PROJECT NUMBER: PSR-26-18

FUNDING SOURCE: Caltrans

TOTAL COST: $100,000

PERFORMANCE PERIOD: JANUARY 2027 - JUNE 2028

Project description

Problem statement: Several cities are characterized by transit vehicles (trains, trams, and buses) sharing signalized roadways with general auto traffic, and agencies increasingly look to prioritize transit at intersections to improve service reliability without the cost of dedicated transit lanes. Evaluating this tradeoff between transit priority and the throughput of other vehicles requires traffic flow models that resolve signal-level detail: green and red phases, offsets, and phase sequence. Macroscopic models, though successful for freeway traffic, are typically too coarse to capture this detail on signalized corridors, while microscopic simulation captures it but is too computationally expensive to support control design or real-time operation. This project develops a high-resolution macroscopic traffic flow model that closes this gap, and uses it to design and evaluate passive and active transit signal priority (TSP) strategies.

Approach: The technical approach begins with developing a high-resolution macroscopic traffic flow model for signalized corridors that explicitly represents cycle length, offsets, and splits, and supports queue estimation from loop detector and connected-vehicle data. The model is validated against microscopic simulation in PTV VISSIM on a representative ten-intersection corridor, confirming that it captures the queueing and flow dynamics that matter for transit signal priority while remaining far cheaper to simulate and analyze.

Building on this model, the research designs transit signal priority control for two regimes: a passive mode, where signal splits and offsets are adapted around a known transit schedule, and an active mode, where a model predictive control framework uses real-time transit location together with detector and connected-vehicle data to estimate queues and continually re-optimize signal parameters. Both strategies are evaluated through simulation case studies on the corridor, characterizing the tradeoff between transit travel-time reduction and the resulting impact on throughput and delay for other vehicles. This is guidance directly usable by an agency deciding how aggressively to prioritize transit on a given corridor. The resulting models, algorithms, and simulation software are documented and available at the project's conclusion.