A prediction model with wavelet neural network optimized by the chicken swarm optimization for on-ramps metering of the urban expressway

Traffic control strategy plays a significant role in obtaining sustainable objectives because it not only improves traffic mobility but also enhances traffic management systems. It has been developed and applied by the research community in recent years and still offers various challenges and issues that may require the attention of researchers and engineers. Recent technological developments toward connected and automated vehicles are beneficial for improving traffic safety and achieving sustainable goals. There is a need to develop a survey on traffic control techniques, which could provide the recent developments in the traffic control strategy and could be useful in obtaining sustainable goals. This survey presents a comprehensive investigation of traffic control techniques by carefully reviewing existing methods from a new perspective and reviews various traffic control strategies that play an important role in achieving sustainable objectives. First, we present traffic control modeling techniques that provide a robust solution to obtain reasonable traffic and sustainable mobilities. These techniques could be helpful for enhancing the traffic flow in a freeway traffic environment. Then, we discuss traffic control strategies that could be helpful for researchers and practitioners to design a robust freeway traffic controller. Second, we present a comprehensive review of recent state-of-the-art methods on the vehicle design control strategy, which is followed by the traffic control design strategy. They aim to reduce traffic emissions and energy consumption by a vehicle. Finally, we present the open research challenges and outline some recommendations which could be beneficial for obtaining sustainable goals in traffic systems and help researchers understand various technical aspects in the deployment of traffic control systems.

Section: Machine Learning Methodsmentioning

confidence: 99%

A Comprehensive Review on Traffic Control Modeling for Obtaining Sustainable Objectives in a Freeway Traffic Environment

Sheikh

Peng

2022

“…In addition, some scholars have studied the short-term parking space reservation allocation strategy for special situations (e.g., unpunctuality or uncertainty in travelers' arrival/departure time, and time-limited opening spaces for shared parking) [35][36][37][38][39], trading mechanisms [40,41], and optimization algorithms [42][43][44][45][46][47][48][49].…”

Section: Introductionmentioning

confidence: 99%

Research on Parking Service Optimization Based on Permit Reservation and Allocation

Sun

2022

Parking facilities in central urban areas have limited supply, high utilization, and turnover rate, leading to the high parking cost. To draw the issues of parking uncertainty, high search time, and underutilization of parking lots, this study shows the application of permits in parking management. It first analyzes the characteristics and costs of “arrival priority” and “reservation priority” modes, and then, it proposes the parking permit reservation and allocation mode based on “service order optimization” and designs an “ant colony-genetic” algorithm to solve the optimal service order. The numerical example shows that the measures of quantity control and matching optimization are effective in parking management. The parking reservation mode of “service order optimization” has advantages in parking lot utilization rate, service demand quantity, and total parking cost.

“…In commercial implementations of the social force model, the parameters are calibrated against by maximizing likelihood or minimizing nonlinear square error between field experiment results and simulated motion [12][13][14]. Recently, Ci et al integrated a chicken swarm optimization and K-means algorithm to select key-point for dynamic flow control [15]. Yuan et al considered sample size and precision of data and found that Bayesian Logistic regression can identify significant risk factors when data sets are of different precision [16].…”

Section: Introductionmentioning

confidence: 99%

Social Force Model Calibration for Preschool Children Evacuations Based on Multiscenario Experiments

She

Liu

et al. 2022

The social force model has been widely used in simulating and analyzing pedestrian behavior. Like any agent-based models, the fidelity of the social force model largely relies on its numerical parameters that characterizes pedestrians’ behaviors. While parameters describing normal walking behaviors have been observed and calibrated in field experiments, those describing behaviors under abnormal and urgent circumstances have rarely been studied but are of practical significance in evaluating safety functionality of facilities, particularly those serving children or elders. Specifically aiming at providing a set of social force model parameters characterizing children’s behavior during evacuation, this study conducted evacuation experiments with preschool children under multiple emergency scenarios involving impaired-vision and flame scenarios and benchmarked against a normal scenario. A simulation-calibration framework is developed based on the social force model to calibrate evacuation behavior parameters by minimizing trajectory distance. The numerical approximation results indicate evident parameter disparities of preschool children from adults. This study can improve evacuation strategies and the designing/evaluation process of dedicated facilities layouts such as kindergarten corridors, activity rooms, and playgrounds.