As each training cycle was taking about 4 hours I did not perform any hyper parameter optimization to choose the best learning rate or regularization. Acknowledgements: I am very thankful to Udacity for selecting me for the first cohort, this allowed me to connect with many like-minded ...
traffic signal control typically formulates signal timing as an optimization problem. In this work, reinforcement learning (RL) techniques have been investigated to tackle traffic signal control problems through trial-and-error interaction with the environment. Comparing with traditional approaches, RL tech...
Spatial differentiationThe intelligent control of the traffic signal is critical to the optimization of transportation systems. To achieve global optimal traffic efficiency in large-scale road networks, recent works have focused on coordination among intersections, which have shown promising results. However...
The accurate short-term prediction of traffic speed in minutes can support traffic management, such as the optimization of signal timing and traffic resources allocation (Wang et al., 2016). Moreover, traffic participants can utilize the traffic trend to plan their travel (Park et al., 2014)....
The traffic condition at time step t is represented as a graph signal Xt∈ℝN×C on graph 𝒢, where C is the number of traffic conditions of interest (e.g., traffic volume, traffic speed, etc.). Problem Studied Given the observations at N vertices of historical P time steps 𝒳=...
RSVP operates at each LSP hop and is used to signal and maintain LSPs based on the calculated path. MPLS-TE Link Management Module This module operates at each LSP hop, performs link call admission on the RSVP signaling messages, and keep track on topology and resource information to ...
Such a dynamic optimization process is complicated and yet to be developed. This is due to the circular causality between the traffic lights and the actual traffic. However, in the era of the big-data revolution, it is only reasonable to assume that despite the computational challenges, such ...
optimization method in which the modeled curves forc(t) are fit to the traffic data with the objective function to minimize the RMSE. The pattern search algorithm falls under the general category of global optimization methods in which an initial mesh is first specified in the solution space ...
This approach significantly reduces the size of the action space, especially when the number of signal phases is large. Furthermore, the multi-discrete policy optimization algorithm is utilized to optimize the policy Getting Start All the scripts can be found in scripts. For example, we can run...
Standard Application-Layer Traffic Optimization (ALTO) Toolset. Main Components This ALTO toolset includes the following basic components: ALTO Protocol Parser ALTO Client Library ALTO Client CLI OpenALTO Server Stack OpenALTO Data Source Agent Framework ...