The impacts of stochastic capacity on freeway traffic flow benefits and costs: A model and a case study from Portland, Oregon

Abstract

When freeway traffic flow approaches capacity, minor disturbances or perturbations can cause traffic streams to break down into queued or bottleneck conditions. Traffic research has shown that the traffic volume at which flow breaks down is a stochastic variable. Since travel in heavily congested conditions increases travel time, fuel consumption, and emission levels, this research characterizes the impacts of stochastic capacity on travel, fuel, and emissions costs. We apply this stochastic model to a congested freeway corridor in Portland, Oregon to illustrate the sensitivity and impact of various traffic parameters on costs and net social benefits of traffic flow. Portland results indicate that travel time is the dominant cost, followed by fuel costs. For a given value per trip (in $/mile), the traffic flow volume that maximizes social benefits decreases as travel time reliability decreases. Traffic flows near capacity are justified by trip values that are, at least, 50% higher than trip values under deterministic freeway capacity.