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[NTC2016-MU-R-04] Active Bottleneck Management on Freeways Through Connected Vehicles

P.I.: 
Mecit Cetin, George List
Old Dominion University, North Carolina State University
Year: 
2016
Website: 
http://ntc.umd.edu/node/164
Subject Area: 
Collaborative Research


Description: 

Bottlenecks along freeways (such as lane drops, tunnels, sag curves, etc.) have lower capacities than their upstream segments. Consequently, they are the constriction points where traffic congestion occurs whenever the inflow or demand exceeds capacity. To minimize congestion-related delays it is essential to ensure that the throughput at these choke points is kept as high as possible while not compromising capacity due to incidents or irregular/turbulent traffic flow.

In addition, it is well-known that bottleneck capacity drops by as much as 10-20% when traffic breakdowns occur at bottleneck locations (1-4). To avoid such capacity drops, Active Traffic Management (ATM) strategies have been developed. These include adaptive ramp metering, dynamic lane use, and dynamic speed limits. These strategies have historically required the installation of field equipment, such as Dynamic Message Signs (DMSs), to regulate traffic or advise drivers about speed limits. Due to the high cost of installing, maintaining, and operating such field equipment, ATM strategies have been deployed only at a limited number of locations. However, the emergence of Connected Vehicle (CV) technology offers new ways to achieve dynamic traffic control at a fraction of cost required for traditional ATM deployments.