A field evaluation case study of the environmental and energy impacts of traffic calming

This study quantifies the energy and environmental impact of a selection of traffic calming measures using a combination of second-by-second floating-car global positioning system data and microscopic energy and emission models. It finds that traffic calming may result in negative impacts on vehicle fuel consumption and emission rates if drivers exert aggressive acceleration levels to speed up to their journeys. Consequently by eliminating sharp acceleration maneuvers significant savings in vehicle fuel consumption and emission rates are achievable through driver education. The study also demonstrates that high emitting vehicles produce CO emissions that are up to 25 times higher than normal vehicle emission levels while low emitting vehicles produce emissions that are 15–35% of normal vehicles. The relative increases in vehicle fuel consumption and emission levels associated with the sample traffic calming measures are consistent and similar for normal, low, and high emitting vehicles.     

Simulating the environmental effects of isolated and area-wide traffic calming schemes using traffic simulation and microscopic emission modeling

This study focuses on the development of a microscopic traffic simulation and emission modeling system which aims at quantifying the effects of different types of traffic calming measures on vehicle emissions both at a link-level and at a network-level. It also investigates the effects of isolated traffic-calming measures at a corridor level and area-wide calming schemes, using a scenario analysis. Our study is set in Montreal, Canada where a traffic simulation model for a dense urban neighborhood is extended with capabilities for microscopic emission estimation. The results indicate that on average, isolated calming measures increase carbon dioxide (CO₂), carbon monoxide (CO), and nitrogen oxides (NO_x) emissions by 1.5, 0.3, and 1.5 %, respectively across the entire network. Area-wide schemes result in a percentage increase of 3.8 % for CO₂, 1.2 % for CO, and 2.2 % for NO_x across the entire network. Along specific corridors where traffic calming measures were simulated, increases in emissions of up to 83 % were observed. We also account for the effect of different measures on traffic volumes and observe moderate decreases in areas that have undergone traffic calming. In spite of traffic flow reductions, total emissions do increase.     

A model of speed profiles for traffic calmed roads

The influence of traffic calming measures on the speed of unimpeded vehicles has been investigated by evaluating differences in speed profiles obtained from various combinations of traffic calming measures. A case study has been conducted in the City of York (UK) focusing on traffic calming measures such as speed humps (flat-topped and round topped), speed cushions and chicanes implemented in sequence. Vehicles' passing times were simultaneously recorded at 16 points along each traffic calmed link. From these data a speed profile for each individual vehicle could be derived. An empirical model was developed using multiple regression analysis techniques based on data collected at three calibration sites. Speeds along these links were described as a function of the input speed, the type of measure and the distance between measures. The speed profile model was shown to be a good representation for the data from the calibration sites. It efficiently predicted speeds of unimpeded vehicles over a given combination of traffic calming measures in sequence. The validation process, based on data collected at three validation sites, also indicated that the model provided a good representation of the observed profiles at these sites, with the exception of the prediction of the effects of the chicanes on speeds. This type of measure was shown to produce diverse impacts on speeds which depended on the detailed design. While the model is a useful design tool, recommendations have been made for further enhancement to it.     

Simulating the air quality impacts of traffic calming schemes in a dense urban neighborhood

In this study, the effects of isolated traffic calming measures and area-wide calming schemes on air quality in a dense neighborhood were estimated using a combination of microscopic traffic simulation, emission, and dispersion modeling. Results indicated that traffic calming measures did not have as large an effect on nitrogen dioxide (NO₂) concentrations as the effect observed on nitrogen oxide (NO_x) emissions. Changes in emissions resulted in highly disproportional changes in pollutant levels due to daily meteorological conditions, road geometry and orientation with respect to the wind. Average NO₂ levels increased between 0.1% and 10% with respect to the base-case while changes in NO_x emissions varied between 5% and 160%. Moreover, higher wind speeds decreased NO₂ concentrations on both sides of the roadway. Among the traffic calming measures, speed bumps produced the highest increases in NO₂ levels.     

