Impacte da interação entre veículos motorizados e bicicletas na escolha de rota, desempenho de tráfego, emissões e segurança

Mobility in urban areas is highly complex because of the variety of possible facilities and routes, the multitude of origins and destinations, the increase of population and traffic. Increased use of active modes, such as cycling, presents economic and environmental benefits, and contributes to health improvement. However, it can lead to safety concerns such as bicycles sudden or unexpected movements mainly when circulating together with motor vehicles (MVs) or when there is an overtaking situation between MVs and bicycles. The main goal of this doctoral thesis is to quantify and assess the impact of the interaction motor vehicle-bicycle on traffic performance, road safety and emissions to define a multi-objective analysis model of the impacts regarding the use of motor vehicle and/or bicycle. The thesis was focused on three main topics developed based on the evaluation of traffic performance, safety and emissions at urban areas : (i) to perform a multi-objective analysis in an integrated manner of the traffic performance, pollutant emissions and road conflicts between bicycles and MVs at a signalized intersection; (ii) to assess the driving volatility in MV-bicycle interactions at two-lane roundabouts and its impacts on safety, pollutant emissions and traffic performance; and (iii) to analyze the impacts of the overtaking lateral distance between a bicycle and a MV on road safety and energy consumption at two-lane urban roads. Second-by-second bicycle and vehicle dynamic data were collected using GPS travel recorders. The methodology developed in this thesis was applied based on real world case studies at different urban road types in the city of Aveiro, Portugal. The present work uses a microscopic simulation platform of traffic (VISSIM), road safety (Surrogate Safety Assessment Methodology – SSAM) and emissions (Vehicle Specific Power – VSP) to analyze traffic operations, road safety concerns and to estimate carbon dioxide (CO2), nitrogen oxide (NOX), carbon monoxide (CO), and hydrocarbons (HC) pollutant emissions. Furthermore, the Fast Non-Dominated Sorting Genetic Algorithm (NSGA-II) was used in order to address the multi-objective analysis of traffic performance, road conflicts between MVs and bicycles, and emissions. Bicycle Specific Power (BSP) and VSP concepts were used in order to analyze the impacts on cyclist and vehicle energy consumption as well. The findings showed that roundabouts present, in general, better traffic performance (number of stops and travel time reduced in 78% and 14%, respectively) and less emissions (CO2, NOX, and HC decreased 9%, 7%, and 12%, respectively) than other intersections, even with high demand of cyclists (270 bicycles per hour). Regarding safety, roundabout layout lead to more severe conflicts and potential crashes while the number of total conflicts can be reduced significantly (-49%). It was also found that the impact of MVs and bicycles speeds, as well as roundabout design, were more important factors than bicycle volumes at roundabouts. Considering the MV-bicycle interaction at two-lane roundabout, the results of emissions dictated good relationships (R2 > 70%) between acceleration and VSP modes distributions. Finally, the findings showed 50% of overtaking lateral distance (between bicycle and MV) lower than 0.5m in both morning and afternoon peak hours. Moreover, it was found that there was a good fit between overtaking lateral distance and traffic volumes in morning (R2 = 72%) and afternoon (R2 = 67%) peak hours. The findings of this research can be useful for policy makers of the mobility and road safety fields, municipalities, road designers, and traffic engineers.A complexidade inerente à mobilidade em áreas urbanas está associada ao excesso de tráfego e à multiplicidade de origem-destinos, rotas e motivos de