01594816

Component

Currently red light running fines are legislated or based off of red light running camera system costs and not the risk imposed by the runner. This paper seeks to provide a basis for red light running fines through the simulation of the probability of a crash for a given time after red that a runner enters the intersection. The probability of a crash occurring was determined by the use of a physical model based on data from four red light camera intersections in the City of Opelika, Alabama. Data were collected through video taken at the camera intersections and included driver reaction to the signal change and driver acceleration with other variables used in the model such as intersection geometry being available for modification. The model was run as a Monte Carlo simulation in order to generate a crash probability distribution for a discrete time after red that a runner entered the intersection. Furthermore, model variables were altered to examine their impact on probabilistic crash risk to allow municipalities the option to adjust the all-red clearance interval to mitigate intersection geometry effects. Due to the multitude of laws and regulations on the dollar value of red light running fines, probabilities are reported for discrete times and a tiered fine structure is discussed.

This paper was sponsored by TRB committee AL010 Standing Committee on Transportation Law.

01584066

16-4619

English

13p

2016

Transportation Research Board 95th Annual Meeting

Web

Figures; Maps; References (18) ; Tables

Acceleration (Mechanics); Behavior; Drivers; Fines (Penalties); Mathematical models; Red light running; Signalized intersections; Video cameras

Opelika (Alabama)

Highways; Law; Operations and Traffic Management; Safety and Human Factors

Transportation Research Board Annual Meeting 2016 Paper #16-4619

TRIS, TRB, ATRI

Jan 12 2016 6:02PM