Exploration of correlation between environmental factors and mobility at signalized intersections

Characterizing the relationship between environmental factors and mobility is critical for developing a sustainable traffic signal control system. In this study, the authors investigate the correlation of the environmental impacts of transport and mobility measurements at signalized intersections. A metamodeling-based method involving experimental design, simulations, and regression analysis was developed. The simulations, involving microscopic traffic modeling and emission estimation with an emerging emission estimator, provide the flexibility of generating cases with various intersection types, vehicle types, and other parameters such as driver behavior, fuel types, and meteorological factors. A multivariate multiple linear regression (MMLR) analysis was applied to determine the relationship between environmental and mobility measurements. Given the limitations of using the built-in emissions modules within current traffic simulation and signal optimization tools, the metamodeling-based approach presented in this paper makes a methodological contribution. The findings of this study set up the base for extensive application of simulation optimization to sustainable traffic operations and management. Moreover, the comparison of outputs from an advanced estimator with those from the current tool recommend improving the emissions module for more accurate analysis (e.g., benefit-cost analysis) in practical signal retiming projects.     

Developing link-based particle number emission models for diesel transit buses using engine and vehicle parameters

To better assess health impacts from diesel transportation sources, particle number emissions can be modeled on a road network using traffic operating parameters. In this work, real-time particle number emissions rates from two diesel transit buses were aggregated to the roadway link-level and modeled using engine parameters and then vehicle parameters. Modern statistical methods were used to identify appropriate predictor variables in the presence of multicollinearity, and controlled for correlated emission measurements made on the same day and testing route. Factor analysis helped to reduce the number of potential engine parameters to engine load, engine speed, and exhaust temperature. These parameters were incorporated in a linear mixed model that was shown to explain the variation attributable to link-characteristics. Vehicle specific power and speed were identified as two surrogate vehicle travel variables that can be used in the absence of engine parameters, although with a loss in predictive power compared to the engine parameter model. If vehicle speed is the only operating input available, including road grades in the model can significantly improve particle number emission estimates even for links with mild grade. Although the data used are specific to the buses tested, the approach can be applied to modeling emissions from other vehicle models with different engine types, exhaust systems, and engine retrofit technologies.     

Environmental,functional and economic criteria for comparing “target roundabouts” with one- or two-level roundabout intersections

The article describes a criterion based on functional, environmental and economic aspects for comparing conventional roundabouts with innovative one- or two-level roundabouts. We compared the performances of eight roundabout types, differing in geometric layout, number of lanes and traffic flow regulation from each other, with regard to vehicle delays and CO₂, NO_x, PM_2.5 and PM₁₀ pollutant emissions. Recently-designed roundabouts – target roundabouts and flyover roundabouts – have also been studied for their undoubted practical interest. By means of closed-form capacity models and CORINAIR methodology, several traffic simulations were carried out to examine a typical annual traffic demand curve in a suburban context, three different distribution test matrices for traffic flows (ρ1, ρ2, ρ3) and maximum annual traffic flow values Q_max ranging between 1300 and 3300 veh/h.Estimating vehicle delays and annual pollutant emissions, along with construction and management costs, allowed obtaining overall costs for each roundabout examined, in function of traffic demand and several other parameters. Thanks to these analyses, we identified the roundabout types which best suit to each traffic condition.     

The impact of speed post-processing methods on regional mobile emissions estimation

Average roadway segment travel speeds play an important role in estimating stabilized running vehicle emissions. Currently stabilized, or hot, running emissions are computed based on speeds produced during the travel demand modeling process. Speed data from the travel forecasting models are widely recognized as being insufficiently accurate for air quality purposes. Frequently post-processing techniques are seen as the most cost-effective means of improving the accuracy of the speed estimates. Using the Sacramento Metropolitan area, this paper focuses on the impacts of different speed post-processors on regional peak period emissions inventories. The results indicated that most post-processed speeds produce consistently and significantly higher running emissions, particularly in locations with heavy traffic. The observed differences in emissions between different types of post-processed speeds vary with congestion level, pollutant type and the underlying approach encapsulated in the speed post-processor calculations. The Sacramento case study suggests that the post-processor used to develop speeds for the purposes of calculating on-road emissions inventories can significantly influence the emissions inventories.     

