Congestion," in Proc. of IEEE Vehicular Networking Conference 2014 (IEEE VNC 2014), pp. 179-186.
Serious traffic congestion is a major social problem in large cities. Inefficient setting of traffic signal cycles, especially, is one of the main causes of congestion. GreenWave is a method for controlling traffic signals which allows one-way traffic to pass through a series of intersections without being stopped by a red light. GreenWave was tested in several cities around the world, but the results were not satisfactory. Two of the problems with GreenWave are that it still stops the crossing traffic, and it forms congestion in the traffic turning into or out of the crossing streets. To solve these problems, we propose a method of controlling traffic signals, GreenSwirl, in combination with a route guidance method, GreenDrive. GreenSwirl controls traffic signals to enable a smooth flow of traffic through signals times to turn green in succession and through non-stop circular routes through the city. The GreenWave technology is extended thereby. We also use navigation systems to optimize the overall control of the city's traffic. We did a simulation using the traffic simulator SUMO and the road network of Manhattan Island in New York. We confirmed that our method shortens the average travel time by 10%-60%, even when not all cars on the road are equipped to use this system.
Seig seminar 2014 - A Smarter Way to Lower Emissions - Kenny BissettSTEP_scotland
Fife Council's air quality strategy involves managing local traffic to improve air quality in two areas. Monitoring found exceedances of NO2 and PM10 standards in Cupar's Bonnygate and Dunfermline's Appin Crescent due to traffic. Action plans for these areas focus on traffic management measures like queue relocation in Bonnygate and lane markings in Appin Crescent, which modeling shows can reduce pollutant levels. The council also partners with organizations and engages communities to integrate air quality into policies and strategies.
This document summarizes different techniques for assigning routes in transportation network modeling. It describes the all-or-nothing assignment method, direction curve method, capacity restraint assignment techniques, and multi-route assignment technique. For each method, it provides details on the approach, limitations, and examples of models that use the technique. The document is presented by five students as part of their course on urban transportation systems.
Transportation Planning & Travel Demand Forecasting (Transportation Engineering)Hossam Shafiq I
This document provides an overview of transportation planning and travel demand forecasting. It discusses long-term and short-term transportation planning, including examples. It also explains the four-step travel demand forecasting process of trip generation, trip distribution, mode split, and trip assignment. Key models used include Poisson models for trip generation, gravity models for trip distribution, and logit models for mode split.
ETC ASSISTED TRAFFIC LIGHT CONTROL SCHEME FOR REDUCING VEHICLES’ CO2 EMISSIONSIJMIT JOURNAL
This paper presents a vehicle’s CO2 emission reduction scheme by an ETC-assisted real-time traffic light
control scheme in vehicular networks. Using Electronic Toll Collection (ETC) devices, real-time road
conditions can be obtained by wireless communication between the ETC devices and the traffic lights. A
decision tree classification algorithm is used to assign the changing policy for the traffic lights, and then
the optimal average waiting time can be calculated. Less waiting time will result in less fuel consumption
and fewer CO2 emissions. Compared with the most widely used fixed time control, the ETC-assisted real-
time traffic light control scheme has much better performances in reducing the average waiting time,
improving non-stop passing rate, and reducing CO2 emission.
10 Capacity and LOS Analysis for Freeway (Traffic Engineering هندسة المرور & ...Hossam Shafiq I
This document discusses capacity and level of service analysis for freeways. It covers topics such as capacity under ideal conditions, measures of effectiveness, levels of service criteria, operational analysis including calculating speed and level of service, and planning and design analysis including calculating service flow rates, service volumes, and number of lanes needed. Examples are provided for calculating free-flow speed, passenger car equivalents, operational analysis, service flow rates and volumes, and design analysis. Homework problems are also assigned from Chapter 14.
The document discusses modal split and trip distribution models in transportation planning. It describes the factors that influence mode choice such as trip characteristics, transportation facilities, and traveler attributes. Two main types of modal split models are discussed: trip-end models which are sensitive to short-term changes, and trip-interchange models which can incorporate long-term policy decisions. Trip distribution is the second stage of travel demand modeling and involves distributing trips from origins to destinations using methods like the growth factor model and gravity model.
This document provides an overview of using Highway Capacity Software (HCS) 2010 to analyze signalized intersections. HCS 2010 implements procedures from the Highway Capacity Manual to evaluate traffic conditions, roadway characteristics, signal phasing and timing, and determine levels of service. The analysis involves inputting data, adjusting volumes, computing capacities and delays, and optimizing signal timing to minimize delays. The tutorial demonstrates completing inputs, running analyses, and interpreting output reports to evaluate intersection performance.
This document summarizes 13 proposed public transport measures in Lviv, Ukraine. It provides details on the type of transport (tramway or trolleybus), length, expected traffic volumes, estimated costs and benefits for each measure. Key information included are traffic performance increases expected to range from 1 to 33 million passenger-km per year, cost estimates ranging from 4.5 to 261 million UAH, and estimated CO2 emission reductions. The proposed measures aim to expand and improve the tramway and trolleybus networks in Lviv according to an optimistic development scenario for 2030.
