This study adopted the Highway Safety Information System’s (HSIS) data for crashes occurred on road segments to develop supervised machine learning prediction models. Five models are developed: Linear Regression (LR), Generalize Additive Model (GAM), Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN). A comparison among five model was performed using root mean...

1 2 A major focus for transportation safety analysts is the development of crash prediction models, a 3 task for which an extremely wide selection of model types are available. Perhaps the most common 4 crash prediction model is the negative binomial (NB) regression model. The NB model gained 5 popularity due to its relative ease of implementation and its ability to handle overdispersion in 6 c...

Any reader of the paper by Laloux et al. [1] would have been left utterly confused after consulting the time series for the price of Japanese Government Bonds (JGB) around May 1995 looking for a log-periodic power law acceleration in the data. The authors of [1] now confess their error and admit that the prediction date given in [1] was incorrect and that the correct prediction was for August 1...

The aim of the present study was to evaluate mortality and functional outcome in old and very old patients with severe traumatic brain injury (TBI) and compare to the predicted outcome according to the internet based CRASH (Corticosteroid Randomization After Significant Head injury) model based prediction, from the Medical Research Council (MRC). Methods. Prospective, national multicenter study...

road traffic crashes (rtcs) account for great mortality and morbidity rates worldwide, resulting in substantial global burden. factors contributing to rtc generally fall into three categories: environmental, vehicle, and human, with the human factor being by far the leading determinant. obtaining an in-depth exploration of driving behavior and factors underpinning risky driving could be of part...

Johansen and Sornette proposes that the crash has fundamentally an endogenous origin and exogenous shocks only serve as triggering factors. This endogenous force is shown in price as power law log-periodicity (PLLP) signature prior to a crash. We estimate the highly nonlinear model developed by them using a hybrid approach which combines scatter search, genetic adaptor and tabu search. The mode...

Current procedures for estimating occupant risk in real-world vehicle crashes do not account for the performance of the occupant restraints, such as seatbelts and airbags. This paper compares the ability of two restraint performance metrics, the ridedown efficiency and the restraint quotient, to predict occupant injury as measured by a crash test dummy. The responses of crash test dummies were ...

This study investigates the relationship between occupant injury and a host of other factors, including traffic and weather conditions present at the time of crash, road design, vehicle type, and occupant characteristics. Crash and traffic-detector data from six Orange County freeways were used in an ordered probit model. Crash outcomes were classified for each occupant, as no injury, non-visib...