viagem. O incremento do uso dos modos suaves, nomeadamente da bicicleta, apresenta benefícios económicos e ambientais, contribuindo para a melhoria da saúde. No entanto, a presença de bicicletas acarreta preocupações ao nível da segurança dos ciclistas. As questões de segurança podem estar relacionadas com movimentos súbitos ou inesperados dos ciclistas, principalmente quando circulam em conjunto com veículos motorizados (VMs), ou quando há uma situação de ultrapassagem entre VMs e bicicletas. O principal objetivo da Tese de Doutoramento consistiu em quantificar e avaliar o impacto da interação entre veículos motorizados e bicicletas ao nível do desempenho de tráfego, segurança rodoviária e emissões para definir um modelo de análise multiobjetivo. A tese foi focada em três tópicos principais, desenvolvidos com base na avaliação do desempenho do tráfego, segurança e emissões em áreas urbanas: (i) análise multiobjetivo de forma integrada do desempenho do tráfego, emissões poluentes e conflitos rodoviários entre bicicletas e VMs em intersecções sinalizadas; (ii) avaliação da volatilidade de condução em interações VM-bicicleta em rotundas de duas vias e seus impactos na segurança, emissões de poluentes e desempenho de tráfego; e (iii) análise dos impactos ao nível de segurança rodoviária e consumo de energia em vias urbanas, com a avaliaçao da distância lateral de ultrapassagem entre uma bicicleta e um VM. Os dados da dinâmica do velocípede e do VM foram recolhidos e gravados segundo a segundo com um GPS. A metodologia desenvolvida nesta tese foi aplicada tendo por base os estudos de caso associados a diferentes tipos de vias urbanas na cidade de Aveiro, Portugal. O presente trabalho utiliza uma plataforma de simulação microscópica de tráfego (VISSIM), segurança rodoviária (SSAM) e emissões (Potência Específica do Veículo - VSP) para analisar as operações relacionadas com tráfego, questões com segurança rodoviária e estimar o dióxido de carbono (CO2), emissões de poluentes como o óxido de azoto (NOX), monóxido de carbono (CO) e hidrocarbonetos (HC). Além disso, para a análise multiobjetivo do desempenho do tráfego, conflitos rodoviários entre VMs e bicicletas, e emissões, o algoritmo genético NSGA-II (Nondominated sorted genetic algorithm II) foi utilizado. As metodologias de Potência Específica de Bicicleta (BSP) e VSP foram usados para analisar os impactos no consumo de energia do ciclista e do veículo, respetivamente. Os resultados mostraram que, em geral, as rotundas apresentam melhor desempenho de tráfego (número de paragens e tempo de viagem reduzidos em 78% e 14%, respetivamente) e menores emissões (CO2, NOX e HC diminuíram 9%, 7% e 12%, respetivamente) quando comparadas a outras interseções, mesmo com elevados níveis de ciclistas (270 bicicletas por hora). Em relação à segurança, o design da rotunda tende a favorecer a ocorrência de conflitos mais graves e potenciais acidentes, apesar do número total de conflitos poder diminuir significativamente (menos 49%). Descobriu-se também que o impacto das velocidades de circulação dos VMs e das bicicletas, bem como o design da rotunda constituem fatores mais importantes do que o volume de ciclistas nas rotundas. Considerando a interação VM-bicicleta numa rotunda de duas vias, os resultados das emissões sugerem boas relações (R2> 70%) entre as distribuições dos modos de aceleração e VSP. Por fim, os resultados mostraram que em 50% das ultrapassagens a distância lateral entre o velocípede e o VM foi menor que 0,5m, tanto na hora de ponta da manhã como da tarde. Além disso, verificou-se um bom ajuste entre a distância lateral de ultrapassagem e os volumes de tráfego nas horas de ponta da manhã (R2 = 72%) e da tarde (R2 = 67%). A metodologia e resultados desta investigação poderão ser utilizados por decisores políticos na área da mobilidade e da segurança rodoviária, câmaras, gestores e engenheiros de tráfego.Programa Doutoral em Engenharia Mecânic

