Stochastic adaptive control model for traffic signal systems

Abstract

An adaptive control model of a network of signalized intersections is proposed based on a discrete-time, stationary, Markov decision process. The model incorporates probabilistic forecasts of individual vehicle actuations at downstream inductance loop detectors that are derived from a macroscopic link transfer function. The model is tested both on a typical isolated traffic intersection and a simple network comprised of five four-legged signalized intersections, and compared to full-actuated control. Analyses of simulation results using this approach show significant improvement over traditional full-actuated control, especially for the case of high volume, but not saturated, traffic demand.

Modelling and Simulation of Vehicle Speed Guidance in Connected Vehicle Environment

“…Most of the literature falls into the following two classes: mathematical programming approach and simulation-based approach [9]. Mathematical programming approach employed a set of mixed integer linear programming (MILP) formulations to minimize the total intersection delays or to maximize the green bandwidth [10][11][12], while simulation-based approach are developed to represent the complicated interactions between traffic flow interactions and signal timing parameters [13][14][15].…”

Traffic Light Signal Parameters Optimization using Modification of Multielement Genetic Algorithm

“…Some works for traffic light signal parameters optimizations have been proposed which can be classified to three approaches: firstly, using artificial intelligence (GA, Fuzzy, Neural Networks) and their variations; secondly, using statistical such as stochastic [4]; and finally using vehicle involvement [2]. Among them, the approaches using Journal Homepage: http://iaescore.com/journals/index.php/IJECE artificial intelligence play important roles for traffic light signal parameters optimizations such as approaches based on PSO [1], GA [5,6,7,8,9], fuzzy logic which determine the best signal parameters using fuzzy rule [10,11].…”

“…Through the API, the n-populations of traffic light signal parameters are saved as output by H-MEGA . 4. The API orders the Aimsun 6.1 performing traffic simulation on road network for all n-populations of traffic light signal parameters and save the simulation results on the database.…”

Traffic-Congestion Forecasting Algorithm Based on Pheromone Communication Model

“…The growth of intelligent transport systems (ITS) has recently been quite fast and impressive, and various kinds of studies on ITS from the viewpoint of artificial intelligence have also been done [1][2] [3][4] [5]. However, there are still many problems that need to be solved and alleviating traffic congestion is one of the main issues.…”