Reducing the effect of local conditions on the capacity intersection approaches with the support of intelligent transportation identification software

• Autores: Figueroa Tejada, Gisella, Sotil, Andrés, Un Jan, Alberto
• Formato: objeto de conferencia
• Fecha de Publicación: 2017
• Institución: Universidad San Ignacio de Loyola
• Repositorio: USIL-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.usil.edu.pe:usil/2897
• Enlace del recurso: https://repositorio.usil.edu.pe/handle/usil/2897
• Nivel de acceso: acceso abierto
• Materia: Transportation routes; Mass transportation; Highway engineering; Traffic congestion

Public transportation in Peru was regulated in the mid-90's to encourage improvements in service, routes and quantities of vehicles. Since then, contrary to what was expected, traffic jams, accidents, and overall poor levels of service are encountered in expressways, avenues and intersections alike. Mismanagement, lack of knowledge, political interests and even constitutional restrictions do not help improving the current conditions (Quistberg, Koepsell, Boyle, Miranda, Johnston and Ebel, 2014). Within this context, this paper focuses on conditions at intersections that can be improved if proper organization is provided. Saturation and capacity of intersections approaches are governed by equations by factors. The Highway Capacity Manual HCM (Transportation Research Board TRB, 2010) explains these factors, like grade, bus blocking, parking maneuvers, right and left turns, pedestrian and bicycle activity, number of lanes, presence of heavy vehicles, and other similar factors. The purpose of this paper is to identify such conditions, rank them, and provide solutions (which may include traffic sanctions/tickets) to reduce their effect on the capacity of intersection approaches. The paper will apply Systems Dynamics. With the support of intelligent transportation solution will provide the foundations of the "E-Lean Traffic" concept based on the application on System Dynamics approach, the use of Internet of Things technology and methodologies as "Lean Manufacturing" in Industrial Engineering and "Lean Construction" in Civil Engineering.