Prediction of potential wrong-way entries at exit ramps of signalized partial cloverleaf interchanges

Several previous studies, based upon wrong-way driving (WWD) crash history, have demonstrated that partial cloverleaf (parclo) interchanges are more susceptible to WWD movements than others. Currently, there is not a method available to predict WWD incidents and to prioritize parclo interchanges for implementing safety countermeasures for reducing WWD crashes.

The focus of this manuscript is to develop a mathematical method to estimate the probability of WWD incidents at exit ramp terminals of this type of interchange.

VISSIM traffic simulation models, calibrated by field data, are utilized to estimate the number of potential WWD maneuvers under various traffic volumes on exit ramps and crossroads. The Poisson distribution model was implemented without field observation and crash data.

A comparison between the field data and simulation outputs revealed that the developed model enjoys an acceptable level of accuracy. The proposed model is largely sensitive to left-turn volume toward an entrance ramp (LVE) than stopped vehicles at an exit ramp (SVE). The results indicated that potential WWD events increase when LVEs increase and SVEs decrease. Also, the probability of WWD event decreases as road users are more familiar with the facility.

The proposed method can diminish one of the challenges in front of transportation engineers, which is to identify high WWD crash locations due to insufficient information in crash reports. The results are helpful for transportation professionals to take proactive steps to identify locations for implementing safety countermeasures at high risk signalized parclo interchanges.