Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway.

Detecting high-collision-concentration locations based solely on collision frequency may produce different results compared to those considering the severities of the collisions. In particular, it can lead government agencies focusing sites with a high collision frequency while neglecting those with a lower collision frequency but a higher percentage of injury and fatal collisions. This study developed systematic ways of detecting reproducible fatal collision locations (R) using the naïve Bayes approach and a continuous risk profile (CRP) that estimates the true collision risk by filtering out random noise in the data.

Spatiotemporal filtering method for detecting kinematic waves in a connected environment.

Backward-moving kinematic waves (KWs) (e.g., stop-and-go traffic conditions and a shock wave) cause unsafe driving conditions, decreases in the capacities of freeways, and increased travel time.

An optimal network screening method of hotspot identification for highway crashes with dynamic site length.

We propose a novel network screening method for hotspot (i.e., sites that suffer from high collision concentration and have high potential for safety improvement) identification based on the optimization framework to maximize the total summation of a selected safety measure for all hotspots considering a resource constraint for conducting detailed engineering studies (DES).

Evaluating and addressing the effects of regression to the mean phenomenon in estimating collision frequencies on urban high collision concentration locations.

Two different methods for addressing the regression to the mean phenomenon (RTM) were evaluated using empirical data: Data from 110 miles of freeway located in California were used to evaluate the performance of the EB and CRP methods in addressing RTM. CRP outperformed the EB method in estimating collision frequencies in selected high collision concentration locations (HCCLs). Findings indicate that the performance of the EB method can be markedly affected when SPF is biased, while the performance of CRP remains much less affected.

Denoising traffic collision data using ensemble empirical mode decomposition (EEMD) and its application for constructing continuous risk profile (CRP).

Filtering out the noise in traffic collision data is essential in reducing false positive rates (i.e., requiring safety investigation of sites where it is not needed) and can assist government agencies in better allocating limited resources.

Surrogate safety measure for evaluating rear-end collision risk related to kinematic waves near freeway recurrent bottlenecks.

This study presents a surrogate safety measure for evaluating the rear-end collision risk related to kinematic waves near freeway recurrent bottlenecks using aggregated traffic data from ordinary loop detectors. The attributes of kinematic waves that accompany rear-end collisions and the traffic conditions at detector stations spanning the collision locations were examined to develop the rear-end collision risk index (RCRI). Together with RCRI, standard deviations in occupancy were used to develop a logistic regression model for estimating rear-end collision likelihood near freeway recurrent bottlenecks in real-time.

Evaluating the performance of network screening methods for detecting high collision concentration locations on highways.

This paper documents findings from evaluating performances of three different methods for segmenting freeway sites for the purpose of identifying high collision concentration locations: Sliding Moving Window (SMW), Peak Searching (PS) and Continuous Risk Profile (CRP). The traffic collision data from sites segmented in each method under two different roadway definitions were used to estimate excess expected average crash frequency with Empirical Bayes adjustment with respect to two different sets of Safety Performance Functions (SPFs). The estimates from each of the methods were then used to prioritize the detected sites for safety investigation and these lists were compared with previously confirmed high collision concentration locations (or hot spots).