Modelação interpretativa da segurança e emissões em corredores de rotundas e semáforos

Scientific research has demonstrated that the operational, environmental and safety performance for pedestrians depend on the geometric and traffic stream characteristics of the roundabout. However, the implementation of roundabouts may result in a trade-off among capacity, environmental, and safety variables. Also, little is known about the potential impacts for traffic from the use of functionally interdependent roundabouts in series along corridors. Thus, this doctoral thesis stresses the importance of understanding in how roundabout corridors affect traffic performance, vehicular emissions and safety for vulnerable users as pedestrians. The development of a methodology capable of integrating corridor’s geometric and operational elements is a contribution of this work. The main objectives of the thesis are as follows: 1) to analyze the effect of corridor’s design features in the acceleration patterns and emissions; 2) to understand the differences in the spatial distribution of emissions between roundabouts in isolation and along corridors; 3) to compare corridors with different forms of intersections such as conventional roundabouts, turbo-roundabouts, traffic lights and stop-controlled intersections; and 4) to design corridor-specific characteristics to optimize vehicle delay, and global (carbon dioxide – CO2) and local (carbon monoxide – CO, nitrogen oxides – NOX and hydrocarbons – HC) pollutant emissions. Vehicle dynamics along with traffic and pedestrian flow data were collected from 12 corridors with conventional roundabouts located in Portugal, Spain and in the United States, 3 turbo-roundabout corridors in the Netherlands, and 1 mixed roundabout/traffic-lights/stop-controlled corridor in Portugal. Data for approximately 2,000 km of road coverage over the course of 50 h have been collected. Subsequently, a microscopic platform of traffic (VISSIM), emissions (Vehicle Specific Power – VSP) and safety (Surrogate Safety Assessment Model – SSAM) was introduced to faithful reproduce site-specific operations and to examine different alternative scenarios. The main research findings showed that the spacing between intersections influenced vehicles acceleration-deceleration patterns and emissions. In contrast, the deflection angle at the entrances (element that impacts emissions on isolated roundabouts) impacted slightly on the spatial distribution of emissions. It was also found that the optimal crosswalk locations along mid-block sections in roundabout corridor was generally controlled by spacing, especially in the case of short spacing between intersections (< 200 m). The implementation of turbo-roundabout in series along corridors increased emissions compared to conventional two-lane roundabout corridors (1-5%, depending on the pollutant). By changing the location of a roundabout or turbo-roundabout to increase spacing in relation to upstream/downstream intersection resulted in an improvement of corridor emissions. Under conditions of high through traffic and unbalanced traffic flows between main roads and minor roads, vehicles along roundabout corridors produced fewer emissions (~5%) than did vehicles along signalized corridors, but they emitted more gases (~12%) compared to a corridor with stop-controlled intersections. This research contributed to the current state-of-art by proving a full comprehension about the operational and geometric benefits and limitations of roundabout corridors. It also established correlations between geometric variable of corridors (spacing), crosswalk locations or traffic streams, and delay, and CO2, CO, NOX or HC variables. With this research, it has been demonstrated that the implementation of a given intersection form within a corridor focused on minimizing CO2 may not be translated to other variables such as CO or NOX. Therefore, the develop methodology is a decision supporting tool capable of assessing and selecting suitable traffic controls according the site-specific needs.Estudos anteriores