Modeling and Application of Pedestrian Safety Conflict Index at Signalized Intersections

Quasi-induced Exposure Method for Pedestrian Safety at Signalized Intersections

To investigate pedestrian exposure when only pedestrian-crash data are available, the quasi-induced exposure method is used to identify the factors that contributed to pedestrian-vehicle crashes in Las Vegas from 2004 to 2008. The results show that overall crash severity, light conditions and weather conditions are potentially risky factors in pedestrian crashes, and the time of day or day of t...

Estimating Pedestrian Volumes and Crashes at Urban Signalized Intersections

Crash prediction models are used to estimate the number of crashes using a set of explanatory variables. The highway safety community has used modeling techniques to predict vehicle-to-vehicle crashes for decades. Specifically, generalized linear models (GLMs) are commonly used because they can model non-linear count data such as motor vehicle crashes. Regression models such as the Poisson, Zer...

Video-Based Monitoring of Pedestrian Movements at Signalized Intersections

Pedestrian and cyclist crossing characteristics are important for the design of urban intersections and signalized crossings. Parameters, such as waiting time, crossing time, and arrival rate are key variables for describing pedestrian characteristics and improving crossing design and signal timing plan. Manually collecting such data is often extremely labor intensive. Therefore, we introduce a...

Pedestrian sensing for increased traffic safety and efficiency at signalized intersections

Aggressiveness propensity index for driving behavior at signalized intersections.

The development of a quantitative intersection aggressiveness propensity index (API) is described in this paper. The index is intended to capture the overall propensity for aggressive driving to be experienced at a given signalized intersection. The index is a latent quantity that can be estimated from observed environmental, situational and driving behavior variables using structural equations...