Accessibility Analysis and Modeling in Public Transport Networks - A Raster b...Beniamino Murgante
The document summarizes research on modeling accessibility in public transportation networks using a raster-based approach. The research aimed to create an accessibility indicator for jobs via public transit that had low data requirements to allow transfer to other regions. The study area was the capital region of Denmark. Accessibility was modeled using land use, transportation, and temporal components. The model calculated cost distances from population and job centers using rasterized transportation network data. Results showed variability in accessibility scores and generally aligned with commuting statistics. The raster approach allowed fast calculation with low data needs but did not fully account for travel time or mode changes.
This document discusses applications of headway models in traffic analysis. Headway data was collected for traffic flows ranging from 170 to 750 vehicles per hour on a two-lane roadway. The hyperlang model and shifted negative exponential model were fitted to the observed headway distributions. The composite exponential model provided a good fit for flows from 170-750 vph. The shifted negative exponential model fit lower flows where most vehicles were free-moving. The parameters of the composite exponential model trended with traffic flow, allowing estimation of parameters for unmonitored flows. Applications demonstrated include justifying pedestrian crossing needs, predicting vehicle arrival patterns, testing flow randomness, and timing traffic signals.
The document discusses two traffic management schemes investigated using Paramics, a traffic simulation model, and VERSIT+, an emissions model. The first scheme reduced speed limits throughout the network, which decreased emissions, especially on freeways where emissions are lower at 70 km/h than 100 km/h. The second scheme examined the impact of a "green wave" traffic light synchronization along a major road, finding it reduced emissions by about 10% by limiting unnecessary acceleration at intersections.
This document proposes integrating a macroscopic traffic flow model (METANET) with a microscopic dynamic emission and fuel consumption model (VT-Micro) to enable model-based dynamic traffic control. The control aims to reduce emissions, fuel consumption, and travel time using dynamic speed limit control. Simulation results indicate this approach can balance the conflicting objectives of reducing environmental impacts while improving traffic flow.
A Dynamic Vehicular Traffic Control Using Ant Colony And Traffic Light Optimi...Kristen Carter
This document proposes a dynamic vehicular traffic control system using ant colony optimization and optimized traffic lights. It aims to reduce traffic congestion in urban areas. The system divides the road network into cells and uses artificial ants to guide vehicles along the least congested paths within each cell. It also proposes a new method for optimizing traffic light timing at intersections based on real-time vehicle count data collected from vehicles and traffic lights using VANET technology. Simulation results using the DIVERT simulator show that the proposed traffic light optimization method improves average vehicle speed and reduces waiting times and stopped vehicles at intersections compared to a system with usual fixed-duration traffic lights.
This article describes a method for developing a high-resolution vehicular emission inventory by integrating an emission model with a traffic model. The method uses portable emissions monitoring system data to categorize vehicle driving conditions into discrete speed and vehicle-specific power bins. Average emission rates and time spent in each bin are used to calculate total trip emissions and emission factors under specific average link speeds. The model was validated and found to predict emissions within 20% of measured data. This approach allows integration of emission and traffic models to better evaluate traffic emission reduction measures.
Traffic flow measurement for smart traffic light system designTELKOMNIKA JOURNAL
Determining congestions on intersection roads can significantly improve the performance of a traffic light system. One of the everyday problems on our roads nowadays is the unbalanced traffic on different roads. The blind view of roads and the dependency on the conventional timer-based traffic light systems can cause unnecessary delays on some arterial roads on expense of offering a needless extra pass time on some other secondary minor roads. In this paper, a foreground extraction model has been built in MATLAB platform to measure the congestions on the different roads constructing an intersection. Results show a satisfactory performance in terms of accuracy in counting cars and in consequence reducing the wait time on some major roads. System was tested under different weather and lighting conditions, and results were adequately promising.
Light vehicle dynamics and NOx emissions on the motorway networkIES / IAQM
This document summarizes a presentation on light vehicle dynamics and NOx emissions on motorways. It discusses previous UK guidance on assigning speed bands and corresponding emissions. It then analyzes real-world vehicle dynamics and emissions data to develop a more accurate understanding of emissions in different speed ranges. Specifically, it finds higher emissions occur in certain speed ranges due to traffic dynamics and at higher speeds. This informs revisions to the UK's speed band structure and emissions estimates to better reflect real-world conditions.
The document discusses platoon dispersion of heterogeneous traffic on a corridor in Chennai, India. Data on platoon sizes and travel times was collected at distances of 200-1400m between intersections under fixed-time signal control. Platoon sizes decreased with distance due to differences in vehicle speeds and interactions. The average travel speed was 46km/hr. Robertson's platoon dispersion model with a smoothing factor of 0.878 provided the best fit to the data. Traffic composition and distances between six intersections on the study corridor are also presented.
