the highway safety manual [hsm, 2010] recommends safety evaluations be performed beforeimplementing any roadway treatment to predict the expected safety consequences. safety consequences canbe measured using crash prediction models, crash modification factor (cmfs), or both. this paperdevelops a cmf to show the expected impact of red-light cameras (rlcs) on safety at signalizedintersections. a ...

Advances in safety research--trying to improve the collective understanding of motor vehicle crash causes and contributing factors--rest upon the pursuit of numerous lines of research inquiry. The research community has focused considerable attention on analytical methods development (negative binomial models, simultaneous equations, etc.), on better experimental designs (before-after studies, ...

Stock price crash risk is a phenomenon in which stock prices are subject to severe negative and sudden adjustments. So far, different approaches have been proposed to model and predict  the  stock price crash risk, which in most cases have been the main emphasis on the factors affecting it, and often traditional methods have been used for prediction. On the other hand, using  Meta Heuristic Alg...

Every year nearly 1.5 million people are dying in traffic collisions around the world, due to unexpected behavior of pedestrians while crossing road. To address this problem an augmentation function for predicting crash risk active pedestrian is proposed. The has several functions like pre-crash scenario, vehicle trajectory, and trajectory. In a Pre-Crash movement such as entering road boundary...

The rapid increase in traffic volume on urban roads, over time, has altered the global scenario. Additionally, it increased number of road crashes, some which are severe and fatal nature. identification hazardous roadway sections using spatial pattern analysis crashes recognition primary contributing factors may assist reducing severity (R.T.C.s). For crash prediction, along with patterns, vari...

Data mining is the analysis of large "observational" datasets to find unsuspected relationships that might be useful to the data owner. It typically involves analysis where objectives of the mining exercise have no bearing on the data collection strategy. Freeway traffic surveillance data collected through underground loop detectors is one such "observational" database maintained for various IT...