The Research of Pedestrian Platoon Multiple Events at Signalized Intersection

2011 ◽  
Vol 301-303 ◽  
pp. 864-869
Author(s):  
Hui Zhang ◽  
Quan Yu ◽  
Jian Rong ◽  
Li Ping Shi
Keyword(s):  
Cluster Analysis ◽  
Video Analysis ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Average Speed ◽  
Multiple Events

This paper studies the multiple events character of pedestrian platoon with the technique of video analysis. Meanwhile, applying K-means cluster, we select three criterions which are the average speed, the width and the length of pedestrian platoon, the crossing process was divided into multiple events at signalized intersections. The application of cluster analysis in the division of multiple events was proved through case study, and it reflected the phased characteristics of pedestrian platoon.

scholarly journals Car-following Behavior Analysis of Left-turn Vehicles at Signalized Intersections

2020 ◽  
Vol 6 (1) ◽  
pp. 186-193 ◽  
Author(s):  
Fulu Wei ◽  
Long Chen ◽  
Yongqing Guo ◽  
Mingtao Chen ◽  
Jiaxiang Ma
Keyword(s):  
Field Data ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Velocity Difference ◽  
Left Turn ◽  
Average Speed ◽  
Car Following ◽  
Turning Radius ◽  
The Stability ◽  
Stability And Accuracy

In order to enrich the car-following theory of urban signalized intersections, and reveal the car-following characteristics of left turn at signalized intersections, the car-following behavior of left turn at signalized intersections is studied. The car-following data acquisition test which was based on high precision GPS was designed. And the car-following characteristics of left-turning vehicles at signalized intersections with different turning radii were analyzed. Based on which, the influence of radius on the car-following behavior was explained, and the New Full Velocity Difference (NFVD) model was developed. The genetic algorithm was used to calibrate the parameters of the NFVD model. The stability and accuracy of the calibrated model was further analyzed by using field data. The results showed that the average speed of the following car increases with the turning radius of the signalized intersection; the car-following speed which the highest frequency occurs under different turning radii tends to increase with the enlargement of turning radius; the larger the average headway distance between the car-following vehicles, the more intense of the driver’s response to the deceleration of the front vehicle. These findings could be used in traffic simulation and to make engineering decisions.

Applicability Study on Simulating Interference of Mixed Traffic at Signalized Intersections Using VISSIM

2013 ◽  
Vol 423-426 ◽  
pp. 2946-2949
Author(s):  
Cheng Hua Li ◽  
Shan Shan Li
Keyword(s):  
Signalized Intersections ◽  
Simulation Software ◽  
Signalized Intersection ◽  
Simulation Platform ◽  
Mixed Traffic ◽  
Average Speed ◽  
Simulation Results

The applicability of the interference of mixed traffic of VISSIM is inspected indexed by the rate of interference, delay and the average speed of right turn vehicles. This paper took Jiaoda east road and Xueyuan south road intersection (Hereinafter referred to as Sidaokou) as an example, established the simulation platform. Then the actual running condition of vehicles and simulation results were compared. The error between the measured values of each index and simulation values are in the range of 20%, which shows that it is applicable to use the simulation software VISSIM to simulate the interference between mixed traffic at signalized intersection.

scholarly journals A Comparison of Traffic Flow Performance of Roundabouts and Signalized Intersections: A Case Study in Nigde

2020 ◽  
Vol 14 (1) ◽  
pp. 120-132
Author(s):  
Hatice G. Demir ◽  
Yusuf K. Demir
Keyword(s):  
Traffic Flow ◽  
Signalized Intersections ◽  
Urban Traffic ◽  
Signalized Intersection ◽  
Negative Effects ◽  
Average Delay ◽  
Current State ◽  
Intersection Analysis ◽  
High Traffic Volume

