Traffic congestion, which costs Ontario billions of dollars a year, follows traffic breakdown, often at bottlenecks, but generally when the demand for travel exceeds the available road capacity. Controlling traffic flows through adaptive traffic signal control at ramps and intersections and road congestion pricing strategies has the potential to ensure more rational use of road resources.
Capacity-Boosting Congestion-Reduction Real-Time Dynamic Congestion Pricing
Road pricing has the potential to influence travel choices in a manner that reduces congestion while raising funds for improving sustainable transportation infrastructure.It can also be used as a supply control policy that can eliminate hyper-congestion that arises when traffic densities increase the critical density (at capacity flow).
Design and Analysis of a Self-Learning Adaptive Ramp Metering on a Test Case in Toronto
Freeway congestion forms when demand exceeds the freeway capacity. While congestion results in increased travel time, decreased throughput due to congestion will have a more significant effect on freeway performance. Ramp metering is considered the most effective traffic control measure and has the potential to prevent congestion by limiting the inflow to freeway.
A Novel Self-Learning Intelligent Traffic Signal Control System for Congested Urban Areas
The population is steadily increasing worldwide; consequently the demand for mobility is increasing, especially in times of good economy. When the growth in social and economic activities outpaces the growth of transportation infrastructure, congestion is inevitable. Severe congestion and long commutes plague many large urban areas around the word, and the Greater Toronto Area (GTA) is no exception.