Zhaocheng He

Optimized two-stage fuzzy control for urban traffic signals at isolated intersection and Paramics simulation

This paper presents two adaptive two-stage fuzzy controllers for traffic signals at isolated intersections. Firstly, a two-stage combination fuzzy controller is designed. For traffic status variables in two-stage controller leading to the inefficiency of traffic states weakening under low traffic flow, the controller introduces 0–1 combination and determines the combination of traffic status variables of fuzzy controllers inputs from the perspective of structural optimization. Secondly, aiming at the problems of fuzzy controller parameter empirical settings and functional disability of learning, a two-stage fuzzy logic traffic signal controller with online optimization is proposed; this controller introduces the rolling horizon framework and optimizes the parameters of membership functions and controller rules by using hybrid genetic algorithm. The performance of two proposed models is validated via online Paramics-based simulation platform, and extensive simulation tests have demonstrated the potential of developed controllers for adaptive traffic signal control.

Urban traffic signal two-stage combination fuzzy control and Paramics simulation

In the light of more traffic status variables are considered under low traffic flow in traffic intensity-based two-stage fuzzy control for urban traffic signals, thus leading to the inefficiency of traffic states weakening at isolated intersections. This paper introduces a two-stage combination fuzzy optimal controller for traffic signals at urban isolated intersections: the proposed controller adopts 0-1 combination; depending on the traffic status at intersections, the combination of variables of traffic status of fuzzy controllers inputs will be determined; and the single-stage controller is applied under low traffic flow, while the traffic intensity-based two-stage fuzzy controller is used under medium or high traffic flow. Experiment is carried on a typical urban isolated intersection and performance of proposed model and algorithm is validated via Paramics. Furthermore, four kinds of control strategies are extensively simulated on different simulations scenes. Simulation results indicate that the proposed controller is able to choose status variables based on traffic status features at isolated intersections and the signal strategy derived from the proposed controller is more effective.

Survey the impact of different rainfall intensities on urban road traffic operations using Macroscopic Fundamental Diagram

This paper focuses on investigating the effects of different rainfall intensities on traffic operations of urban road networks. Macroscopic Fundamental Diagram (MFD) and Spearman correlation coefficient are used to quantitatively describe the networks operation and measure the rainfall impact on it. Mastering the rainfall impact on urban road traffic operation is not only important for the traffic state evaluation in rainy days, but also for the development of effective management strategies under rainy conditions. An empirical analysis is carried out on a major arterial network located on Haizhu district of Guangzhou, China. The results indicate that the rainfall events increased the uncertainty in network performance, and the reduction is in an increasing tendency with the increase in rainfall intensity. Furthermore, the different rainfall intensities have divergent impacts on macroscopic traffic variables. The heavy rain and rainstorm have remarkable negative effect on macroscopic traffic parameters, which produced Critical Accumulation and Maximum Production reduction of 10.5%, 16.7% and 21.0%, 18.7%, respectively. While the light rain and moderate rain have relative small impact on networks operation. Whats more, the precipitation resulted in a significant decrease effect on the parameters of weighted free-flow speed and weighted jam density of the study network, the average reduction is 9.7% and 12.3%, regardless of the intensity. The production and weighted speed are also reduced by rainy condition, but the parameter of accumulation is not rainy-sensitive.

Paramics-Based Microscopic Simulation Evaluation for Urban Traffic Signal Two-Stage Controller

This paper proposes the design and Paramics-based evaluation of a two-stage fuzzy logic traffic signal controller (TSTFC) for an isolated intersection. The fuzzy controller employs traffic intensity-based two stage fuzzy logic procedure, and the design principles of two-stage fuzzy controller are first presented. Then, the COM-based hybrid programming is employed to make the micro traffic simulator Paramics interact with fuzzy controllers developed by Matlab, and a Paramics-based simulation platform of TSTFC is developed via Paramics API. Finally, experiments are conducted on a typical urban isolated intersection, and the performance of the developed two-stage fuzzy control simulation model is validated by comparison to those of fixed-time, actuated, and classic fuzzy controllers for different traffic conditions. Extensive simulation results have demonstrated the potential of developed hybrid programming in time efficiency and simulating real traffic conditions and indicated that the signal strategy derived from TSTFC is more effective when traffic status at intersections is above low saturation.

Investigation of the Impact of Different Rainfall Intensities on Macroscopic Traffic Variables of Urban Road Networks

For all road users and managers, rainfall events are seen as a source of uncertainty that can affect both traffic safety and traffic operation. The investigation of the impact of different rainfall intensities on traffic operations of urban road network represents the first step toward the development of weather-responsive traffic management strategies. An empirical analysis is carried out on a major arterial network located on Haizhu district of Guangzhou, China. The results indicate that different rainfall intensities have divergent impacts on macroscopic traffic variables. Specifically, the precipitation resulted in a significant decrease in weighted free-flow speed and weighted jam density of the study network. Moreover, heavy rain, rainstorm, and heavy rainstorm have remarkably negative effects on macroscopic traffic parameters, which produced critical accumulation and maximum production reduction of 10.5%, 22.2%, 15.1% and 16.6%, 21.6%, 15.6%, respectively. While light rain and moderate rain have relatively small affect on network.

An Adaptive Two-Stage Fuzzy Controller for Traffic Signals: Architecture, Algorithms, and Simulation

This paper presents the design and evaluation of a two-stage fuzzy logic traffic signal controller with online optimization for an isolated intersection. The controller is designed to be adaptive to real-time traffic demands and has the following two critical features: (1) designing a two-stage fuzzy logic controller. The fuzzy controller uses strategic and tactical vehicle loop detectors, placed respectively upstream and at the stop-line of the intersection on each approach, to measure approach arrival flows and estimate queues. This data is used to decide whether to extend or terminate the current signal phase. These decisions are made using the proposed two-stage fuzzy logic procedure. (2) Developing an adaptive optimization framework of fuzzy controller to adjust fuzzy membership functions and controller rules with on-line learning. This study models the performance index of average delays based on traffic status identification, and at regular time intervals, employs a hybrid genetic algorithm to efficiently yield the reliable solution through reappearance of statistical traffic flow. The performance of this controller is compared to those of fixed-time, actuated, classic fuzzy and two-stage fuzzy controller for different traffic conditions.