Showing papers in "Accident Analysis & Prevention in 2013"

TL;DR: A modified version of the Human Factors Analysis and Classification System, which has been adapted to the maritime context and used to analyse human and organisational factors in collisions reported by the Marine Accident and Investigation Branch (UK) and the Transportation Safety Board (Canada) is presented.

TL;DR: It was found that mobile-phone related injuries among pedestrians increased relative to total pedestrian injuries, and paralleled the increase in injuries for drivers, and in 2010 exceeded those for drivers.

TL;DR: Several other factors were found to significantly increase the probability of fatal injury for drivers in single-vehicle crashes, most notably: male driver, drunk driving, unsafe speed, older driver (65+) driving an older vehicle, and darkness without streetlights.

TL;DR: There was a tendency for the estimated effects of drug use on accident risk to be smaller in well-controlled studies than in poorly controlled studies, and evidence of publication bias was found for some drugs.

TL;DR: Analysis of traffic accident data for the period 2006-2010 in Guangdong Province, China will shed lights on the development of similar (adjusted) measures to reduce traffic violations and/or accident fatalities and injuries, and to promote road safety in other regions.

TL;DR: Support vector machine (SVM), a recently proposed statistical learning model was introduced to evaluate real-time crash risk and results indicate that smaller sample size would enhance the SVM model's classification accuracy and explanatory variables have identical effects on crash occurrence for the S VM models and logistic regression models.

TL;DR: In-depth data from the Australian National Crash In-depth Study indicates that a majority of serious injury crashes involve driver inattention, and most forms of inatt attention and distraction observed are preventable.

TL;DR: Bayesian Networks (BNs) are used to identify the main factors involved in accident severity for both, the entire database (EDB) and the clusters previously obtained by LCC and the results show that the combined use of both techniques is very interesting as it reveals further information that would not have been obtained without prior segmentation of the data.

TL;DR: A two-stage calibration procedure to calibrate and validate the VISSIM simulation models improved the goodness-of-fit between the simulated conflicts and the real-world conflicts and was found to be successful.

TL;DR: It is concluded that crash and near-crash risk for individual drivers is associated with critical incident rate, demographic, and personality characteristics, and thecritical incident rate is an effective predictor for high-risk drivers.

TL;DR: Findings are consistent with previous results obtained for France using a similar approach, with the exception of the negative correlation between precipitation and the number of injury accidents found for the Athens region, which is further investigated.

TL;DR: In this paper, the authors used a logistic regression model to estimate the risk of severe injury or death for pedestrians struck by vehicles using data from a study of crashes that occurred in the United States in years 1994-1998 and involved a pedestrian struck by a forward-moving car, light truck, van, or sport utility vehicle.

TL;DR: The research findings indicated that steering wheel variability provides a basis for developing a cost-effective and easy-to-install alternative technology for in-vehicle driver drowsiness detection at moderate levels of fatigue.

TL;DR: Driving simulator performance was more impaired in the THC and alcohol combined conditions, and regular cannabis users displayed more driving errors than non-regular cannabis users.

TL;DR: Results suggest greater mixing of residences and commercial land uses is associated with higher pedestrian crash risk across different severity levels, ceteris paribus, presumably since such access produces more potential conflicts between pedestrian and vehicle movements and Interestingly, network densities show variable effects, and sidewalk provision isassociated with lower severe-crash rates.

TL;DR: This study suggests that the research-practice gap should be closed and efforts to bridge the gap should focus on ensuring that systemic methods meet the needs of practitioners and improving the communication of SAA research.

TL;DR: An analysis leading to a re-parameterisation of the Power Model in terms of continuously varying exponents which depend on initial speed, which implies that the effect on accidents of a given relative change in speed is largest when initial speed is highest.

TL;DR: A procedure which evaluates clusters of traffic accident and organizes them according to their significance and introduced the cluster strength and cluster stability evaluation procedures was applied in the Southern Moravia Region of the Czech Republic.

TL;DR: In this paper, the authors compared the performance of different discrete outcome frameworks for modeling driver injury severity in traffic crashes, including the generalized ordered logit (GOL), the unordered response framework (URCF), the multinomial logit framework (MNL), the nested logit model (NL), and the MMNL model.

TL;DR: Random parameter logit models for explaining pedestrian injury severity levels of New York City accounting for unobserved heterogeneity in the population and across the boroughs are developed.

TL;DR: The findings of this study can be used to predict the probabilities of crash at different severity levels, which is valuable knowledge in the pursuit of reducing the risk of severe crashes through the use of dynamic safety management systems on freeways.

TL;DR: The results indicate that the weather condition variables, especially precipitation, play a key role in the crash occurrence models and imply that different active traffic management strategies should be designed based on seasons.

TL;DR: Pedestrian behavior was influenced, and generally considerably riskier, when participants were simultaneously using mobile Internet and crossing the street than when crossed the street with no distraction, reinforcing the need for increased awareness concerning the risks of distracted pedestrian behavior.

TL;DR: The results indicate that distracted driving, particularly texting, may lead to reduced safety and traffic flow, thus having a negative impact on traffic operations.

TL;DR: The results of this study are useful for traffic incident management agencies to implement strategies to reduce incident duration, leading to reduced congestion, secondary incidents, and the associated human and economic losses.

TL;DR: The results suggest that in general there was a significant improvement in log-likelihood when using RPNB compared to a fixed parameter negative binomial baseline model, and show that road segment-specific insights into crash frequency occurrence can lead to improved design policy and project prioritization.

TL;DR: The findings suggest that the primary cause of the incident was a looked-but-failed-to-see error driven by a faulty activation of schema error, leading the truck driver to assume initially that the crossing was in fact in a non-activated state with no train present.

TL;DR: The results of a structural equation analysis indicated that job demands and job resources could affect emotional exhaustion and safety compliance, and thus influence the occurrence of injuries and near-misses.

TL;DR: The results indicate that drug use is associated with a significantly increased risk of fatal crash involvement, particularly when used in combination with alcohol.

TL;DR: It was concluded that the relative validity of simulators is acceptable for many variables, but that in absolute terms simulators cause higher sleepiness levels than real driving.