جستجوی مقالات مرتبط با کلیدواژه "لوجیت ترتیبی" در نشریات گروه "عمران"

Fatality, injury, disability, and medical expense, road and vehicle damage, and mental aspects are the main disadvantages of crashes in a community. This study tries to find the influential factors, which are predictable on the severity of crashes in the rural highway using the descriptive logit model family. First, crash data are integrated with traffic data obtained from loop detectors in rural road. Second, the Ordered logit (OL) and Multinomial logit (MNL) models are developed to identify the influential factors on crash severity. Third, the models are evaluated in terms of goodness of fit. They are applied for the short-term prediction of crash severity on rural road network in Khorasan Razavi, one of the most populated province in the northeast of Iran. Results show that the overall goodness of fit for both OL and MNL models are 0.017 and 0.019, respectively that expectedly indicates the MNL model is more accurate. The independent traffic variables "heavy vehicle flow" and "speed above 85 km/h" are significant in the suggested OL model. In the MNL model, the independent variable "minimum headway" is also significant for accidents with serious damage, in addition to the significant variables "heavy vehicle flow" and "speed above 85 km/h" for the severity levels of injury and fatality.

Nowadays traffic congestion in metropolitan areas like Tehran has become a critical issue requiring transportation demand management policies as solutions to reduce demand and maximize facilities efficiency. An effective transportation management measure is congestion pricing, which needs special attention to be performed successfully because of its low public acceptance. In this study, based on the data gathered from 455 face-to-face questionnaires through a surveys conducted at restricted traffic areas of Tehran in 2018, we analyze latent factors affecting acceptance of Tehran peak-based scheme. Exploratory factor analysis and ordinal logit models are used for our purpose. Results show that attitudinal factors like perceived effectiveness of the scheme, officials’ performance, scheme design and the way it is performed and environmental concerns besides some socioeconomic factors like education, car ownership and travel patterns are among the most effective items. Results also show that congestion pricing acceptability among people with more information about this program is more, and less for regular users of restricted traffic areas. This research can assist transportation decision makers in taking appropriate measures and policies with maximum acceptance level.