Traffic smoothing from an economic perspective, traffic management considerations, and the reduction of environmental pollutants are critical issues in large metropolitan areas. This paper analyzes the traffic problem of a congested freeway network by integrating microscopic traffic simulation with Design of Experiments (DoE) to investigate the effects of highway traffic control strategies.
To manage network traffic, two strategies—ramp metering and lane blocking—are employed. These strategies have recently been implemented on Tehran’s freeways using police vehicles to reduce the volume of incoming traffic to the main freeway.
To evaluate traffic-smoothing strategies, the effects of six decision variables, three variables representing the occurrence of lane blocking near three entrance ramps, and three variables representing ramp metering activation at these ramps, on two performance measures (average speed and total network throughput) are examined using a two-level factorial experimental design.
A total of 64 experimental scenarios were executed in the Aimsun microscopic simulation software, and the outputs were analyzed in Minitab to assess the significance of main and interaction effects of the decision variables. Finally, a regression model was fitted for each performance measure.
The application of Design of Experiments provides enhanced insights into the impacts of traffic-smoothing strategies and opens new avenues for the combined use of these strategies to improve traffic flow.