Background: Intersections affect the safety and capacity of urban traffic. Therefore, the design and selection of the type of intersection need to be made very carefully. According to the demand level, a different intersection can be designed. Signalized intersections are one of the intersection types in which the sequence and duration of the flow at the intersection are provided by the lights. Generally, this type of intersection is used on roads with high traffic volume. Modern roundabouts are one of the types of circular intersections that provide advantages over other types of intersection in terms of smooth operation and safety. Modern roundabouts exist in several types today worldwide. In practice, the distinction about the kinds of roundabouts would not be fully clarified; as a result, queuing and delay can be seen as negative effects. Methods: In this study, to make a distinction and clarify the kinds of roundabouts, first, the roundabouts types are introduced according to geometric and operational aspects. A signalized intersection, where a circular island is placed and also signalized, was investigated in terms of capacity, delay, and emissions located in Niğde. The traffic flow performance of the current state (nested signalized roundabout) was calculated with HCM Method (for signalized intersection) using SIDRA and compared with roundabout solutions of the intersection with HCM6 (for roundabout) method using SIDRA Intersection analysis software. Results: From the results of the intersection capacity analysis study based on HCM6, it was seen that the application of a roundabout scenario (intersection considered as a modern roundabout) showed higher performance at the intersections than the intersection having a secondary signal. Capacity increased to 67.8%, the average delay decreased to 72.8% and 95th percentile queue dropped to 82.2%. Conclusion: Roundabout controlling instead of a nested signal system can be an example of the increase in the performance of traffic flow. This highlights the importance of choosing the appropriate roundabout design.

Modeling Capacity of Through Movement at Signalized Intersection Affected by Short Left-Turn Bay under Different Signal Settings

2021 ◽  
pp. 036119812110064
Author(s):  
Zihang Wei ◽  
Yunlong Zhang ◽  
Xiaoyu Guo ◽  
Xin Zhang
Keyword(s):  
Cycle Length ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Essential Factor ◽  
Highway Capacity ◽  
Left Turn ◽  
Highway Capacity Manual ◽  
Proposed Model ◽  
Vehicle Demand ◽  
The One

Through movement capacity is an essential factor used to reflect intersection performance, especially for signalized intersections, where a large proportion of vehicle demand is making through movements. Generally, left-turn spillback is considered a key contributor to affect through movement capacity, and blockage to the left-turn bay is known to decrease left-turn capacity. Previous studies have focused primarily on estimating the through movement capacity under a lagging protected only left-turn (lagging POLT) signal setting, as a left-turn spillback is more likely to happen under such a condition. However, previous studies contained assumptions (e.g., omit spillback), or were dedicated to one specific signal setting. Therefore, in this study, through movement capacity models based on probabilistic modeling of spillback and blockage scenarios are established under four different signal settings (i.e., leading protected only left-turn [leading POLT], lagging left-turn, protected plus permitted left-turn, and permitted plus protected left-turn). Through microscopic simulations, the proposed models are validated, and compared with existing capacity models and the one in the Highway Capacity Manual (HCM). The results of the comparisons demonstrate that the proposed models achieved significant advantages over all the other models and obtained high accuracies in all signal settings. Each proposed model for a given signal setting maintains consistent accuracy across various left-turn bay lengths. The proposed models of this study have the potential to serve as useful tools, for practicing transportation engineers, when determining the appropriate length of a left-turn bay with the consideration of spillback and blockage, and the adequate cycle length with a given bay length.

scholarly journals Cluster analysis of parking behaviour: A case study in Munich

2021 ◽  
Vol 52 ◽  
pp. 485-492
Author(s):  
Syrus Gomari ◽  
Christoph Knoth ◽  
Constantinos Antoniou
Keyword(s):  
Cluster Analysis

scholarly journals Trajectory Planning Method for Mixed Vehicles Considering Traffic Stability and Fuel Consumption at the Signalized Intersection

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Shan Fang ◽  
Lan Yang ◽  
Tianqi Wang ◽  
Shoucai Jing
Keyword(s):  
Fuel Consumption ◽  
Trajectory Planning ◽  
Signalized Intersections ◽  
Planning Method ◽  
Signalized Intersection ◽  
Driver Model ◽  
Connected Vehicles ◽  
Connected Vehicle ◽  
Traffic Lights ◽  
Trigonometric Model

