Assessing Crash Risks of Evacuation Traffic: A Simulation-based Approach

US Transportation Collectionhttps://doi.org/10.7910/DVN/BZ6IJN2019PDFTech ReportHasan, SamiulRahman, RezaurSafety Research Using Simulation (SAFER-SIM) University Transportation CenterUniversity of Central Florida. Department of Civil, Environmental and Construction EngineeringUnited States. Department of Transportation. University Transportation Centers (UTC) ProgramUnited States. Department of Transportation. Office of the Assistant Secretary for Research and TechnologySafety Research Using Simulation (SAFER-SIM) University Transportation CenterUnited StatesFloridaAutonomous intelligent cruise controlBehaviorCalibrationCrash risk forecastingDriver support systemsDriversEvacuationHurricanesImpactsTraffic flowTraffic safetyTraffic simulation69A3551747131Final ReportRecently, hurricanes have caused major concern for transportation agencies and policymakers attempting to find better evacuation strategies. This was especially evident after Hurricane Irma, which forced about 6.5 million Floridians to evacuate the state. This mass evacuation caused a significant amount of delays on state highways due to heavy congestion and car crashes. Crashes and accidents on roads and highways are of major concern during evacuation efforts. Though several strategies have been implemented to manage the heavy traffic demand during a hurricane evacuation, current approaches seem to have less of an impact on traffic safety. In this context, this project had three objectives: (1) To assess the impact of hurricane evacuation on crash risks; (2) To identify if there are any changes in traffic flow behavior between evacuation and non-evacuation periods; and (3) To assess the impact of an in-vehicle driving assistance system during an evacuation period. First, to assess the impact of hurricane evacuation on crash risks, the authors adopted a matched case control approach. After collecting traffic and crash data along a major evacuation route in Florida, the authors estimated models for three different conditions: regular period, evacuation period, and a combination of both evacuation and regular period data. Model results show that if there is high occupancy at an upstream station and high variation of speed at a downstream station, the probability of crash occurrence increases. The authors estimate the effect of evacuation itself on crash risk and find that, after controlling for traffic characteristics, during evacuation the chance of an accident is higher than in a regular period. These findings will help the research team develop advanced real-time crash prediction models which will work for evacuation traffic conditions, and design proactive countermeasures to reduce crash occurrences during evacuation. Second, to understand driver behavior during evacuation and to assess the potential safety impacts of adaptive cruise control (ACC) systems, the authors developed a microscopic simulation model in SUMO for a segment of the Interstate highway 75 (I-75), and calibrate it using real-world traffic data collected from the evacuation period of hurricane Irma. For the calibrated model, the authors find that the values of maximum acceleration and deceleration are 4.5 ????/????2 and 6.5 ????/????2, respectively. These values are higher than those in typical car-following models calibrated under regular traffic conditions. Also, higher acceleration and deceleration values indicate abrupt speed variation, which is the most common scenario for evacuation traffic. To evaluate the safety impact of ACC systems, the authors adopted two surrogate measures: time to collision (TTC) and deceleration rate to avoid a collision (DRAC). The experiment results show that during evacuation, about 49% of traffic collisions can be reduced at a 25% market penetration of ACC-equipped vehicles. The findings from this project have further implications for evacuation declarations and highlight the need for better traffic management strategies during evacuation. Based on the findings, the authors propose several traffic management strategies to reduce the number of crashes during evacuation. The authors also propose solutions based on in-vehicle driving assistance systems and identify the challenges to increase market penetration rate for such technologies.120