Etc assisted traffic light control scheme for reducing vehicles co2 emissionsIJMIT JOURNAL
This paper presents a vehicle’s CO2 emission reduction scheme by an ETC-assisted real-time traffic light control scheme in vehicular networks. Using Electronic Toll Collection (ETC) devices, real-time road conditions can be obtained by wireless communication between the ETC devices and the traffic lights. A decision tree classification algorithm is used to assign the changing policy for the traffic lights, and then the optimal average waiting time can be calculated. Less waiting time will result in less fuel consumption and fewer CO2 emissions. Compared with the most widely used fixed time control, the ETC-assisted realtime traffic light control scheme has much better performances in reducing the average waiting time, improving non-stop passing rate, and reducing CO2 emission.
The Effects of Countdown Signals on Intersection Capacity drboon
This study presents the effects of countdown signals on the total start-up lost time of automobiles at signalized intersections based on the data collected at intersections in Bangkok, Thailand. This countdown signal is used to warn motorists in queue at the stop line during any red phase on when the green phase will be started. The data indicated that the countdown signals did not have any effects on the saturation headway of automobiles, but on the total start-up lost time. With the use of the countdown signals, the total start-up lost time was decreased from 4.3 seconds to 2.9 seconds, or was reduced by thirty-three percent. Therefore, the countdown signals may be used to increase the capacity of signalized intersections.
1.8 Joaquin decision support tool (C.Stroobants)Stevie Swenne
Presentation of Christophe Stroobants (Flanders Environment Agency) on 'Joaquin decision support tool' during the conference 'Environmental challenges & Climate change opportunities' organised by Flanders Environment Agency (VMM)
1) The document tracks changes over 20 years to the traffic service quality in downtown Fort Worth using the Two-Fluid model. It calibrates the model for 1990 and 2012 to compare the Two-Fluid parameters (Tm, n) over time.
2) Key network attributes like block length, number of lanes, and signal timing were also compared between 1990 and 2012. Changes to these attributes help explain changes to the Two-Fluid parameters.
3) The results show certain attributes like the fraction of one-way streets and signal density are major factors in determining traffic service quality as represented by the Two-Fluid parameters. Comparing the 1990 and 2012 calibrations indicates how the downtown network
The report summarizes a literature study conducted to identify suitable emission and noise models to estimate the impact of traffic management strategies. It evaluates several American and European models and determines that the Versit+ model is best suited as it can predict emissions for different pollutants, is based on a large validated database, and is commercially available and easy to use. Initial tests coupling Versit+ with a micro-traffic simulation model showed promising results in accurately estimating emissions under different traffic conditions.
Roadside barriers - Accounting for the effect of vehicle induced momentum and...IES / IAQM
The document discusses using computational fluid dynamics (CFD) modeling to assess the performance of different roadside barrier designs in improving air quality. It summarizes the CFD model setup, which included traffic pollution source terms and accounting for vehicle-induced turbulence and momentum. Various barrier designs were explored through automated optimization. Key results showed that taller barriers containing pollution performed best, with overhanging designs forcing flow upwards and vertical designs pushing pollution over the barrier but also upwards. Overall, CFD modeling predicted a 39% reduction in pollution concentrations with barriers.
Inaugural Professorial lecture by Simon Shepherd, Professor of Choice Modelling & Policy Design. Institute for Transport Studies, University of Leeds, 9th September 2014.
For audio recording see: www.its.leeds.ac.uk/about/events/inaugural-lectures2014
www.its.leeds.ac.uk/people/s.shepherd
www.its.leeds.ac.uk/research/themes/dynamicmodelling
A Robust Algorithm To Solve The Signal Setting Problem Considering Different ...Joshua Gorinson
This paper presents an algorithm to optimize traffic signal settings that considers the interaction between signal timing and traffic assignment. The algorithm iteratively updates signal timings based on fixed traffic flows, and then updates traffic flows based on the new signal timings, with the goal of minimizing total delay. Two different traffic assignment approaches are considered: user equilibrium assignment and a platoon simulation model. The proposed algorithm is compared to other optimization methods on a real traffic network, demonstrating its robustness in handling different assignment approaches.
Simulating the dispersion of traffic emissions at the microscaleIES / IAQM
The MAGIC project aims to develop integrated models to simulate urban air quality and energy consumption at microscales. It uses computational fluid dynamics (CFD) software and data assimilation to model pollutant dispersion from traffic emissions. Field, wind tunnel and laboratory experiments are used to validate the models. Exposure analyses show highly variable pollutant concentrations at microscales. Momentary peak exposures of seconds to minutes may impact total exposure, but their health effects are unclear. Ultra-fast measurements of nitrogen oxides show concentration spikes corresponding to vehicles. CFD simulations of a crossroads reproduce observed hotspots at junctions from queuing traffic. Tracking vehicle movements through simulations could help identify scenarios leading to acute exposures that need mitigation.
