La tesis titulada “Influencia de la Construcción del Puente Arequipa en los Niveles de Servicio de las Intersecciones de la Calle Real con Jr. Ayacucho y la Calle Real con Jr. Santa Rosa”; consistió en analizar y determinar los NdS, para todas las intersecciones influenciadas, que a continuación se detallaran: Calle Real con Jr. Ayacucho (X1), Calle Real con Jr. Santa Rosa (X2), Jr. Arequipa con Jr. Santa Rosa (X3) y Jr. Arequipa con Jr. Ayacucho (X4). El Puente Arequipa se convertirá en un tramo alternativo, para todo vehículo cercano y también lejano.

La presente tesis propone una solución a la congestión vehicular a través de una microsimulación con el software Vissim v9 de la rotonda Las Américas ubicada frente al Aeropuerto Internacional Jorge Chávez. La microsimulación se realizó mediante los parámetros de Wiedemann, los cuales fueron utilizados en la calibración y validación del modelo haciéndolo lo más cercano a la realidad considerando la geometría del área de estudio y la Psicología de los conductores. En el primer capítulo se encontrará el problema de la congestión vehicular en Perú y Lima, algunos antecedentes de estudios similares, la hipótesis y los objetivos de la investigación. En el segundo capítulo se desarrolló el marco teórico que respalda los criterios con los que se ha desarrollado tanto el modelo de microsimulación como la propuesta de mejora. Aquí podremos encontrar la definición de los diferentes tipos de modelos, los fundamentos de la microsimulación (modelo de Wiedemann) y se explica el análisis que ejecuta el software Vissim v9. El tercer capítulo describe la metodología que se utiliza desde la recolección de datos de campo hasta el modelo de microsimulación debidamente calibrado y validado. En el cuarto capítulo se presentan los resultados de la microsimulación, los cuales nos indican el nivel de servicio actual de la rotonda es “F” y se logró mejorar hasta uno “D”, según la HCM (2010). En el último capítulo se encontrarán las conclusiones y recomendaciones a las que se llegaron respondiendo así el objetivo general de la presente tesis. / This thesis proposes a solution to vehicular congestion through microsimulation with the Vissim v9 software of the Las Americas roundabout located opposite the Jorge Chavez International Airport. Microsimulation was performed using Wiedemann parameters, which were used in the calibration and validation of the model making it as close to reality considering the geometry of the study area and the Psychology of the drivers. In the first chapter you will find the problem of vehicular congestion in Peru and Lima, some background of similar studies, the hypothesis and the objectives of the investigation. In the second chapter the theoretical framework was developed that supports the criteria with which both the microsimulation model and the proposal for improvement have been developed. Here we can find the definition of the different types of models, the fundamentals of microsimulation (Wiedemann model) and the analysis that runs the Vissim v9 software is explained. The third chapter describes the methodology used from the collection of field data to the properly calibrated and validated microsimulation model. In the fourth chapter the results of the microsimulation are presented, which indicate the current service level of the roundabout is “F” and it was possible to improve up to one “D”, according to the HCM (2010). In the last chapter you will find the conclusions and recommendations reached in response to the general objective of this thesis. / Tesis

No description available.

Automatic Vehicles is a possible future, but it does not mean that we should forget about improving the present day to day life. Most vehicles have Cruise Control, and few have Adaptive Cruise Control, but very few have Cooperative Adaptive Cruise Control(CACC) because it's an integration of software and hardware as different companies produce different vehicles it's hard to get on common ground. CACC at the core is communication among vehicles and sharing information; in this thesis, I tried to make it usable in any car with just the software used in a smartphone. As everybody has a phone in their hand with an inbuilt GPS, it is easier to use it directly rather than have a unique mechanical device embedded with a software application. My application gives the estimated speed usable at a particular time based on the other two vehicles, and it keeps changing based on other cars. It does not depend on any external sensors; hence, no environmental change can affect the data give by my vehicle. This application is a guide that could be used in the snow, rain, or hail when even eyes or technology cannot help. Location and speed are something, and using them and providing safety is my thesis all about.