demonstram que os desempenhos operacional, ambiental e ao nível da segurança para os peões de uma rotunda dependem das suas características geométricas e dos fluxos de tráfego e de peões. Porém, a implementação de uma rotunda pode traduzir-se numa avaliação de compromisso entre as variáveis da capacidade, emissões de poluentes e segurança. Para além disso, a informação relativa às potencialidades de rotundas interdependentes ao longo de corredores é diminuta. Assim, esta tese de doutoramento centra-se na compreensão dos impactos no desempenho do tráfego, emissões e segurança dos peões inerentes ao funcionamento de corredores de rotundas. Uma das contribuições deste trabalho é o desenvolvimento de uma metodologia capaz de avaliar as características geométricas e operacionais dos corredores de forma integrada. Os principais objetivos desta tese são: 1) analisar o impacto dos elementos geométricos dos corredores de rotundas em termos dos perfis de aceleração e das emissões; 2) investigar as principais diferenças na distribuição espacial das emissões entre rotundas isoladas e em corredores; 3) comparar os desempenhos operacional e ambiental de corredores com diferentes tipos de interseções tais como rotundas convencionais, turbo-rotundas, cruzamentos semaforizados e interseções prioritárias; e 4) dimensionar um corredor de modo a otimizar o atraso dos veículos, e emissões de poluentes globais (dióxido de carbono – CO2) e locais (monóxido de carbono – CO, óxidos de azoto – NOx e hidrocarbonetos – HC). O trabalho de monitorização experimental consistiu na recolha de dados da dinâmica do veículo, e volumes de tráfego e pedonais. Para tal, foram selecionados 12 corredores com rotundas convencionais em Portugal, Espanha e Estados Unidos da América, 3 corredores com turbo-rotundas na Holanda e ainda um corredor misto com rotundas, sinais luminosos e interseções prioritárias em Portugal. No total foram recolhidos aproximadamente 2000 km de dados da dinâmica do veículo, num total de 50 h. Foi utilizada uma plataforma de modelação microscópica de tráfego (VISSIM), emissões (Vehicle Specific Power – VSP) e segurança (Surrogate Safety Assessment Model – SSAM) de modo a replicar as condições de tráfego locais e avaliar cenários alternativos. Os resultados mostraram que o espaçamento entre interseções teve um impacto significativo nos perfis de aceleração e emissões. No entanto, tal não se verificou para o ângulo de deflexão de entrada (elemento fulcral nos níveis de emissões em rotundas isoladas), nomeadamente nos casos em que as rotundas adjacentes estavam próximas (< 200 m). A implementação de corredores de turbo-rotundas conduziu ao aumento das emissões face a um corredor convencional de rotundas com duas vias (1-5%, dependendo do poluente). A relocalização de uma rotunda ou turbo-rotunda no interior do corredor, de modo a aumentar o espaçamento em relação a uma interseção a jusante e/ou a montante, levou a uma melhoria das emissões do corredor. Conclui-se também que em condições de elevado tráfego de atravessamento e não uniformemente distribuído entre as vias principais e secundárias, os veículos ao longo de um corredor com rotundas produziram menos emissões (~5%) face a um corredor com semáforos, mas emitiram mais gases (~12%) comparativamente a um corredor de interseções prioritárias. Esta investigação contribuiu para o estado de arte através da análise detalhada dos benefícios e limitações dos corredores de rotundas tanto ao nível geométrico como ao nível operacional. Adicionalmente, estabeleceram-se várias correlações entre variáveis geométricas do corredor (espaçamento), localização das passadeiras e volume de tráfego, o atraso, e emissões de CO2, CO, NOX e HC. Demonstrou-se ainda que a implementação de uma interseção ao longo do corredor com a finalidade de minimizar o CO2 pode não resultar na melhoria de outras variáveis tais como o CO ou NOX. Esta metodologia serve como apoio à decisão e, portanto, permite avaliar o tipo de interseção mais adequado de acordo com as especificidades de cada local.Programa Doutoral em Engenharia Mecânic