An IoT based Dynamic Traffic Signal ControlGauthamSK4
Used Kerner three-phase traffic theory to establishing an Intelligent Traffic System that will provide automatic management of traffic lights based on the concept of the Internet of Things which will resolve the traffic jam issues which will in turn reduce CO2 emissions and also the mobility metrics like the travel time.
This document presents a bottom-up methodology to estimate vehicle emissions in Beijing, China at the grid level. The methodology combines vehicle emission factors based on speed from the MOBILE5B-China model with vehicle activity data from a travel demand model. Applying this approach, total emissions of HC, CO and NOx in Beijing's urban area in 2005 were estimated to be 13.33×104, 100.02×104 and 7.55×104 tons respectively. The grid-based estimates provide a more accurate spatial distribution of emissions compared to typical macro-scale approaches used in China.
This document provides a review of optimal speed traffic models. It begins with introductions to traffic modeling approaches including microscopic and macroscopic models. Microscopic models describe individual vehicle dynamics while macroscopic models use aggregated quantities like density and flow. The optimal velocity model is then defined as a car-following model where vehicles accelerate/decelerate to match an optimal speed based on headway. Properties, applications, and limitations of the optimal velocity model are discussed. Research on extensions like the full velocity difference model is also summarized. The document concludes with recommendations for further studying simulation problems to improve understanding of jam formation and congestion dynamics.
The document reviews optimal speed car-following models. It discusses macroscopic and microscopic traffic models, with a focus on microscopic optimal speed models. The optimal speed model defines a desired speed that is a function of headway distance and helps model traffic flow situations. The document also proposes enhancements to the optimal speed model, including a weighting factor dependent on relative speed and spacing to improve braking reactivity. In conclusion, it evaluates optimal speed models and their ability to realistically model traffic dynamics while avoiding collisions.
Similar to 6. Assessment of impact of speed limit reduction and traffic signal (20)
This document summarizes studies on using urban traffic management to reduce noise pollution. Some key findings include:
- Speed humps can reduce noise by 1-2 dB(A) but also increase it by 2-3 dB(A) near the humps due to braking and acceleration.
- Reducing road widths can lower noise by 1-3 dB(A), especially combined with other measures.
- Intersections are typically penalized by 0-3 dB(A) in noise models due to stop-and-go traffic. Coordinating traffic lights or using roundabouts can reduce noise by 1-2 dB(A).
- Lowering speed limits from 50 to 30 km/h decreases
The document discusses sustainability and consumerism. It argues that modern economies are unsustainable because they treat non-renewable natural resources as income rather than capital. Consumerism has failed to provide fulfillment and instead harms the environment. Ultimately, curtailing consumption of ecologically destructive goods and cultivating non-material sources of happiness can help balance human and environmental well-being.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help boost feelings of calmness, happiness and focus.
This document provides emissions data from chassis dynamometer testing of five 2003-2005 model year heavy-duty trucks. Carbon dioxide (CO2) emissions were found to correlate well with dispersed axle power, with an R2 of 0.86. Nitrogen oxides (NOx) emissions did not correlate as well with power, with an R2 of only 0.53, due to increasingly complex engine emissions controls affecting the linear dependence of NOx on power. The average ratio of NOx to CO2 emissions for the 2003-2005 model year trucks was found to be 0.0051, agreeing reasonably well with estimated certification standards, and lower than the average ratio of 0.0141 found for 1994-2002 model year
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
This document presents a new technique called the Modified Deconvolution Technique (MDT) to reconstruct instantaneous heavy duty vehicle emissions from measured data. MDT models the emissions analyzer system using a gamma probability density function to account for time dispersion effects. It uses fast Fourier transforms to divide the analyzer output signal by the impulse response function to estimate the original instantaneous emissions signal. The technique was tested on emissions data from a transit bus and showed improved correlation between reconstructed emissions and engine power compared to an earlier Differential Coefficients Method. The new technique provides a more accurate way to relate emissions to operating conditions like vehicle speed and acceleration.
The document discusses methods to improve the accuracy of reconstructing transient emissions measurements from heavy-duty vehicles. It examines using higher order derivatives and different numerical differentiation methods in the differential coefficients method. Using backward differences for numerical differentiation and including higher order derivatives improved the reconstruction accuracy by about 10% compared to just the first two derivatives. This margin of improved accuracy may be important for model accuracy or assessing emissions criteria compliance.
The sequential inversion technique (SIT) and differential coefficients method (DCM) are two methods discussed to reconstruct true transient emission signals from measurements taken by analyzers, which introduce delays and dispersion. The SIT reconstructs the input second by second based on the measured response and dispersion characteristics. Testing with real data showed it can accurately reconstruct signals without noise. However, reconstruction fails if the dispersion characteristics change or there is signal noise. The DCM defines the real input as a linear combination of the output and its derivatives. It was more accurate than SIT when noise was present. Both methods aim to compensate for measurement delays and dispersion to obtain instantaneous emissions from analyzer readings.
