The U.S. DOT developed a simulation model to test the potential impacts of integrating ITS in major transportation corridors. The goal was to demonstrate that increased integration among freeways, arterials, and transit systems can help balance traffic flow and enhance corridor performance.
Having a sufficient variety of ITS, network management functions, and archived traffic data, the I-880 corridor in San Francisco was selected as the ICM Test Corridor. The corridor located between Oakland and Fremont covered a distance of approximately 34 miles (250 lane miles) and contained an extensive network of alternate routes and transit options (bus and rail).
To evaluate the potential impacts of independent and combined ICM strategies in the corridor, an Analysis, Simulation, and Modeling (AMS) framework was developed. The model examined recurring and nonrecurring (incident–related) operational conditions using three levels of analysis: macroscopic, mesoscopic, and microscopic. The macroscopic analysis examined trip tables to evaluate overall trip patterns. The mesoscopic analysis examined driver behavior to evaluate traffic response to different ICM strategies, and the microscopic analysis examined the impacts of traffic control at roadway junctions.
The AMS framework analyzed the following ICM strategies:
- Zero ITS baseline
- Traveler information. In the test corridor, drivers were provided with real-time information, both pre-trip and en route, about incident conditions, expected delays, availability of transit and highway options, travel times for these options, and availability of parking.
- Transit traveler information
- Ramp metering
- HOT lanes
- Arterial traffic signal coordination
The results focused on four key performance measures: mobility (movement of people and freight), reliability (relative predictability of the public’s travel time), safety (safety characteristics in the corridor including fatalities, injuries, and property damage from crashes), and emissions and fuel consumption. The benefits data derived from the impact analysis were monetized and compared to costs data (capital, operating, and maintenance costs) derived from planning-level and life cycle cost estimates.
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