Integrating vehicle specific power methodology and microsimulation in estimating emissions on urban roundabouts

In this study pollutant emissions were estimated from VSP modal emission rates and the distribution of time spent in each VSP mode obtained from the speed profiles both gathered in the field and simulated in AIMSUN at a sample of urban roundabouts. The versatility of the micro-simulation model for a calibration aimed at improving accuracy of emissions estimates was tested in order to ensure that second-by-second trajectories experienced in the field by a test vehicle through the sampled roundabouts properly reflected the simulated speed profiles. The first results which the thesis will refer, confirmed the feasibility of the smart approach that integrates the use of field-observed and simulated data to estimate emissions at urban roundabouts. It is also revealed friendly in collecting information via smartphone and in the subsequent data analysis and provided suggestions for large-scale data collection through a digital community. Another goal of this research is to investigate about the environmental performance after a conversion of a traditional existing roundabout into a turbo-roundabout. This aspect has been considered a positive approach for a novel attitude in the performance evaluation of road networks to align the infrastructural design with the aim of sustainable and low-emission mobility. The main finding provided from this study is referred to the positive potential of a novel attitude in the conceptualization and performance evaluation of road units in order to align urban infrastructural projects with the worldwide shared long-term ambitions for a low-emission mobility

Modeling Driving Behavior at Traffic Control Devices

Transportation is a major source of many major air pollutants as well as greenhouse gas emissions. The four common factors responsible for vehicular emissions are vehicle, road characteristics, traffic conditions and driving behavior. The objective of this dissertation was to study driving behavior since it is highly correlated to emissions as shown by previous studies. Understanding driving behavior is likely to help improve emissions estimates. In this dissertation, three levels of analyses of driving behavior were conducted including: (1) exploring driving behavior parameters and assessing their impact on emissions, (2) comparing driving behavior among the three most common traffic control devices, and (3) modeling second-by-second driving behavior of individual drivers. In order to explore these relationships, spatial location, vehicle kinematics, and CO2 emissions were collected along a study road corridor in Urbandale (IA) was. The chosen road corridor comprised of a roundabout, an all-way-stop and a traffic signal along with curve and tangent sections. The traffic during peak and off-peak hours on the corridor was comparable. This was useful for comparing driving behavior across drivers under similar conditions. A single instrumented vehicle was driven over the corridor by four different subject drivers. The vehicle was equipped with a portable emissions measurement device which had engine sensor, tail-pipe sample lines and a GPS. In the first analysis, vehicle kinematic variables were used to derive driving behavior parameters that included gas pedal use and brake pedal use. Two groups of drivers were identified based on these parameters. The study identified gaspad and brakepad as important driving behavior parameters which can explain variation in vehicular emissions. Driving behavior parameters used in previous studies for developing driving cycle were utilized in this study to compare driving behavior between traffic control devices for the second analysis. These parameters characterized speed behavior, speed change behavior and energy gain behavior. A MANOVA model was used for comparing the overall driving behavior between traffic control devices by comparing these parameters. Results showed that driving behavior at the roundabout and all-way-stop differ significantly (p \u3c 0.001) on at least one of driving behavior parameter. Likewise, roundabout and traffic signals also differed in terms of driving behavior (p \u3c 0.001). Driving behavior and emissions are highly correlated. This implies using separate emission factors for different traffic control devices. In the third analysis, speed profiles at roundabout were modeled for the drivers using a fourth degree polynomial regression. Results showed that speed profiles models were significantly different across drivers. This implied that drivers must be treated as random variables in modeling driving behavior and emissions for a given road or driver population. Average speeds of drivers at yield point were simulated based on the model. The maximum difference was found to be about 1.5 mph

Assessing the Environmental Performances of Urban Roundabouts Using the VSP Methodology and AIMSUN

In line with globally shared environmental sustainability goals, the shift towards citizen-friendly mobility is changing the way people move through cities and road user behaviour. Building a sustainable road transport requires design knowledge to develop increasingly green road infrastructures and monitoring the environmental impacts from mobile crowdsourced data. In this view, the paper presents an empirically based methodology that integrates the vehicle-specific power (VSP) model and microscopic traffic simulation (AIMSUN) to estimate second-by-second vehicle emissions at urban roundabouts. The distributions of time spent in each VSP mode from instantaneous vehicle trajectory data gathered in the field via smartphone were the starting point of the analysis. The versatility of AIMSUN in calibrating the model parameters to better reflect the field-observed speed-time trajectories and to enhance the estimation accuracy was assessed. The conversion of an existing roundabout within the sample into a turbo counterpart was also made as an attempt to confirm the reproducibility of the proposed procedure. The results shed light on new opportunities in the environmental performance evaluation of road units when changes in design or operation should be considered within traffic management strategies and highlighted the potential of the smart approach in collecting big amounts of data through digital communities