Network-wide traffic and environmental impacts of acceleration and deceleration among Eco-Driving Vehicles in different road configurations

Eco-Driving, a driver behaviour-based method, has featured in a number of national policy documents as part of CO₂ emission reduction or climate change strategies. This investigation comprises a detailed assessment of acceleration and deceleration in Eco-Driving Vehicles at different penetration levels in the vehicle fleet, under varying traffic composition and volume. The impacts of Eco-Driving on network-wide traffic and environmental performance at a number of speed-restricted road networks (30?km/h) is quantified using microsimulation. The results show that increasing levels of Eco-Driving in certain road networks result in significant environmental and traffic congestion detriments at the road network level in the presence of heavy traffic. Increases in CO₂ emissions of up to 18% were found. However, with the addition of vehicle-to-vehicle or vehicle-to-infrastructure communication technology which facilitates dynamic driving control on speed and acceleration/deceleration in vehicles, improvements in CO₂ emissions and traffic congestion are possible using Eco-Driving.     

Emission evaluation of inter-vehicle safety warning information systems

Driver inattentiveness is one of critical factors contributing to vehicle crashes. The inter-vehicle safety warning information system (ISWS) is a technology to enhance driver attentiveness by providing warning messages about upcoming hazards using connected vehicle environments. A novel feature of the proposed ISWS is its ability to detect hazardous driving events, such as abrupt accelerations and lane changes, which are defined as moving hazards with a higher potential of causing crashes. This study evaluated the effectiveness of the ISWS in reducing vehicle emissions and its potential for traffic congestion mitigation. This study included a field experiment that documented actual vehicle maneuvering patterns for abrupt accelerations and lane changes, which were used for more realistic simulation evaluations, in addition to normal accelerations and lane changes. Probe vehicles equipped with customized on-board units consisting of a global positioning system (GPS) device, accelerometer, and gyro sensor were used to obtain the vehicle maneuvering data. A microscopic simulator, VISSIM, was used to simulate a driver’s responsive behavior when warning messages were delivered. A motor vehicle emission simulator (MOVES) was then used to estimate vehicle emissions. The results show that reduction in vehicle emissions increased when the ISWS’s market penetration rate (MPR) and the congestion level of the traffic conditions increased. The maximum CO and CO₂ emission reductions achieved were approximately 6% and 7%, respectively, under LOS D traffic conditions. The outcomes of this study can be valuable for deriving smarter operational strategies for ISWS to account for environmental impacts.     

Evaluating unintended outcomes of regional smart-growth strategies: Environmental justice and public health concerns

Many urban areas are perusing infill, transit oriented, and other “smart-growth” strategies to address a range of important regional goals. Denser and more mixed use urban development may increase sustainability and improve public health by reducing vehicle travel and increasing the share of trips made by transit, walking and bicycling. Fewer vehicle trips results in fewer greenhouse gas and toxic vehicle emissions, and more trips made by walking and bicycle increases physical activity. Prior research has largely focused on modeling and estimating the potential size of these and other smart-growth strategy benefits. A largely overlooked area is the potential for unexpected public health costs and environmental justice concerns that may result from increasing density. We evaluate regional land-use and transportation planning scenarios developed for the year 2040 by a metropolitan planning organization with a newly developed regional air quality modeling framework. Our results find that a set of regional plans designed by the MPO to promote smart-growth that are estimated to result in less vehicle use and fewer vehicle emissions than a more typical set of plans results in higher population exposure to toxic vehicle emissions. The smart-growth plans also result in greater income-exposure inequality, raising environmental justice concerns. We conclude that a more spatially detailed regional scale air quality analysis can inform the creation of smarter smart-growth plans.     

