Exploring the impact of connected and autonomous vehicles on freeway capacity using a revised Intelligent Driver Model

Connected and autonomous vehicle (CAV) technologies are expected to change driving/vehicle behavior on freeways. This study investigates the impact of CAVs on freeway capacity using a microsimulation tool. A four-lane basic freeway segment is selected as the case study through the Caltrans Performan...

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Bibliographic Details
Published in:Transportation planning and technology 2020-04, Vol.43 (3), p.279-292
Main Authors: Liu, Pengfei, Fan, Wei (David)
Format: Article
Language:English
Subjects:
calibration
Car following
Computer simulation
Connected and autonomous vehicles
Drivers
Driving
Driving conditions
genetic algorithm
Genetic algorithms
Highways
Impact strength
Intelligent Driver Model
Market penetration
microsimulation
Penetration
Performance measurement
Speed limits
Traffic
Vehicles
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Summary:Connected and autonomous vehicle (CAV) technologies are expected to change driving/vehicle behavior on freeways. This study investigates the impact of CAVs on freeway capacity using a microsimulation tool. A four-lane basic freeway segment is selected as the case study through the Caltrans Performance Measurement System (PeMS). To obtain valid results, various driving behavior parameters are calibrated to the real traffic conditions for human-driven vehicles. In particular, the calibration is conducted using genetic algorithm. A revised Intelligent Driver Model (IDM) is developed and used as the car-following model for CAVs. The simulation is conducted on the basic freeway segment under different penetration rates of CAVs and different freeway speed limits. The results show that with an increase in the market penetration rate, freeway capacity increases, and will increase significantly as the speed limit increases.
ISSN:0308-1060
1029-0354
DOI:10.1080/03081060.2020.1735746