Real-Time Vehicle Emission Estimation Using Traffic Data

The current state of climate change should be addressed by all sectors that contribute to it. One of the major contributors is the transportation sector, which generates a quarter of greenhouse gas emissions in North America. Most of these transportation related emissions are from road vehicles; as result, how to manage and control traffic or vehicular emissions is therefore becoming a major concern for the governments, the public and the transportation authorities. One of the key requirements to emission management and control is the ability to quantify the magnitude of emissions by traffic of an existing or future network under specific road plans, designs and traffic management schemes. Unfortunately, vehicular traffic emissions are difficult to quantify or predict, which has led a significant number of efforts over the past decades to address this challenge. Three general methods have been proposed in literature. The first method is for determining the traffic emissions of an existing road network with the idea of measuring the tail-pipe emissions of individual vehicles directly. This approach, while most accurate, is costly and difficult to scale as it would require all vehicles being equipped with tail-pipe emission sensors. The second approach is applying ambient pollutant sensors to measure the emissions generated by the traffic near the sensors. This method is only approximate as the vehicle-generated emissions can easily be confounded by other nearby emitters and weather and environmental conditions. Note that both of these methods are measurement-based and can only be used to evaluate the existing conditions (e.g., after a traffic project is implemented), which means that it cannot be used for evaluating alternative transportation projects at the planning stage. The last method is model-based with the idea of developing models that can be used to estimate traffic emissions. The emission models in this method link the amount of emissions being generated by a group of vehicles to their operations details as well as other influencing factors such as weather, fuel and road geometry. This last method is the most scalable, both spatially and temporally, and also most flexible as it can meet the needs of both monitoring (using field data) and prediction. Typically, traffic emissions are modelled on a macroscopic scale based on the distance travelled by vehicles and their average speeds. However, for traffic management applications, a model of higher granularity would be preferred so that impacts of different traffic control schemes can be captured. Furthermore, recent advances in vehicle detection technology has significantly increased the spatiotemporal resolutions of traffic data. For example, video-based vehicle detection can provide more details about vehicle movements and vehicle types than previous methods like inductive loop detection. Using such detection data, the vehicle movements, referred to as trajectories, can be determined on a second-by-second basis. These vehicle trajectories can then be used to estimate the emissions produced by the vehicles. In this research, we have proposed a new approach that can be used to estimate traffic generated emissions in real time using high resolution traffic data. The essential component of the proposed emission estimation method is the process to reconstruct vehicle trajectories based on available data and some assumptions on the expected vehicle motions including cruising, acceleration and deceleration, and car-following. The reconstructed trajectories containing instantaneous speed and acceleration data are then used to estimate emissions using the MOVES emission simulator. Furthermore, a simplified rate-based module was developed to replace the MOVES software for direct emission calculation, leading to significant improvement in the computational efficiency of the proposed method. The proposed method was tested in a simulated environment using the well-known traffic simulator - Vissim. In the Vissim model, the traffic activities, signal timing, and vehicle detection were simulated and both the original vehicle trajectories and detection data recorded. To evaluate the proposed method, two sets of emission estimates are compared: the “ground truth” set of estimates comes from the originally simulated vehicle trajectories, and the set from trajectories reconstructed using the detection data. Results show that the performance of the proposed method depends on many factors, such as traffic volumes, the placement of detectors, and which greenhouse gas is being estimated. Sensitivity analyses were performed to see whether the proposed method is sufficiently sensitive to the impacts of traffic control schemes. The results from the sensitivity analyses indicate that the proposed method can capture impacts of signal timing changes and signal coordination but is insufficiently sensitive to speed limit changes. Further research is recommended to validate the proposed method using field studies. Another recommendation, which falls outside of this area of research, would be to investigate the feasibility of equipping vehicles with devices that can record their instantaneous fuel consumption and location data. With this information, traffic controllers would be better informed for emission estimation than they would be with only detection data

Intersection Signal Control and Design for Improved Person Mobility and Air Quality in Urban Multimodal Transportation Systems

Alternative geometric designs (e.g. roundabouts) and multi-objective signal control strategies are promising measures to improve sustainability of traffic networks. However, roundabouts are mostly used because of their safety and operational advantages. There has been less attention to the environmental performance of roundabouts. Also, the existing studies have been mostly used through field measurements and current simulation models, which need high calibration efforts and they are not inclusive in terms of considering all influencing factors on vehicular emissions at roundabouts. Furthermore, the existing real-time signal control strategies do not account for the emission rates of different vehicle types (e.g. cars and buses). In addition, the real-time multi-objective signal control systems does not consider environmental objectives. This dissertation develops a real-time bi-objective signal control system for isolated intersections, which operate at undersaturated traffic conditions that minimizes a weighted combination of vehicle delay (or person delay) and emissions of auto and transit vehicles. Pareto Frontiers of the optimal solutions are presented to help decision makers select the most appropriate combinations of objectives to achieve desirable levels of delay and emissions. Additionally, a simple simulation tool based on Cellular Automata (CA) model of traffic simulation is developed to estimate delay and reproduce vehicle trajectories for emission estimation. The models are used to compare the operational and environmental performance of roundabouts and signalized intersections and perform sensitivity analysis with respect to total traffic demand, left turn ratio, and pedestrian volume. Evaluation tests show that replacing a signalized intersection with a roundabout results in improved delay and emissions at undersaturated traffic conditions and any pedestrian volume. It also shows that roundabouts’ performance is less affected by high left turning demand compared to signalized intersections. On the contrary, roundabouts’ performance is sensitive to frequent pedestrian crossings while the performance of signalized intersections is not affected by pedestrian crossings

