This study was conducted to examine the ability of two ramp metering strategies at reducing the real-time crash risk along a typical urban freeway. The strategies were tested using a simulated freeway network of Interstate-4 in Orlando, Florida created in the PARAMICS micro-simulation package. Measurements of the real-time crash risk along the freeway were estimated using models created by Pande and Abdel-Aty (2006a, 2006b). The ramp metering strategies tested were the uncoordinated ALINEA algorithm and the coordinated Zone ramp metering algorithm. Two implementation methods of these algorithms were examined the traffic-cycle realization and the one-car-per-cycle realization. This study shows that both algorithms successfully reduce the real-time crash risk along the freeway. The traffic-cycle realization provides better safety and operational benefits when applied with the ALINEA algorithm. The ALINEA algorithm works best with shorter cycle lengths while the Zone algorithm performs best with longer cycle lengths. The ALINEA algorithm proves to be superior to the Zone algorithm at reducing the crash risk as it is more restrictive and generally allows fewer vehicles onto the network. However, at the 90 percent loading scenario, evidence of crash risk migration (the lowering of crash risk at one location combined with the increase at another) appears when the ALINEA algorithm is applied. This crash risk migration is a function of the specific geometry and demand patterns of the network used and is reduced by applying the Zone algorithm. This shows that while the ALINEA algorithm provides better overall results, there are cases where a less restrictive algorithm would perform better from a safety perspective.
Samenvatting