The connected vehicle technology presents an innovative way of sharing information between vehicles and the transportation infrastructure through wireless communications. The technology can potentially solve safety, mobility, and environmental challenges that face the transportation sector. Signal phasing and timing information is one category of information that can be broadcasted through connected vehicle technology. This thesis presents an in-depth study of possible ways signal phasing and timing information can be beneficial as far as safety and mobility are concerned. In total, three studies describing this research are outlined. The first study presented herein focuses on data collection and calibration efforts of the simulation model that was used for the next two studies. The study demonstrated a genetic algorithm procedure for calibrating VISSIM discharge headways based on queue discharge headways measured in the field. Video data was used to first compute intersection discharge headways for individual vehicle queue position and then to develop statistical distributions of discharge headways for each vehicle position. Except for the 4th vehicle position, which was best fitted by the generalized extreme value (GEV) distribution, the Log-logistic distribution was observed to be the best fit distribution for the rest of vehicle positions. Starting with the default values, the VISSIM parameters responsible for determining discharge headways were heuristically adjusted to produce optimal values. The optimal solutions were achieved by minimizing the Root Mean Square Error (RMSE) between the simulated and observed data. Through calibration, for each vehicle position, it was possible to obtain the simulated headways that reflect the means of the observed field headways. However, calibration was unable to replicate the dispersion of the headways observed in the field mainly due to VISSIM limitations. Based on the findings of this study, future work on calibration in VISSIM that would account for the dispersion of mixed traffic flow characteristics is warranted. The second study addresses the potential of connected vehicles in improving safety at the vicinity of signalized intersections. Although traffic signals are installed to reduce the overall number of collisions at intersections, rear-end collisions are increased due to signalization. One dominant factor associated with rear-end crashes is the indecisiveness of the driver, especially in the dilemma zone. An advisory system to help the driver make the stop-or-pass decision would greatly improve intersection safety. This study proposed and evaluated an Advanced Stop Assist System (ASAS) at signalized intersections by using Infrastructure-to-Vehicle (I2V) and Vehicle-to-Vehicle (V2V) communication. The proposed system utilizes communication data, received from Roadside Unit (RSU), to provide drivers in approaching vehicles with vehicle-specific advisory speed messages to prevent vehicle hard-braking upon a yellow and red signal indication. A simulation test bed was modeled using VISSIM to evaluate the effectiveness of the proposed system. The results demonstrate that at full market penetration (100% saturation of vehicles equipped with on-board communication equipment), the proposed system reduces the number of hard-braking vehicles by nearly 50%. Sensitivity analyses of market penetration rates also show a degradation in safety conditions at penetration rates lower than 40%. The results suggest that at least 60% penetration rate is required for the proposed system to minimize rear-end collisions and improve safety at the signalized intersections. The last study addresses the fact that achieving smooth urban traffic flow requires reduction of excessive stop-and-go driving on urban arterials. Smooth traffic flow comes with several benefits including reduction of fuel consumption and emissions. Recently, more research efforts have been directed towards reduction of vehicle emissions. One such effort is the use of Green Light Optimal Speed Advisory (GLOSA) systems which use wireless communications to provide individual drivers with information on the approaching traffic signal phase and advisory speeds to arrive at the intersection on a green phase. Previously developed GLOSA algorithms do not address the impact of time to discharge queues formed at the intersection. Thus, this study investigated the influence of formed intersection queues on the performance of GLOSA systems. A simulation test-bed was modeled inside VISSIM to evaluate the algorithm’s effectiveness. Three simulation scenarios were designed; the baseline with no GLOSA in place, scenario 2 with GLOSA activated and queue discharge time not considered, and scenario 3 with GLOSA activated and where queue dissipation time was used to compute advisory speeds. At confidence level the results show a significant reduction in the time spent in queue when GLOSA is activated (scenarios 2 and 3). The change in the average number of stops along the corridor was found not to be significant when the base scenario was compared against scenario 2. However, a comparison between scenarios 2 and 3 demonstrates a significant reduction in the average number of stops along the corridor, and also in the time spent waiting in queues