The document summarizes Thomas L. Friedman's book "Hot, Flat and Crowded" which discusses how the world is getting hotter, flatter, and more crowded due to increasing population and technology. This is resulting in a growing demand for energy, a transfer of wealth to oil-rich nations, climate change, energy poverty, and loss of biodiversity. The book proposes a "Code-Green" action plan to generate clean, cheap, and abundant energy through various scientific solutions.
This document summarizes Thomas Friedman's book "Hot, Flat, and Crowded" which addresses the major energy, climate, and environmental challenges facing the world. It diagnoses trends of increasing energy demand, climate change impacts, and a growing global population that is putting pressure on natural resources. The document outlines five key problems, and discusses how transitioning to renewable energy and reducing fossil fuel dependence can help address these issues and lift people out of energy poverty.
This document discusses rationality and making rational decisions. It argues that people often make irrational decisions due to errors in estimating the value and effort of seeking something and due to caring too much about social acceptance and what others think. Some key points made include that happiness is similar in most circumstances because people can synthesize happiness from friends, family, purpose and health. The document advocates making rational financial decisions based on accurate probability and value estimates rather than media influences, and embracing minimalism to maximize happiness from possessions.
Dr. Madhava runs Logic Academy, an educational institution located in Hyderabad, India. The academy offers intensive SAT, PSAT, and SAT Subject test preparation courses that are 3 months long and involve lectures, practice tests, and individual feedback sessions. Dr. Madhava employs effective learning tools like visual cues and simulation software to help students understand concepts and retain information. He has a PhD in Engineering from the USA and experience teaching Mathematics, Physics, and English.
6. Assessment of impact of speed limit reduction and traffic signal
1. Assessment of the impact of speed limit reduction and traffic signal
coordination on vehicle emissions using an integrated approach
Madhava Madireddy a,b
, Bert De Coensel a,⇑
, Arnaud Can a
, Bart Degraeuwe b
, Bart Beusen b
,
Ina De Vlieger b
, Dick Botteldooren a
a
Ghent University, Department of Information Technology, Acoustics Research Group, St.-Pietersnieuwstraat 41, B-9000 Ghent, Belgium
b
Flemish Institute for Technological Research, Boeretang 200, B-2400 Mol, Belgium
a r t i c l e i n f o
Keywords:
Microscopic traffic simulation
Road speed limits
Traffic light synchronization
Green wave traffic lights
a b s t r a c t
This paper examines the effects of two traffic management measures, speed limit reduction
and coordinated traffic lights, in an area of Antwerp, Belgium. An integrated model is
deployed that combines the microscopic traffic simulation model Paramics with the CO2
and NOX emission model VERSIT+. On the one hand, reductions in CO2 and NOX emissions
of about 25% were found if speed limits are lowered from 50 to 30 km/h in the residential
part of the case study area. On the other hand, reductions in the order of 10% can be
expected from the implementation of a green wave signal coordination scheme along an
urban arterial road.
Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction
The increased amount of road traffic in urban areas over the last few decades has meant that controlling congestion and
vehicle related emissions have become major challenges for city planners. Congestion increases travel times and idling, and
because of this, urban regions are facing increasing concentrations of local air pollutants. Related to this, there has also been
an increase in atmospheric carbon dioxide. A number of traffic management measures have been considered and some
implemented in cities, such as diverting traffic from peak hours to off-peak hours using congestion pricing, reducing speed
limits, coordinating traffic lights along major arterials, replacing signalized intersections with roundabouts, or even adding
additional lanes where expanding the road network is feasible.
It is widely accepted that if the number of acceleration and deceleration events associated with stop-and-go traffic is re-
duced, fuel efficiency increases and emissions are reduced. One action has been that optimized signal timing and coordinated
traffic lights are increasingly applied along major arterials, in order to smoothen traffic flow. Usually, systems are designed to
create green waves along arterial roads facing high demands. Alternatively, speed reductions, such as through the introduc-
tion of zones with a 30 km/h speed limit, are becoming popular for protecting residential areas, as they provide benefits in
terms of road safety, traffic diversion, as well as smoother flows and reduced emissions.
Because it is often not feasible to employ a trial-and-error method for assessing the environmental effects of traffic man-
agement measures, microscopic simulation models are increasingly employed for this purpose.1
Microscopic traffic models
consider the behavior of individual vehicles, which are modeled to follow empirically based rules for car following, lane chang-
ing and overtaking (Helbing, 2001). They allow to estimate the impact of detailed measures, because the influence of braking
and acceleration is taken into account. However, they require a large amount of detail in input data on road layout, signal tim-
1361-9209/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved.
doi:10.1016/j.trd.2011.06.001
⇑ Corresponding author. Tel.: +32 92649994; fax: +32 92649969.
E-mail address: bert.decoensel@intec.ugent.be (B. De Coensel).
1
De Coensel et al. (2007), for example, examined the case of noise emissions and Smit and McBroom (2009) air pollutants.
