Although concepts of the XDL intersection or CFI (Continuous Flow Intersection) have been around for approximately four decades, users do not yet have a simplified procedure to evaluate its traffic performance and compare it with a conventional intersection. Several studies have shown qualitative and quantitative benefits of the XDL intersection without providing accessible tools for traffic engineers and planners to estimate average control delays, and queues. Modeling was conducted on typical geometries over a wide distribution of traffic flow conditions for three different design configurations or cases using VISSIM simulations with pre-timed signal settings. Some comparisons with similar conventional designs show considerable savings in average control delay, and average queue length and increase in intersection capacity. The statistical models provide an accessible tool for a practitioner to assess average delay and average queue length for three types of XDL intersections. Pre-timed signal controller settings are provided for each of the five intersections of the XDL network. In this research, a "real-time" traffic signal control strategy is developed using genetic algorithms and neural networks to provide near-optimal traffic performance for XDL intersections. Knowing the traffic arrival pattern at an intersection in advance, it is possible to come up with the best signal control strategy for the respective scenario. Hypothetical cases of traffic arrival patterns are generated and genetic algorithms are used to come up with near-optimal signal control strategy for the respective cases. The neural network controller is then trained and tested using pairs of hypothetical traffic scenarios and corresponding signal control strategies. The developed neural network controller produces near-optimal traffic signal control strategy in "real-time" for all varieties of traffic arrival patterns. / Master of Science

Las ciudades altamente congestionadas requieren de una óptima gestión de la movilidad urbana. Muchas de estas ciudades se caracterizan porque su infraestructura vial no va acorde con su demanda vehicular, como es el caso de la ciudad de Lima. Por consiguiente, se debe priorizar el desarrollo de la infraestructura vial, ya que existen por ejemplo intersecciones amplias que presentan gran cantidad de puntos de conflicto. En efecto, reducen la capacidad operacional y el nivel de servicio de la intersección. Esta investigación tiene como objetivo reducir los puntos de conflicto y el tiempo de cruce en intersecciones amplias tipo cruz, en base a la Metodología de Flujo Continuo (CFI, por sus siglas en inglés) con delineadores elevados (bolardos compuestos) y detectores (sensores) a fin de mejorar la capacidad y seguridad operacional de la intersección. El objeto de estudio de la presente investigación se encuentra en una zona comercial ubicada entre la Avenida República de Venezuela con la Avenida Aurelio García y García, Lima. Los movimientos vehiculares de giro a la izquierda son los que afectan el rendimiento de las intersecciones señalizadas. Por tanto, se recolectaron 3219 vehículos en total, de los cuales 561 vehículos giraron a la izquierda demostrando así la alta densidad de este tipo de maniobras. La efectividad del diseño propuesto se valida empleando una microsimulación en el software Vissim. Los resultados obtenidos muestran los puntos de conflictos tipo cruz se redujeron a 8 puntos con el modelo propuesto frente al estado actual, el cual posee 58 puntos de conflictos tipo cruz. Por otro lado, el tiempo promedio de cruce de los vehículos disminuyó en 4.20 y 9.79 segundos en la fase 1, debido al rediseño de la geometría de la intersección. En efecto, la capacidad operacional aumentó en 33.85%, ya que el aforo vehicular con el nuevo ciclo semafórico de 150 segundos es de 431vehículos con respecto a los 322 vehículos que se tenía con el modelo anterior. Finalmente, los riesgos de colisiones posteriores y laterales se reducen mediante el uso de delineadores elevados en un 83%. / Highly congested cities require optimal management of urban mobility. Many of these cities are characterized because their road infrastructure does not match their vehicular demand, as is the case in the city of Lima. Therefore, the development of road infrastructure should be prioritized, since there are, for example, wide intersections that present a large number of conflict points. In effect, they reduce the operational capacity and service level of the intersection. This research aims to reduce conflict points and crossing time at wide cross-type intersections, based on the Continuous Flow Methodology (CFI) with elevated eyeliners (composite bollards) and detectors (sensors) in order to improve the capacity and safety of the intersection. The object of study of the present investigation is in a commercial area located between avenue Republica de Venezuela with avenue Aurelio Garcia y Garcia, Lima. The left-turn vehicular movements are those that affect the performance of the signposted intersections. Therefore, 3219 vehicles were collected in total, of which 561 vehicles turned left demonstrating the high density of this type of maneuver. The effectiveness of the proposed design is validated using microsimulation in the Vissim software. The results obtained show the points of cross-type conflicts were reduced to 8 points with the proposed model compared to the current state, which has 58 points of cross-type conflicts. On the other hand, the average crossing time of the vehicles decreased by 4.20 and 9.79 seconds in phase 1, due to the redesign of the intersection geometry. In fact, the operational capacity increased by 33.85%, since the vehicle capacity with the new traffic light cycle of 150 seconds is 431 vehicles with respect to the 322 vehicles that had the previous model. Finally, the risks of posterior and lateral collisions are reduced by the use of elevated eyeliners by 83%. / Tesis