Horowitz, A. J. (2008). Microsimulation of Freeway Work Zones to Assess Flow and Capacity. Smart Work Zone Deployment Initiative. https://rosap.ntl.bts.gov/view/dot/88120
Horowitz, Alan J.. Microsimulation of Freeway Work Zones to Assess Flow and Capacity. Smart Work Zone Deployment Initiative, 2008. https://rosap.ntl.bts.gov/view/dot/88120.
Horowitz, Alan J. Microsimulation of Freeway Work Zones to Assess Flow and Capacity. Smart Work Zone Deployment Initiative, 2008, ROSA P. https://rosap.ntl.bts.gov/view/dot/88120.
This research applied microscopic traffic simulation to freeway work zones to further understand the relationship between traffic variables and capacity. There are two distinct forms of capacity depending upon the flow regime: capacity while traffic is free flowing and capacity while traffic is queued. Actual work zones from the Milwaukee freeway systems were varied by simulation to obtain relationships between capacity and truck volume, lane distribution, ramp location, ramp volumes, grade and merging schemes. Capacity was found to be a random variable, even when all prevailing conditions are held constant, because of stochastic variations in vehicle mix, lane distribution and driver behavior. Capacity was found to be significantly affected by prevailing conditions of grade, vehicle mix, and the lane distribution of trucks.
Horowitz, A. J. (2008). Microsimulation of Freeway Work Zones to Assess Flow and Capacity. Smart Work Zone Deployment Initiative. https://rosap.ntl.bts.gov/view/dot/88120
Horowitz, Alan J.. Microsimulation of Freeway Work Zones to Assess Flow and Capacity. Smart Work Zone Deployment Initiative, 2008. https://rosap.ntl.bts.gov/view/dot/88120.
Horowitz, Alan J. Microsimulation of Freeway Work Zones to Assess Flow and Capacity. Smart Work Zone Deployment Initiative, 2008, ROSA P. https://rosap.ntl.bts.gov/view/dot/88120.
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