Mobility Compass

Abstract

Inappropriate speeds are key factors that may affect the occurrence and the severity of road crashes. Although rural roads are influenced by more severe crashes than urban roads, perhaps due to the higher vehicular speeds, the latter suffer from a higher frequency of crashes. Therefore, exploring factors affecting the vehicular speed in the urban area is crucial. The literature provided several models to usually estimate the operating speed (i.e., V85) in rural roads. However, further investigations are needed to provide these estimations in the urban areas. In addition, these models often estimate the 85th percentile of the speed distribution, that cannot represent the entire distribution. Therefore, the problem of the speed prediction distribution is also a challenge in urban roads. This paper addresses this challenge by exploring the effects of some road factors on the vehicular speed along segments of urban roads. First, this speed is modelled as a random variable with a normal distribution. Next, by using 11,466 car spot speed data collected along a portion of the urban road network of city of Brescia (Italy), two multiple linear regression models were run for the estimation of the speed mean and the related standard deviation, respectively. Preliminary results showed that the presence of median, the bus stop density, the presence of curb and the type of adjacent land are significant predictors of the vehicular speed distribution on urban roads. These results may support road management agencies to set proper actions on speed management, especially for existing roads and/or critical section roads in urban areas.

Topics

• crash
• automobile
• city
• data
• density
• bus
• urban road
• forecasting
• road network
• linear regression analysis
• curb
• standard deviation
• speed control
• speed distribution
• speed data
• bus stop
• operating speed
• random variable
• spot speed
• normal distribution

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