<p>The number of automobiles has been increased on the road in the past few years. Due to high density of vehicles, the potential threats and road accident is increasing. Wireless technology is aiming to equip technology in vehicles to reduce these factors by sending messages to each other.</p><p>The vehicular safety application should be thoroughly tested before it is deployed in a real world to use. Simulator tool has been preferred over out door experiment because it simple, easy and cheap. VANET requires that a traffic and network simulator should be used together to perform this test. Many tools exist for this purpose but most of them have the problem with the proper interaction. In this thesis, we aim at simulating vehicular networks with external stimulus to analyze its effect on wireless communication but to do this job a good simulator is also needed. So we will first debate on the shortcoming of current simulators and come up with our own recommendations to perform our simulation.</p>

The number of automobiles has been increased on the road in the past few years. Due to high density of vehicles, the potential threats and road accident is increasing. Wireless technology is aiming to equip technology in vehicles to reduce these factors by sending messages to each other. The vehicular safety application should be thoroughly tested before it is deployed in a real world to use. Simulator tool has been preferred over out door experiment because it simple, easy and cheap. VANET requires that a traffic and network simulator should be used together to perform this test. Many tools exist for this purpose but most of them have the problem with the proper interaction. In this thesis, we aim at simulating vehicular networks with external stimulus to analyze its effect on wireless communication but to do this job a good simulator is also needed. So we will first debate on the shortcoming of current simulators and come up with our own recommendations to perform our simulation.

No description available.

Fotografía ganadora del Segundo puesto en el "IV Concurso de fotografía para lectores UPC", llevado a cabo el 25 de octubre de 2019. El evento fue organizado por el Centro de Información - Sede San Miguel. Lima, Perú.

Vehicular networks are a promising technology to help solve complex problems of modern society, such as urban mobility. However, the vehicular environment has some characteristics that pose challenges for wireless communication in vehicular networks not usually found in traditional networks. Therefore, the scientific community is yet investigating alternative techniques to improve data delivery in vehicular networks. In this context, the recent and increasing availability of trajectory data offers us valuable information in many research areas. These data comprise the so-called "big trajectory data" and represent a new opportunity for improving vehicular networks. However, there is a lack of specific data mining techniques to extract the hidden knowledge from these data. This thesis explores vehicle trajectory data mining to design intelligent vehicular networks. In the first part of this thesis, we deal with errors intrinsic to vehicle trajectory data that hinder their applicability. We propose a trajectory reconstruction framework composed of several preprocessing techniques to convert flawed GPS-based data to road-network constrained trajectories. This new data representation reduces trajectory uncertainty and removes problems such as noise and outliers compared to raw GPS trajectories. After that, we develop a novel and scalable cluster-based trajectory prediction framework that uses enhanced big trajectory data. Besides the prediction framework, we propose a new hierarchical agglomerative clustering algorithm for road-network constrained trajectories that automatically detects the most appropriate number of clusters. The proposed clustering algorithm is one of the components that allow the prediction framework to process large-scale datasets. The second part of this thesis applies the enhanced trajectory representation and the prediction framework to improve the vehicular network. We propose the VDDTP algorithm, a novel vehicle-assisted data delivery algorithm based on trajectory prediction. VDDTP creates an extended trajectory model and uses predicted road-network constrained trajectories to calculate packet delivery probabilities. Then, it applies the predicted trajectories and some proposed heuristics in a data forwarding strategy, aiming to improve the vehicular network's global metrics (i.e., delivery ratio, communication overhead, and delivery delay). In this part, we also propose the DisTraC protocol to demonstrate the applicability of vehicular networks to detect traffic congestion and improve urban mobility. DisTraC uses V2V communication to measure road congestion levels cooperatively and reroute vehicles to reduce travel time. We evaluate the proposed solutions through extensive experiments and simulations. For that, we prepare a new large-scale and real-world dataset based on the city of Rio de Janeiro, Brazil. We also use other real-world datasets publicly available. The results demonstrate the potential of the proposed data mining techniques (i.e., trajectory reconstruction and prediction frameworks) and vehicular networks algorithms.

Vehicular edge computing (VEC) brings the cloud paradigm to the edge of the network, allowing nodes such as Roadside Units (RSUs) and On-Board Units (OBUs) in vehicles to perform services with location awareness and low delay requirements. Furthermore, it alleviates the bandwidth congestion caused by the large amount of data requests in the network. One of the major components of VEC, computation offloading, has gained increasing attention with the emergence of mobile and vehicular applications with high-computing and low-latency demands, such as Intelligent Transportation Systems and IoT-based applications. However, existing challenges need to be addressed for vehicles' resources to be used in an efficient manner. The primary challenge consists of the mobility of the vehicles, followed by intermittent or lack of connectivity. Therefore, the MPR (Mobility Prediction Retrieval) data retrieval protocol proposed in this work allows VEC to efficiently retrieve the output processed data of the offloaded application by using both vehicles and road side units as communication nodes. The developed protocol uses geo-location information of the network infrastructure and the users to accomplish an efficient data retrieval in a Vehicular Edge Computing environment. Moreover, the proposed MPR Protocol relies on both Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication to achieve a reliable retrieval of data, giving it a higher retrieval rate than methods that use V2I or V2V only. Finally, the experiments performed show the proposed protocol to achieve a more reliable data retrieval with lower communication delay when compared to related techniques.