Transportation Research Part D 16 (2011) 504–508
Contents lists available at ScienceDirect
Transportation Research Part D
journal homepage: www.elsevier.com/locate/trd
2. ings, traffic counts, etc., and are therefore mainly useful to study traffic management measures within small to medium sized
areas, such as a part of a city. Computational models for estimating pollutant emissions that return realistic results for the stop-
and-go behavior of vehicles in urban environment have not been available until recently. Here we examine the potential envi-
ronmental impacts of traffic management measures in Antwerp using a microscopic traffic model in combination with a state-
of-the art air pollution model.
2. Methodology
2.1. The study area
The study area, ‘‘Zurenborg’’, is located in the southeastern part of the 19th century city belt of Antwerp, Belgium. Fig. 1
shows a map of the region. In the east, the area is bounded by the R1 freeway that has a speed limit of 100 km/h, and a major
road, the R10 or ‘‘Singel’’, with a speed limit of 70 km/h. In the southwest, the area is bounded by a railway track. In the
north, the area is bounded by a major arterial road, the N184 or ‘‘Plantin en Moretuslei’’, which connects the city of Antwerp
to the west side of the area with suburban areas in the east. This road has two lanes in each direction, and implements traffic
signal coordination. More in particular, during morning rush hour, all signals along this road operate at the same cycle time
(60–90 s intervals, depending on the presence of pedestrians or buses), and the temporal offset of the cycle of each intersec-
tion is set such that vehicles traveling from east to west encounter only green lights, when driving at the desired speed of
50 km/h. A similar traffic signal setting is applied in the reverse direction during the evening rush hour. Traffic intensity dur-
ing morning rush hour, from east to west, varies between 700 and 1000 vehicles/hour, depending on the segment that is
considered (vehicles also enter along the side streets). The triangular area within the eastern, southwestern and northern
borders is mainly residential, with an overall speed limit of 50 km/h.
2.2. Microscopic traffic simulation model
We use Quadstone Paramics, a commercially available microscopic traffic simulation tool, to simulate traffic conditions. A
network of the triangular case study area is constructed on the basis of geographic information system (GIS) data and aerial
photographs, which supply the detailed positions of all roads and buildings in the area. Network wide traffic demands are
calibrated for the morning rush-hour, based on traffic counts made available by the Flemish Department of Mobility and
Public Works. Traffic signal parameters (cycle times, signal offsets between intersections, etc.) were set according to the ac-
tual situation, based on data obtained from the Antwerp police department. Light- and heavy-duty vehicles are considered,
which were linked to the respective emission classes of the emission model. The railway passing through the area is not
modeled. The simulation period is 1 h, with a timestep of 0.5 s. Vehicles are loaded onto the network at the edge roads along
R10
R1
N184
Railway
0 100 200 300 400m
N
E
S
W
Note: The triangular area bounded by the R1, the N184 and the railway forms the outline
of the traffic simulation network. The circles along the N184 mark signalized
intersections with coordinated traffic lights.
Fig. 1. Study area of ‘‘Zurenborg’’ in Antwerp, Belgium.
M. Madireddy et al. / Transportation Research Part D 16 (2011) 504–508 505
3. the sides of the network, according to the traffic demand. During simulation, the position, speed and acceleration of each
vehicle is recorded at each timestep, for subsequent calculation of emissions.
Although the microscopic traffic model is able to take into account a wide range of vehicle driving behavior, a number of
factors that have an influence on vehicle speeds and accelerations cannot be fully embraced. Among those are the influence
of pedestrians crossing the street, cars slowing down to park or cars leaving a parking spot, or the full extent of the stochastic
component in driver’s behavior. Next to this, the traffic counts used to calibrate the model reflect the average situation dur-
ing morning rush hour. Therefore, traffic counts and speed distributions measured at a single instant in time within the sim-
ulated region could significantly differ from those that are simulated. Nevertheless, as only average trends are usually
considered, microscopic traffic simulation models are increasingly being applied for estimating the emissions from traffic
flows. Earlier work has shown that, for emission modeling purposes, a reasonably good agreement between simulated
and measured speeds and accelerations can be achieved (De Coensel et al., 2005).
2.3. Emission model
The instantaneous CO2 and NOX emission of each vehicle in the simulation is calculated using the VERSIT+ vehicle exhaust
emission model, based on the speeds and accelerations extracted from the traffic model. The latter model (Smit et al., 2007),
is based on more than 12,500 measurements on vehicles of a wide range of makes and models, fuel types, Euro class, fuel
injection technology, types of transmission, etc. It uses multivariate regression techniques to determine emission factors
for different vehicle classes. As the model requires actual driving pattern data as input, it is fully capable of accounting
for the effects of congestion on emission. A derived model was recently developed by TNO (Ligterink and De Lange,
2009), specifically targeted at a coupling with microscopic traffic simulation models. For this, emission parameters of vehi-
cles of varying age, fuel type, etc. are aggregated into a prototypical vehicle emission model representing the average emis-
sion of the Dutch vehicle fleet. While there may be differences between individual vehicles, the model aims at predicting
aggregates over a sufficiently large number of vehicles sampled from the Dutch vehicle fleet. Here the VERSIT+ light and hea-
vy-duty vehicle classes representing the fleet in Dutch urban environments during 2009 are used. Finally, only overall emis-
sions are considered; the dispersion of air pollutants is not modeled.