Controlling vehicular emissions in Beijing during the last decade

The vehicle population of Beijing is sharply increasing at an average annual rate of 14.5%, causing severe transportation and environmental problems. The Beijing municipal government and the public have worked hard to control vehicular emissions since 1995. Strategies and measures have been introduced to regulate land use and traffic planning, emission control of in-use vehicles and new vehicles, fuel quality improvement, introduction of clean fuel vehicle technology and fiscal incentives. New development plans for Beijing will change the transportation structure by encouraging public transportation. For in-use vehicles, the I/M program has employed ASM tests since early 2003 and the government has encouraged the retirement of high-emission vehicles. For new vehicles, Beijing introduced Euro 1 and Euro 2 emission standards in early 1999 and 2003, respectively. It is also confirmed that Euro 3 standards will be introduced in 2005. At the same time, the fuel quality in Beijing was improved significantly, by banning lead and reducing sulfur among other changes. CNG and LPG were introduced in 1999 and are used in buses and taxis. Today Beijing has the largest CNG bus fleet in the world with more than 2000 dedicated CNG buses. Beijing has also focused on fiscal incentives such as tax deductions for new vehicles meeting enhanced emission standards to encourage their sales. These strategies and measures have had an impact on the control of vehicular emissions. Despite the rapid increase of the vehicle population by 60% between 1998 and 2003, total vehicular emissions have not increased. With the enhancement of vehicular emission control, the air quality in Beijing is improving as the city strives to its goal for a “Green Olympics”.     

Analysis of a cooperative variable speed limit system using microscopic traffic simulation

Variable speed limit systems where variable message signs are used to show speed limits adjusted to the prevailing road or traffic conditions are installed on motorways in many countries. The objectives of variable speed limit system installations are often to decrease the number of accidents and to increase traffic efficiency. Currently, there is an interest in exploring the potential of cooperative intelligent transport systems including communication between vehicles and/or vehicles and the infrastructure. In this paper, we study the potential benefits of introducing infrastructure to vehicle communication, autonomous vehicle control and individualized speed limits in variable speed limit systems. We do this by proposing a cooperative variable speed limit system as an extension of an existing variable speed limit system. In the proposed system, communication between the infrastructure and the vehicles is used to transmit variable speed limits to upstream vehicles before the variable message signs become visible to the drivers. The system is evaluated by the means of microscopic traffic simulation. Traffic efficiency and environmental effects are considered in the analysis. The results of the study show benefits of the infrastructure to vehicle communication, autonomous vehicle control and individualized speed limits for variable speed limit systems in the form of lower acceleration rates and thereby harmonized traffic flow and reduced exhaust emissions.     

Optimal vehicle speed trajectory on a signalized arterial with consideration of queue

Vehicle speed trajectory significantly impacts fuel consumption and greenhouse gas emissions, especially for trips on signalized arterials. Although a large amount of research has been conducted aiming at providing optimal speed advisory to drivers, impacts from queues at intersections are not considered. Ignoring the constraints induced by queues could result in suboptimal or infeasible solutions. In this study, a multi-stage optimal control formulation is proposed to obtain the optimal vehicle trajectory on signalized arterials, where both vehicle queue and traffic light status are considered. To facilitate the real-time update of the optimal speed trajectory, a constrained optimization model is proposed as an approximation approach, which can be solved much quicker. Numerical examples demonstrate the effectiveness of the proposed optimal control model and the solution efficiency of the proposed approach.     

香港典型山区道路汽车行驶工况污染物排放研究

通过安装车载测试系统收集香港港岛山区路段正常行驶工况下尾气中的CO、NOx、HC等污染物和油耗并辅助计算机软件进行分析。研究得出,山区道路设计、地形地貌和驾驶习惯对车辆油耗以及CO、NOx和HC排放有直接关系。可以通过坡道加宽、坡道延长、减少坡道红绿灯等措施减少车辆在山区道路行驶过程中速度变化频率,从而减少油耗以及CO、NOx和HC排放。     

Air transport and high-speed rail competition: Environmental implications and mitigation strategies

We build a duopoly model to shed light on the environmental impact of HSR-air transport competition, capturing the effects of induced demand, schedule frequency and HSR speed. The net environmental effect can be negative since there is a the trade-off between the substitution effect – how many passengers using the HSR are shifted from air transport – and the traffic generation effect – how much new demand is generated by the HSR. We conduct a simulation study based on the London-Paris market where HSR has served 70% of the market. The introduction of HSR is detrimental to LAP, while it is beneficial to GHG emissions. HSR entry increases neither LAP nor GHG emissions when the ratio between HSR and air transport emissions is relatively low. Moreover, competition is more likely to be detrimental to the environment when the weight of the social welfare in HSR objective function is high. Since the magnitude of the environmental friendliness of HSR compared to air transport hinges on the mix of energy sources used to generate the electricity (which is heavily constrained by the country in which HSR operates), regulators should assess the implications of HSR entry taking into account the energy policy and mitigation strategies available to transport modes.     

