Huawei Technologies Co., Limited

Huawei Cloud Computing Technologies Co., Ltd.

Hao Hai Ma

Chen Chen

Jason T S Lam

Baher Abdulhai

Soheil Mohamad Alizadeh Shabestary

Yi Huo

Methods, systems, and processor-readable media for adaptive cycle-level traffic signal control are described. An adaptive cycle-level traffic signal controller and control method that operate within a continuous action space. A reinforcement learning algorithm called Proximal Policy Optimization (PPO), which is a type of actor-critic model for reinforcement learning, may be used to generate signal cycle phase durations selected from a continuous range of values. The controller thus does not treat the action space as discrete, but instead produces continuous values as output. The generated phase durations may define a full traffic signal cycle. The inputs to the controller may indicate current and past states of the traffic environment. The average duration of delay of vehicles in the traffic environment may be used to calculate the reward for the reinforcement learning model that drives the behavior of the controller.

Method and system for adaptive cycle-level traffic signal control

Resource scheduling methods and a resource manager define leaf buckets, each of which have coordinates in corresponding dimensions in a coordinate space. Nodes having resource values in the corresponding dimensions are mapped on the leaf buckets. A task request identifies candidate nodes and requested resources that relate to the coordinate space dimensions. The leaf buckets are scanned to find a fittable node among the list of candidates. A result of the scan is stored in a positive or a negative cache entry. When a next task request of a same task group is received, scanning of the leaf buckets is performed using information from the positive or negative cache entry. For a positive cache entry, the scanning is initiated from a point where the previous scanning has ended. For a negative cache entry, the scanning ignores nodes that were found not to contain the requested resources in the previous scanning.

Resource scheduling methods using positive and negative caching, and resource manager implementing the methods

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Hao Hai Ma