Funding source: US DOT

Contract number: 69A3551747109

Funding amount: $100,000

Performance period: 8/16/2021 to 8/15/2022

Traffic systems in several spots of a large city, such as downtown, the area around airport, or the area around major sporting or cultural venues, are characterized by tight spaces. Therefore, during peak period, when traffic demand exceeds supply, congestion could spill to adjoining areas, which could then lead to cascading effects. We propose to develop traffic management strategies for such systems by coordinated control of demand and supply. Specifically, on the supply side, we propose to design boundary control, in the form of traffic signal control and ramp metering. On the demand side, we propose to design time-dependent incentives/payment schemes to spread the demand during periods of peak demand. The novelty will be on coordination between the supply and demand control. Moreover, in contrast to the current literature, we plan to explicitly include budget constraint of a city as well as cap on payment for an individual driver when designing these incentives. Naturally, there will be a tradeoff between such constraints and peak congestion. The study of such constraint will allow a city to quantify the cost to maintain congestion within a desirable limit. While the primary focus will be on technology scenarios currently in use, we shall also study how leveraging the proposed levels of connectivity and autonomy can further enhance supply side control for tight areas. The algorithmic and modeling contributions will be supplemented with case studies involving setups from the Los Angeles area.

In summary, the project objectives are:
1. Demand side control of traffic arrival to tight congestion spots through time-dependent incen- tives/payments to spread the arrival times while also maximizing net travel benefit; emphasis on explicit consideration of traffic agency's budget constraint and cap on payment by an in- dividual driver
2. Pareto curves that characterize tradeoff between spatial extent of congestion and agency's budget, under demand side control
3. Supply side control, in the form of traffic signal control and ramp metering, in coordination with demand side control and its impact on the Pareto curves
4. Utilizing vehicle autonomy to enhance supply side control, and study its effect on the Pareto curves
5. Case study in the Los Angeles area to compare current congestion with the one under the proposed coordinated demand and supply control strategy