This study presents an analysis of detour operations as a concept of congestion management. Since a large portion of traffic delay emanates from traffic incidents, the goal of the study was to alleviate incident-induced impacts on freeways by diverting congested traffic on to adjacent roadway facilities. To balance the demand between freeway and arterial systems, optimization was required through Integrated Corridor Management (ICM). This thesis examines the justification and optimization of dynamic traffic routing strategies. Previous studies have justified detour operations based solely on traffic simulation results. This study quantifies the impacts from freeway incidents on a parallel arterial roadway using a data-driven signal processing technique, with operating speeds adopted as a performance measure. Results show that rerouting traffic to an adjacent arterial road, due to a freeway incident, can mitigate the mobility of the corridor with a probability of up to 88% depending on the type of incident and occurrence time. Results also indicate that diverting traffic during off-peak hours, especially for minor incidents, provides minimal mobility benefits. A secondary focus of this study explored the optimum dynamic traffic diversion, to an adjacent arterial roadway, from incident-induced freeway congestion to better utilize the freeway’s available corridor capacity. VISSIM, a microsimulation tool, was employed to simulate a freeway incident and measure the performance of detour operations. A 23 full factorial central composite design was used to establish a relationship between the performance of the detour operation and three control factors: incident duration, diversion rate, and demand level. The resulting regression equation predicts the corridor delay with over 83% accuracy. The findings of this study can potentially serve as a building block in the understanding and development of future ICM systems and incident management plans.

Abstract Although researchers have studied the effects of platooning, most of the work done so far has focused on fuel consumption. There are a few studies that have targeted the impact of platooning on the highway operations and safety. This thesis focuses on the impact of heavy-duty vehicles (HDVs) platooning on highway characteristics. Specifically, this study aims at evaluating the effects of platooning of HDVs on capacity, safety, and CO2 emissions. This study is based on a hypothetical model that was created using the VISSIM software. VISSIM is a powerful simulation software designed to mimic the field traffic flow conditions. For model validity, the model outputs were compared with recommended values from guidelines such as the Highway Capacity Manual (HCM) (Transportation Research Board, 2016). VISSIM was used to obtain the simulation results regarding capacity. However, in addition to VISSIM, two other software packages were used to obtain outputs that cannot be assessed in VISSIM. MOVES and SSAM are two simulation software packages that were used for emission and safety metrics, respectively. Both software packages depended on input from VISSIM for analysis. It was found that with the presence of HDVs in the model, the capacity, the emission of CO2, and the safety of the roadway would improve positively. A capacity of 4200 PCE/h/ln could be achieved when there are enough HDVs in platoons. Furthermore, more than 3% of the traffic flow emission of CO2 reduction is possible when 100% of the HDVs used in the model are in platoons. In addition to that, a reduction of more than 75% of the total number of conflicts might be obtained. Furthermore, with the analysis of the full factorial method and the Design of Experiment (DOE) conducted by using Excel and Minitab respectively, it was possible to investigate the impact of the platoons’ factors on the highway parameters. Most of these factors affect the parameters significantly. However, the change in the desired speed was found to insignificantly affect the highway parameters, due to the high penetration rate. Keywords: VISSIM, MOVES, SSAM, COM-interface, HDVs, Platooning, Number of Conflicts

Computer based simulation models have often been used to study the multimodal freight transportation system. But these studies have not been able to dynamically couple the various modes into one model; therefore, they are limited in their ability to inform on dynamic system level interactions. This research thesis is motivated by the need to dynamically couple the multimodal freight transportation system to operate at multiple spatial and temporal scales. It is part of a larger research program to develop a systems modeling framework applicable to freight transportation. This larger research program attempts to dynamically couple railroad, seaport, and highway freight transportation models. The focus of this thesis is the development of the coupled railroad and seaport models. A separate volume (Wall 2010) on the development of the highway model has been completed. The model railroad and seaport was developed using Arena® simulation software and it comprises of the Ports of Savannah, GA, Charleston, NC, Jacksonville, FL, their adjacent CSX rail terminal, and connecting CSX railroads in the southeastern U.S. However, only the simulation outputs for the Port of Savannah are discussed in this paper. It should be mentioned that the modeled port layout is only conceptual; therefore, any inferences drawn from the model's outputs do not represent actual port performance. The model was run for 26 continuous simulation days, generating 141 containership calls, 147 highway truck deliveries of containers, 900 trains, and a throughput of 28,738 containers at the Port of Savannah, GA. An analysis of each train's trajectory from origin to destination shows that trains spend between 24 - 67 percent of their travel time idle on the tracks waiting for permission to move. Train parking demand analysis on the adjacent shunting area at the multimodal terminal seems to indicate that there aren't enough containers coming from the port because the demand is due to only trains waiting to load. The simulation also shows that on average it takes containerships calling at the Port of Savannah about 3.2 days to find an available dock to berth and unload containers. The observed mean turnaround time for containerships was 4.5 days. This experiment also shows that container residence time within the port and adjacent multimodal rail terminal varies widely. Residence times within the port range from about 0.2 hours to 9 hours with a mean of 1 hour. The average residence time inside the rail terminal is about 20 minutes but observations varied from as little as 2 minutes to a high of 2.5 hours. In addition, about 85 percent of container residence time in the port is spent idle. This research thesis demonstrates that it is possible to dynamically couple the different sub-models of the multimodal freight transportation system. However, there are challenges that need to be addressed by future research. The principal challenge is the development of a more efficient train movement algorithm that can incorporate the actual Direct Traffic Control (DTC) and / or Automatic Block Signal (ABS) track segmentation. Such an algorithm would likely improve the capacity estimates of the railroad network. In addition, future research should seek to reduce the high computational cost imposed by a discrete process modeling methodology and the adoption of single container resolution level for terminal operations. A methodology combining both discrete and continuous process modeling as proposed in this study could lessen computational costs and lower computer system requirements at a cost of some of the feedback capabilities of the model This tradeoff must be carefully examined.

