Segment videos were produced at different peaks to reflect different sampling criteria like land use characteristics, trails, Ciclocarrils and Ciclovia. Each segment was filmed for 20–40 seconds during bicycle rides at a speed of about 5km/h with a camera strapped, at an angle of 45 degrees, on the head. Curb lane variables such as bicycle pathway widths, curb lane motorised volume (veh/h) and vehicle speed (km/h), bicycle volume on segment, and median width were recorded in addition to secondary data. About 1,360 ratings were acquired from study participants and used in the estimation process. Ordered probability models were used to estimate random parameters of cyclists LOS perception to account for unobserved heterogeneity for all respondents. The deviance (1.085) and Pearson Chi-Square (2.309) with 1,635 degree of freedom at 0.05 level of significance shows that our model provides a better fit of the data. The study observed that BLOS was strongly influenced by side path separation, vehicle speed, motorised traffic volume and conflicts with pedestrians. However, many other factors were found to have high probabilities to influence level of service with unit change. They include bicycle lane width, wide outside lane, pavement conditions, trees and benches, daylight, gender and experience of cyclist. The impact of the variety of observed factors affecting bicyclists reveal the nature and character of urban transportation in Bogota which suggests a range of important trade-offs in further planning and management of the Cicloruta bicycle paths.
La pandemia del COVID-19 y las medidas preventivas que se adoptaron han tenido un amplio abanico de consecuencias que trascienden los problemas de salud para la población de muchas ciudades del mundo. Con el propósito de entender por qué los impactos en la vida de los habitantes resultaron tan diferentes dentro de la ciudad, nos interesamos en las vulnerabilidades socio-espaciales preexistentes, tomando como ejemplo las metrópolis de Lima y Bogotá. Indagamos por la relación entre estructura urbana, patrones de movilidad cotidiana y efectos del COVID-19 durante las cuarentenas del 2020. Adoptamos para ello un enfoque multidimensional que se sustenta en datos censales, en las últimas encuestas origen-destino disponibles y en los niveles de contagio en ambas ciudades durante el 2020. Con base en un análisis factorial y un análisis de conglomerado, proponemos una tipología y un mapa sintético de los factores de vulnerabilidad preexistentes. Los resultados permiten entender el rol de estos factores en las dificultades que tuvieron los habitantes para enfrentar la cuarentena, así como la razón por la cual aquellos que moran en los barrios periféricos de bajos ingresos sufrieron las peores alteraciones en su cotidianidad.
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