Traffic lights force vehicles to stop frequently at signalized intersections, which leads to excessive fuel consumption, higher emissions, and travel delays. To address these issues, this study develops a trajectory planning method for mixed vehicles at signalized intersections. First, we use the intelligent driver car-following model to analyze the string stability of traffic flow upstream of the intersection. Second, we propose a mixed-vehicle trajectory planning method based on a trigonometric model that considers prefixed traffic signals. The proposed method employs the proportional-integral-derivative (PID) model controller to simulate the trajectory when connected vehicles (equipped with internet access) follow the optimal advisory speed. Essentially, only connected vehicle trajectories need to be controlled because normal vehicles simply follow the connected vehicles according to the Intelligent Driver Model (IDM). The IDM model aims to minimize traffic oscillation and ensure that all vehicles pass the signalized intersection without stopping. The results of a MATLAB simulation indicate that the proposed method can reduce fuel consumption and NOx, HC, CO2, and CO concentrations by 17%, 22.8%, 17.8%, 17%, and 16.9% respectively when the connected vehicle market penetration is 50 percent.

A distribution density-based methodology for driving data cluster analysis: A case study for an extended-range electric city bus

2018 ◽  
Vol 73 ◽  
pp. 131-143 ◽  
Author(s):  
Haiming Xie ◽  
Guangyu Tian ◽  
Hongxu Chen ◽  
Jing Wang ◽  
Yong Huang
Keyword(s):  
Cluster Analysis ◽  
Distribution Density ◽  
City Bus ◽  
Extended Range

scholarly journals Performance assessment of alternative SSS networks by combining KPIs and factor-cluster analysis

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Patrizia Serra ◽  
Gianfranco Fancello
Keyword(s):  
Cluster Analysis ◽  
Performance Assessment ◽  
Decision Support Tool ◽  
Transport Systems ◽  
Quantitative Methodology ◽  
Support Tool ◽  
Performance Benchmarking ◽  
Relevant Variables ◽  
Quantitative Results

Abstract Performance assessment is a fundamental tool to successfully monitor and manage logistics and transport systems. In the field of Short Sea Shipping (SSS), the performance of the various maritime initiatives should be analyzed to assess the best way to achieve efficiency and guide related policies. This study proposes a quantitative methodology which can serve as a decision-support tool in the preliminary assessment and comparison of alternative SSS networks. The research is executed via a Mediterranean case study that compares a hypothetical Mediterranean ro-ro SSS network developed in the framework of a past Euro-Mediterranean cooperation project with the network of existing ro-ro liner services operating in the area. Performance benchmarking of the two networks is performed using a set of quantitative Key Performance Indicators (KPIs) and applying a factor-cluster analysis to produce homogeneous clusters of services based on the relevant variables while accounting for sample heterogeneity. Quantitative results mostly confirm the overall better performance of the prospective network and demonstrate that using KPIs and factor-cluster analysis to investigate the performance of maritime networks can provide policymakers with a preliminary wealth of knowledge that can help in setting targeted policy for SSS-oriented initiatives.

scholarly journals Understanding the Usage Patterns of Bicycle-Sharing Systems to Predict Users’ Demand: A Case Study in Wenzhou, China

2018 ◽  
Vol 2018 ◽  
pp. 1-21 ◽  
Author(s):  
Xiaomei Xu ◽  
Zhirui Ye ◽  
Jin Li ◽  
Mingtao Xu
Keyword(s):  
Cluster Analysis ◽  
Comparative Analysis ◽  
Prediction Models ◽  
Transportation Network ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Demand Prediction ◽  
Usage Patterns ◽  
Accuracy Of Prediction

Bicycle-sharing systems (BSSs) have become a prominent feature of the transportation network in many cities. Along with the boom of BSSs, cities face the challenge of bicycle unavailability and dock shortages. It is essential to conduct rebalancing operations, the success of which largely depend on users’ demand prediction. The objective of this study is to develop users’ demand prediction models based on the rental data, which will serve rebalancing operations. First, methods to collect and process the relevant data are presented. Bicycle usage patterns are then examined from both trip-based aspect and station-based aspect to provide some guidance for users’ demand prediction. After that, the methodology combining cluster analysis, a back-propagation neural network (BPNN), and comparative analysis is proposed to predict users’ demand. Cluster analysis is used to identify different service types of stations, the BPNN method is utilized to establish the demand prediction models for different service types of stations, and comparative analysis is employed to determine if the accuracy of the prediction models is improved by making a distinction among stations and working/nonworking days. Finally, a case study is conducted to evaluate the performance of the proposed methodology. Results indicate that making a distinction among stations and working/nonworking days when predicting users’ demand can improve the accuracy of prediction models.

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