El sistema Bus Rapid Transit (BRT) es uno de los modos de transporte más demandados en los últimos años. Este sistema de transporte cuenta con estaciones para los usuarios y múltiples líneas de buses en una determinada ciudad. Sin embargo, el desorden en el recorrido de los usuarios a lo largo de la estación y la alta densidad e interacción peatonal generan largos tiempos de espera para los usuarios desde que entran a la estación hasta su embarco al bus. La presente investigación propone una gestión de la movilidad peatonal, la cual mediante la canalización de flujos peatonales y adaptación de entradas y salidas de la estación tiene por objetivo principal reducir los tiempos de espera de los usuarios dentro de la estación. Se realizó visitas a una estación de BRT en la ciudad de Lima para medir los tiempos de espera de los usuarios dentro de esta. La recolección de información nos permitió establecer el horario de más concurrencia peatonal y demostrar que los usuarios pueden demorar más tiempo dentro de la estación que en el bus. La propuesta fue simulada en el software Vissim para poder determinar su eficiencia. Los resultados muestran que se redujo los tiempos de espera de los usuarios dentro de la estación en un 25%. Por otro lado, el valor de la densidad peatonal y los puntos de conflicto entre peatones disminuyeron en un 44% y 73% respectivamente. Finalmente se obtuvo un aumento en la velocidad peatonal de los corredores en un 37%. / The Bus Rapid Transit (BRT) is a bus-based public transport system that increase the effectiveness of public transportation through dedicated lanes with busways and independent stations. However, the pedestrian routes disorder at the station, the high density and the interaction between pedestrians produce high waiting times since the entrance at the station until the board at the bus. The present research proposes a management of pedestrian mobility focused on modify the pedestrian routes and adapting the entrance and exit of the station. The main objective of the investigation is reducing the waiting times of users at the station. Users waiting times at the station were measured by visiting a BRT station located in the city of Lima. The collection of information makes it possible to establish the peak pedestrian traffic hours and demonstrate that users can spend more time at the station than on the bus. The improvement proposal was simulated in Vissim software in order to determine its reducing waiting times efficiency. The results show that users waiting times at the station were reduced by 25%. On the other hand, the pedestrian density and conflict points between pedestrians decreased by 44% and 73% respectively. Finally, increase in the pedestrian velocity of the corridors was obtained by 37%. / Tesis

No description available.

La presente investigación está orientada a mejorar los niveles de servicio de una rotonda mediante la optimización de su capacidad, a partir de cambios en los elementos de diseño geométrico. En ese sentido se realizó un análisis y evaluación de la rotonda “Higuereta”, la cual se encuentra ubicada en el distrito de Santiago de Surco, en la ciudad de Lima en Perú. Para ello, se realizó una recopilación de bases teóricas a nivel internacional para conocer los fundamentos del diseño geométrico. Es así que, partiendo de un modelo matemático determinístico proveniente de Reino Unido, Kimber 1980, que asocia los parámetros geométricos con el flujo circulante y demuestra que cualquier cambio en un elemento de diseño geométrico es directamente proporcional a la capacidad, podemos concluir que existe mejoras en los niveles de servicio siempre que realicemos variaciones significativas en la geometría. En la presente investigación se evidenció mejoras de un nivel de servicio “F” hasta uno “D”. Por otro lado, se modeló la rotonda a partir de un software de micro simulación, PTV Vissim 9, con el objetivo de poder reflejar mediante simulaciones el comportamiento real del tráfico antes y después de introducir cambios en los parámetros geométricos. Se concluyó que existe mejoras en los niveles de servicio por acceso, de un “D” a un “C. Finalmente, para tener la certeza que el modelo reflejó la realidad se calibró a través de ajustes en los parámetros de comportamiento del conductor y se validó a partir de un indicador estadístico. / This research is aimed at improving the service levels of a roundabout by optimizing its capacity, based on changes in the geometric design elements. In this sense, an analysis and evaluation of the “Higuereta” roundabout was carried out, which is located in the district of Santiago de Surco, in the city of Lima in Peru. For this, a compilation of theoretical bases was carried out at an international level to know the fundamentals of geometric design. Thus, based on a deterministic mathematical model from the United Kingdom, Kimber 1980, which associates geometric parameters with circulating flow and shows that any change in a geometric design element is directly proportional to capacity, we can conclude that there are improvements. in service levels as long as we make significant variations in geometry. In the present investigation, improvements from a service level “F” to a “D” were evidenced. On the other hand, the roundabout was modeled from a micro simulation software, PTV Vissim 9, with the aim of being able to reflect through simulations the real traffic behavior before and after introducing changes in the geometric parameters. It was concluded that there are improvements in service levels per access, from a “D” to a “C. Finally, to be certain that the model reflected reality, it was calibrated through adjustments in the driver's behavior parameters and validated from a statistical indicator. / Tesis