A small-scale validation of the dynamic properties of the emission model was carried out using VOEM, VITO’s on-road
emission and energy measurement system (De Vlieger, 1997). Measurements of instantaneous speed, acceleration, CO2
and NOX emissions were carried out using four diesel vehicles subjected to the MOL30 driving cycle, which is based on real
driving behavior in urban, suburban and freeway traffic situations. Subsequently, the emission model was used to estimate
the CO2 and NOX emissions based on measured speeds and accelerations. Finally, both measured and estimated emission
time series are compared. In general, a good dynamic agreement is found, with temporal correlation factors of
0.90 ± 0.030 for CO2 and 0.72 ± 0.10 for NOX for all test vehicles, indicating that the model is able to capture the dependencies
on speed and acceleration well. The somewhat lower correlations for NOX may be explained by the presence of an exhaust
gas recirculation system in some of the vehicles.2
2.4. Validation of the integrated model
The accuracy of the estimated emissions using the combination of traffic and emission models is examined using data
from a series of vehicle trips through the study area. A vehicle equipped with data logging devices was driven several times
along the N184 on a typical working day. Instantaneous speed, throttle position and fuel consumption were gathered
through the CAN-bus interface of the vehicle on a second-by-second basis, while the vehicle location was logged using a
GPS device. Trip data for all light duty vehicles driving along the N184 is extracted from the microsimulation model. In both
cases, only the part of the trip along the N184 is considered. Instantaneous emissions are calculated using the emission mod-
0.25
0.20
0.15
0.10
0.05
0.00
]dezilamron[noitcarF
NO [g/km]X
simulated trips
measured trips
0.25
0.20
0.15
0.10
0.05
0.00
40 1 2 3 5 6 7 80 250 500 750 1000 1250 1500
]dezilamron[noitcarF
CO [g/km]2
simulated trips
measured trips
Fig. 2. Normalized distributions of CO2 and NOX emissions per km, for measured and simulated vehicle trips along the N184.
2
Details of this validation can be found in Trachet et al. (2010).
506 M. Madireddy et al. / Transportation Research Part D 16 (2011) 504–508
4. el, for both measured and simulated vehicle trips (Fig. 2). In general, a good agreement is found between them, suggesting
that the accuracy of the integrated model is sufficient for estimating the effects of traffic management measures on
emissions.
3. Simulation results
3.1. Reduced speed limits
As a first traffic management measure, the effect of a speed limit reduction is studied. Based on measures being consid-
ered by the traffic planning authorities of the city of Antwerp, speed limits are reduced from 100 to 70 km/h on the freeway,
from 70 to 50 km/h on the Singel, and from 50 to 30 km/h on the other residential roads and the N184. For the latter, the
traffic signal coordination is recalibrated for the lower speed limit to have a green wave as in the original scenario. The
microscopic traffic simulation model applies dynamic traffic assignment: routes are chosen according to the instantaneous
congestion conditions. Traffic demands are kept constant.
The changes in the distribution of instantaneous speeds and accelerations for vehicles driving within the residential part
of the network (excluding the N184, R10 and R1) are seen in Fig. 3. Next to a reduction in average speeds, the speed distri-
bution becomes narrower, coupled with a reduction in the occurrence of maximum acceleration events. Hence, the speed
limit reduction results in a smoother traffic flow in the residential area. Maximum speeds are about 10% above the speed
limits because the traffic model also accounts for speeding to resemble the actual situation as closely as possible.
Fig. 4 shows the corresponding change in distribution of instantaneous distance-based emissions for the light duty vehi-
cles; the results for heavy-duty vehicles show a similar trend. The distance travelled by all vehicles within the residential
area fell by 14.1% because of traffic rerouting, but CO2 and NOX emissions fell by 26.8% and 26.7%. Consequently, a reduction
in distance-based emissions is also seen in Fig. 4. For the vehicles moving along the N184, similar results are found. Although
the distance travelled by all vehicles along the N184 only falls by 0.2%, still, a reduction in CO2 and NOX emissions by 9.9%
and 10.4% is recorded.
3.2. Effect of traffic light coordination
As a second traffic management measure, the effect of traffic signal coordination along the N184 is studied. The original
situation, with implementation of a green wave from east to west, is compared to a scenario in which coordination is re-
moved. To desynchronize the traffic signals, a small but random number of seconds (62) is added or subtracted from the
1.0
0.8
0.6
0.4
0.2
0.0
]dezilamron[noitcarF
Acceleration [m/s ]2
original scenario
reduced speed limits
0.5
0.4
0.3
0.2
0.1
0.0
-2 -1 0 1 20 10 20 30 40 50 60
]dezilamron[noitcarF
Speed [km/h]
original scenario
reduced speed limits
Fig. 3. Normalized distributions of instantaneous speed and acceleration, for vehicles driving within the residential part of the network.
