Left turn crash risk analysis: Development of a microsimulation modeling approach. (September 2020)

• Record Type: Journal Article
• Authors: Appiah, Justice; King, F. Adam; Fontaine, Michael D.; Cottrell, Benjamin H.
• Is Part Of: Accident analysis and prevention. Volume 144(2020)
• Publication Date: 2020-09
• Subjects: Left-turn phasing -- Flashing yellow arrow -- Traffic conflicts -- Crash risk; Accidents -- Prevention -- Periodicals; Accident Prevention -- Periodicals; Accidents -- Prévention -- Périodiques; 363.106
• DOI: 10.1016/j.aap.2020.105591
• Languages: English
• ISSNs: 0001-4575

Abstract

Highlights: Developed an analytical tool for time-of-day use of permissive left-turn phasing. Motivated by recent widespread application of the flashing yellow arrow indication. Used VISSIM and SSAM to study left-turn crash risk as traffic conditions changed. Demonstrated application via time-of-day crash risk profiles and nomograms. Abstract: The use of traffic simulation to analyze complex transportation issues has become common practice in transportation engineering. The further application of microsimulation to the analysis of traffic safety in a systematic, rigorous, and controlled fashion is becoming increasingly viable as simulation models improve and tools for quantifying surrogate safety measures become readily accessible. Using a calibrated traffic microsimulation model and surrogate safety assessment model analysis, this paper examined how the risk for left-turn crashes varied as traffic conditions changed at a signalized intersection. Safety impacts for 750 unique combinations of intersection geometry, traffic, and signal timing parameters were simulated and the number of left-turn conflicts per hour noted. Results of the simulation analyses were used to develop statistical models that expressed the risk of occurrence of a left-turn crash during a given hour as a function of the left-turn phasing mode and prevailing conditions during that hour. The study was motivated by the recent widespread application of the flashing yellow arrow (FYA) which provides the opportunity to vary left-turn phasing mode by time of day—potentially leading to more efficient traffic operations at signalized intersections. In this regard, the study addresses a basic need for tools that predict how the risk for left-turn crashes might vary at a more disaggregated level than that provided by existing crash prediction models, which typically predict yearly totals of left-turn crashes, often based on annual average daily traffic volumes. Potential application of the model to the implementation of a time-variable safety-based left-turn phasing selection scheme using FYA was successfully demonstrated.