The transportation sector is responsible for the majority of airborne particles and global energy consumption in urban areas. Its role in generating air pollution in urban areas is even more critical, as many visitors, commuters and citizens travel there daily for various reasons. Emissions released by transport fleets have an exhaust (tailpipe) and a non-exhaust (brake wears ) origin. Both exhaust and non-exhaust airborne particles can have destructive effects on the human cardiovascular and respiratory systems and even lead to premature deaths. This dissertation aims to estimate the amount of exhaust and brake emissions in a real case study by proposing an innovative methodology. For this purpose, different levels of study have been introduced, including the subsystem level, the system level, the environmental level and the suprasystem level. To address these levels, two approaches were proposed along with a data collection process. First, a comprehensive field survey was conducted in the area of Buonconsiglio Castle and data was collected on traffic and non-traffic during peak hours. Then, in the first approach, a state-of-the-art simulation-based method was presented to estimate the amount of exhaust emissions generated and the rate of fuel consumption in the case study using the VISSIM traffic microsimulation software and Enviver emission modeler at the suprasystem level. In order to calculate the results under different mobility conditions, a total of 18 scenarios were defined based on changes in vehicle speeds and the share of heavy vehicles (HV%) in the modal split. Subsequently, the scenarios were accurately modelled in the simulation software VISSIM and repeated 30 times with a simulation runtime of three hours. The results of the first approach confirmed the simultaneous effects of considering vehicle speed and HV % on fuel consumption and the amount of exhaust emissions generated. Furthermore, the sensitivity of exhaust emissions and fuel consumption to variations in vehicle speed was found to be much higher than HV %. In other words, the production of NOx and VOC emissions can be increased by up to 20 % by increasing the maximum speed of vehicles by 10 km/h. Conversely, increasing the HV percentage at the same speed does not seem to produce a significant change. Furthermore, increasing the speed from 30 km/h to 50 km/h increased CO emissions and fuel consumption by up to 33%. Similarly, a reduction in speed of 20 or 10 km/h with a 100% increase in HV resulted in a 40% and 27% decrease in exhaust emissions per seat, respectively. In the second approach, a novel methodology was proposed to estimate the number of brake particles in the case study. To achieve this goal, a downstream approach was proposed starting from the suprasystem level (microscopic traffic simulation models in VISSIM) and using a developed mathematical vehicle dynamics model at the system level to calculate the braking torques and angular velocities of the front and rear wheels, and proposes an artificial neural network (ANN) as a brake emission model, which has been appropriately trained and validated using emission data collected through more than 1000 experimental tribological tests on a reduced-scale dynamometer at the subsystem level (braking system). Consideration of this multi-level approach, from tribological to traffic-related aspects, is necessary for a realistic estimation of brake emissions. The proposed method was implemented on a targeted vehicle, a dominant SUV family car in the case study, considering real driving conditions. The relevant dynamic quantities of the targeted vehicle (braking torques and angular velocities of the wheels) were calculated based on the vehicle trajectory data such as speed and deceleration obtained from the traffic microsimulation models and converted into braking emissions via the artificial neural network. The total number of brake emissions emitted by the targeted vehicles was predicted for 10 iterations route by route and for the entire traffic network. The results showed that a large number of brake particles (in the order of billions of particles) are released by the targeted vehicles, which significantly affect the air quality in the case study. The results of this dissertation provide important information for policy makers to gain better insight into the rate of exhaust and brake emissions and fuel consumption in metropolitan areas and to understand their acute negative impacts on the health of citizens and commuters.