1.0
0.8
0.6
0.4
0.2
0.0
]dezilamron[noitcarF
NO [g/km]X
original scenario
reduced speed limits
1.0
0.8
0.6
0.4
0.2
0.0
0.0 0.5 1.0 1.5 2.00 250 500 750 1000 1250 1500
]dezilamron[noitcarF
CO [g/km]2
original scenario
reduced speed limits
Fig. 4. Normalized distributions of CO2 and NOX emissions per km, for vehicles driving within the residential part of the network.
M. Madireddy et al. / Transportation Research Part D 16 (2011) 504–508 507
5. cycle times of all lights along the N184. This results in a wide range of waiting times and queue lengths at each intersection
being encountered over the course of the simulation run, with the results representing the average over all possible schemes
in which there is no signal coordination. Again, traffic demands were kept constant.
Fig. 5 shows the changes in the distribution of trip emissions for the light duty vehicles that drove along the N184, com-
pleting their trips during the simulation run; only that part of the trip along the N184 is considered. When the signal coor-
dination is removed, the combined light and heavy-duty vehicles CO2 and NOX emissions increase by 9.5% and 8.7% because
of the more interrupted traffic flow.
4. Conclusions
An integrated approach coupling a microscopic traffic simulation model with a state-of-the-art instantaneous air pollu-
tant emission model reaffirms the environmental benefits of reducing speed limits in residential areas. Reductions in CO2
and NOX emissions of the order of 25% were found if speed limits are lowered from 50 to 30 km/h in residential area, on
top of increased road safety that is expected from lower vehicle speeds. The study also finds that a reduction of the order
of 10% in CO2 and NOX emissions can be expected from the implementation of a green wave signal coordination scheme.
However, traffic signal coordination also decreases travel times, and the effect of facilitating traffic flow may, in the long
term, induce additional traffic with the potential side effect of offsetting some of the beneficial environmental consequences
of signal coordination.
Acknowledgements
The authors are grateful to the Flemish Department of Mobility and Public works for providing traffic counts, and to the
Antwerp police department for providing traffic light timings for the case study area. The authors would also like to thank
Stijn Vernaillen for gathering real-time speed profiles which were used to validate the traffic model. This study was per-
formed within the framework of Steunpunt Mobiliteit, which is supported by the Flemish Government. Bert De Coensel is
a postdoctoral fellow, and Arnaud Can is a visiting postdoctoral fellow of the Research Foundation–Flanders (FWO–Vlaand-
eren); the support of this organization is also gratefully acknowledged.
References
De Coensel, B., Botteldooren, D., Vanhove, F., Logghe, S., 2007. Microsimulation based corrections on the road traffic noise emission near intersections. Acta
Acust. Acust. 93, 241–252.
De Coensel, B., De Muer, T., Yperman, I., Botteldooren, D., 2005. The influence of traffic flow dynamics on urban soundscapes. Appl. Acoust. 66, 175–194.
De Vlieger, I., 1997. On-board emission and fuel consumption measurement campaign on petrol-driven passenger cars. Atmos. Environ. 31, 3753–3761.
Helbing, D., 2001. Traffic and related self-driven many-particle systems. Rev. Mod. Phys. 73, 1067–1141.
Ligterink, N.E., De Lange, R., 2009. Refined vehicle and driving-behaviour dependencies in the VERSIT+ emission model. In: Proceedings of the Joint 17th
Transport and Air Pollution Symposium and 3rd Environment and Transport Symposium, Toulouse.
Smit, R., McBroom, J., 2009. Use of microscopic simulation models to predict traffic emissions. Road Transport. Res. 18, 49–54.
Smit, R., Smokers, R., Rabé, E., 2007. A new modelling approach for road traffic emissions: VERSIT+. Transportation Research Part D 12, 414–422.
Trachet, B., Madireddy, M., Botteldooren, D., De Vlieger, I., 2010. The influence of traffic management on emissions: literature study of existing emission
models and initial tests with microscopic traffic simulation. Technical Report RA-MOW-2010-001. Flemish Policy Research Centre for Mobility & Public
Works, Brussels.
100
80
60
40
20
0
0.0 0.5 1.0 1.5 2.0 2.5
spirtforebmuN
NO [g]X
original scenario
without green wave
50
40
30
20
10
0
0 200 400 600 800 1000
spirtforebmuN
CO [g]2
original scenario
without green wave
Fig. 5. Distributions of CO2 and NOX emissions, for light duty vehicle trips along the N184.
508 M. Madireddy et al. / Transportation Research Part D 16 (2011) 504–508