Evaluating effects of traffic and vehicle characteristics on vehicular emissions near traffic intersections

Urban air quality is generally poor at traffic intersections due to variations in vehicles’ speeds as they approach and leave. This paper examines the effect of traffic, vehicle and road characteristics on vehicular emissions with a view to understand a link between emissions and the most likely influencing and measurable characteristics. It demonstrates the relationships of traffic, vehicle and intersection characteristics with vehicular exhaust emissions and reviews the traffic flow and emission models. Most studies have found that vehicular exhaust emissions near traffic intersections are largely dependent on fleet speed, deceleration speed, queuing time in idle mode with a red signal time, acceleration speed, queue length, traffic-flow rate and ambient conditions. The vehicular composition also affects emissions. These parameters can be quantified and incorporated into the emission models. There is no validated methodology to quantify some non-measurable parameters such as driving behaviour, pedestrian activity, and road conditions     

A new modelling approach for road traffic emissions: VERSIT+

The objective of VERSIT+ LD is to predict traffic stream emissions for light-duty vehicles in any particular traffic situation. With respect to hot running emissions, VERSIT+ LD consists of a set of statistical models for detailed vehicle categories that have been constructed using multiple linear regression analysis. The aim is to find empirical relationships between mean emission factors, including confidence intervals, and a limited number of speed–time profile and vehicle related variables. VERSIT+ is a versatile model that has already been used in different projects at different geographical levels. Compared to COPERT IV, the VERSIT+ average speed algorithms provide increased accuracy with respect to the prediction of emissions in specific traffic situations.     

Evaluating the impacts of urban corridor traffic signal optimization on vehicle emissions and fuel consumption

This study investigates the impacts of traffic signal timing optimization on vehicular fuel consumption and emissions at an urban corridor. The traffic signal optimization approach proposed integrates a TRANSIMS microscopic traffic simulator, the VT-Micro model (a microscopic emission and fuel consumption estimation model), and a genetic algorithm (GA)-based optimizer. An urban corridor consisting of four signalized intersections in Charlottesville, VA, USA, is used for a case study. The result of the case study is then compared with the best traffic signal timing plan generated by Synchro using the TRANSIMS microscopic traffic simulator. The proposed approach achieves much better performance than that of the best Synchro solution in terms of air quality, energy and mobility measures: 20% less network-wide fuel consumption, 8–20% less vehicle emissions, and nearly 27% less vehicle-hours-traveled (VHT).     

Accounting for traffic speed dynamics when calculating COPERT and PHEM pollutant emissions at the urban scale

Coupling a traffic microsimulation with an emission model is a means of assessing fuel consumptions and pollutant emissions at the urban scale. Dealing with congested states requires the efficient capture of traffic dynamics and their conditioning for the emission model. Two emission models are investigated here: COPERT IV and PHEM v11. Emission calculations were performed at road segments over 6 min periods for an area of Paris covering 3 km². The resulting network fuel consumption (FC) and nitrogen oxide (NOx) emissions are then compared. This article investigates: (i) the sensitivity of COPERT to the mean speed definition, and (ii) how COPERT emission functions can be adapted to cope with vehicle dynamics related to congestion. In addition, emissions are evaluated using detailed traffic output (vehicle trajectories) paired with the instantaneous emission model, PHEM.COPERT emissions are very sensitive to mean speed definition. Using a degraded speed definition leads to an underestimation ranging from −13% to −25% for fuel consumption during congested periods (from −17% to −36% respectively for NOx emissions). Including speed distribution with COPERT leads to higher emissions, especially under congested conditions (+13% for FC and +16% for NOx). Finally, both these implementations are compared to the instantaneous modeling chain results. Performance indicators are introduced to quantify the sensitivity of the coupling to traffic dynamics. Using speed distributions, performance indicators are more or less doubled compared to traditional implementation, but remain lower than when relying on trajectories paired with the PHEM emission model.