title: Safety analysis of urban signalized intersections under mixed traffic.
abstract: BACKGROUND
  This study examined the crash causative factors of signalized intersections under mixed traffic using advanced statistical models.
  
  
  METHODS
  Hierarchical Poisson regression and logistic regression models were developed to predict the crash frequency and severity of signalized intersection approaches. The prediction models helped to develop general safety countermeasures for signalized intersections.
  
  
  RESULTS
  The study shows that exclusive left turn lanes and countdown timers are beneficial for improving the safety of signalized intersections. Safety is also influenced by the presence of a surveillance camera, green time, median width, traffic volume, and proportion of two wheelers in the traffic stream. The factors that influence the severity of crashes were also identified in this study.
  
  
  CONCLUSIONS
  As a practical application, the safe values of deviation of green time provided from design green time, with varying traffic volume, is presented in this study. This is a useful tool for setting the appropriate green time for a signalized intersection approach with variations in the traffic volume.
authors: Department of Civil Engineering, National Institute of Technology Calicut, Kerala, India. Electronic address: anjana.sai.09@gmail.com.
authors: Anjana
authors: A
authors: S
authors: Department of Civil Engineering, National Institute of Technology Calicut, Kerala, India.
authors: Anjaneyulu
authors: A
authors: M V L R
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D004779:Environment Design / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D015233:Models, Statistical; D012449:Safety; D014505:Urban Population
keywords: Crash frequency prediction; Crash severity prediction; Hierarchical structure; Signal control