ESTIMATING THE IMPACT OF INTERSECTION TRAFFIC ON AIR QUALITY EMISSIONS AT CAMDEN COOPER MEDICAL HEALTH INTERSECTION THROUGH THE INTEGRATION OF VISSIM/MOVES MODELS

Traffic emissions near intersections can increase significantly due to idling as well as stop-and-go traffic conditions. Increased emissions of pollutants like particulate matter (PM), nitrogen oxides (NOx), carbon monoxide (CO), and polycyclic aromatic hydrocarbons (PAHs) found in traffic exhaust deteriorate the health of the population that is exposed to them. Since general traffic emissions are increased by the stop-and-go conditions produced at intersections, PAH traffic emissions should also increase from intersection driving conditions. The intersection of Dr. Martin Luther King Jr. Blvd and Haddon Ave in Camden, NJ was identified as an ideal site to study PAH traffic emissions. To identify intersection effect on PAH emissions, the traffic modeler VISSIM was used to generate individual vehicle data for intersection driving conditions and hypothetical uncontrolled “Free-Flow” driving conditions based on traffic data obtained from Go Pro videos of the intersection. Output data from VISSIM was converted into input data for the emissions modeler MOVES3 using, VISSIM-MOVES Integration, an Excel-based tool developed for this study. The MOVES results were limited to the PM and PAH emissions to compare with collected air samples. The model showed that particle-bound PAH emissions were 2.4 to 3.4 times higher at intersections and gaseous PAH and PM emissions were twice as high

Are internally observable vehicle data good predictors of vehicle emissions?

Scientific research has demonstrated that on-road exhaust emissions in diesel passenger vehicles (DPV) exceeds the official laboratory-test values. Increasing concern about the quantification of magnitude for these differences has meant an increasing use of Portable Emissions Monitoring System (PEMS), but the direct use of Internally Observable Variables (IOVs) can be useful to predict emissions. The motivation for this paper is to develop an empirical approach that integrates second-by-second vehicle activity and emission rates for DPV. The objectives of this research are two-fold: (1) to assess the effect of variation in acceleration-based parameters, vehicle specific power (VSP) and IOVs on carbon dioxide (CO2) and nitrogen oxides (NOx) emission rates; and (2) to examine the correlation between IOV-based predictors of engine load and VSP. Field measurements were collected from four DPV (two small, one medium and one multi-purpose) in urban, rural and highway routes using PEMS, Global Positioning System (GPS) receivers and On-board Diagnostic (OBD) scan tool, to measure real-world exhaust emissions and engine activity data. Results suggest the relative positive acceleration (RPA) and mean positive acceleration (MPA) allowed a good differentiation with respect to route trips. IOVs models based on the product of manifold absolute pressure (MAP) and engine revolutions per minute (RPM), and VSP showed to be good predictors of emission rates. Although the CO2 correlation was found to be good (R2 > 0.8), the models for NOx showed mixed results since some vehicles showed a reasonable correlation (R2 ~ 0.7) while others resulted in worst model predictions (R2 < 0.6). IOVs models have potential to be integrated into vehicle engine units and connected vehicles, for instance, to provide real-time information on emissions rates, but other parameters regarding the thermal management on after treatment system must be included in NOx prediction. This would allow for a better understanding of true physics behind NOx emissions in DPV.publishe

Modeling, Control, and Impact Analysis of The Next Generation Transportation System

