Hierarchical Speed Planner for Automated Vehicles: A Framework for Lagrangian Variable Speed Limit in Mixed Autonomy Traffic
CoRR(2024)
摘要
This paper introduces a novel control framework for Lagrangian variable speed
limits in hybrid traffic flow environments utilizing automated vehicles (AVs).
The framework was validated using a fleet of 100 connected automated vehicles
as part of the largest coordinated open-road test designed to smooth traffic
flow. The framework includes two main components: a high-level controller
deployed on the server side, named Speed Planner, and low-level controllers
called vehicle controllers deployed on the vehicle side. The Speed Planner
designs and updates target speeds for the vehicle controllers based on
real-time Traffic State Estimation (TSE) [1]. The Speed Planner comprises two
modules: a TSE enhancement module and a target speed design module. The TSE
enhancement module is designed to minimize the effects of inherent latency in
the received traffic information and to improve the spatial and temporal
resolution of the input traffic data. The target speed design module generates
target speed profiles with the goal of improving traffic flow. The vehicle
controllers are designed to track the target speed meanwhile responding to the
surrounding situation. The numerical simulation indicates the performance of
the proposed method: the bottleneck throughput has increased by 5.01
speed standard deviation has been reduced by a significant 34.36
showcase an operational study with a description of how the controller was
implemented on a field-test with 100 AVs and its comprehensive effects on the
traffic flow.
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