This dissertation aims to develop a systematic tool designated for connected and autonomous vehicles, integrating the simulation of traffic dynamics, traffic control strategies, and impact analysis at the network level. The first part of the dissertation is devoted to the traffic flow modeling of connected vehicles. This task is the foundation step for transportation planning, optimized network design, efficient traffic control strategies, etc, of the next generation transportation system. Chapter 2 proposes a cell-based simulation approach to model the proactive driving behavior of connected vehicles. Firstly, a state variable of connected vehicle is introduced to track the trajectory of connected vehicles. Then the exit flow of cells containing connected vehicles is adjusted to simulate the proactive driving behavior, such that the traffic light is green when the connected vehicle arrives at the signalized intersection. Extensive numerical simulation results consistently show that the presence of connected vehicles contributes significantly to the smoothing of traffic flow and vehicular emission reductions in the network. Chapter 3 proposes an optimal estimation approach to calibrate connected vehicles\u27 car-following behavior in a mixed traffic environment. Particularly, the state-space system dynamics is captured by the simplified car-following model with disturbances, where the trajectory of non-connected vehicles are considered as unknown states and the trajectory of connected vehicles are considered as measurements with errors. Objective of the reformulation is to obtain an optimal estimation of states and model parameters simultaneously. It is shown that the customized state-space model is identifiable with the mild assumption that the disturbance covariance of the state update process is diagonal. Then a modified Expectation-Maximization (EM) algorithm based on Kalman smoother is developed to solve the optimal estimation problem. The second part of the dissertation is on traffic control strategies. This task drives the next generation transportation system to a better performance state in terms of safety, mobility, travel time saving, vehicular emission reduction, etc. Chapter 4 develops a novel reinforcement learning algorithm for the challenging coordinated signal control problem. Traffic signals are modeled as intelligent agents interacting with the stochastic traffic environment. The model is built on the framework of coordinated reinforcement learning. The Junction Tree Algorithm based reinforcement learning is proposed to obtain an exact inference of the best joint actions for all the coordinated intersections. The algorithm is implemented and tested with a network containing 18 signalized intersections from a microscopic traffic simulator. Chapter 5 develops a novel linear programming formulation for autonomous intersection control (LPAIC) accounting for traffic dynamics within a connected vehicle environment. Firstly, a lane based bi-level optimization model is introduced to propagate traffic flows in the network. Then the bi-level optimization model is transformed to the linear programming formulation by relaxing the nonlinear constraints with a set of linear inequalities. One special feature of the LPAIC formulation is that the entries of the constraint matrix has only values in {-1, 0, 1}. Moreover, it is proved that the constraint matrix is totally unimodular, the optimal solution exists and contains only integer values. Further, it shows that traffic flows from different lanes pass through the conflict points of the intersection safely and there are no holding flows in the solution. Three numerical case studies are conducted to demonstrate the properties and effectiveness of the LPAIC formulation to solve autonomous intersection control. The third part of the dissertation moves on to the impact analysis of connected vehicles and autonomous vehicles at the network level. This task assesses the positive and negative impacts of the system and provides guidance on transportation planning, traffic control, transportation budget spending, etc. In this part, the impact of different penetration rates of connected vehicle and autonomous vehicles is revealed on the network efficiency of a transportation system. Chapter 6 sets out to model an efficient and fair transportation system accounting for both departure time choice and route choice of a general multi OD network within a dynamic traffic assignment environment. Firstly, a bi-level optimization formulation is introduced based on the link-based traffic flow model. The upper level of the formulation minimizes the total system travel time, whereas the lower level captures traffic flow propagation and the user equilibrium constraint. Then the bi-level formulation is relaxed to a linear programming formulation that produces a lower bound of an efficient and fair system state. An efficient iterative algorithm is proposed to obtain the exact solution. It is shown that the number of iterations is bounded, and the output traffic flow solution is efficient and fair. Finally, two numerical cases (including a single OD network and a multi-OD network) are conducted to demonstrate the performance of the algorithm. The results consistently show that the travel time of different departure rates of the same OD pair are identical and the algorithm converges within two iterations across all test scenarios