Modeling Pedestrian Level of Service at Signalized Intersection Crosswalks under Mixed Traffic Conditions

2015 ◽  
Vol 2512 (1) ◽  
pp. 46-55 ◽  
Author(s):  
Xiaofei Ye ◽  
Jun Chen ◽  
Guiyan Jiang ◽  
Xingchen Yan
Keyword(s):  
Linear Regression ◽  
Pearson Correlation ◽  
Signalized Intersection ◽  
Level Of Service ◽  
Delay Model ◽  
Mixed Traffic ◽  
Factors Affecting ◽  
Traffic Conditions ◽  
Regression Techniques ◽  
Pedestrian Level Of Service

The objectives of this study were to identify the factors affecting the pedestrian level of service (LOS) at signalized intersection crosswalks under mixed traffic conditions and to develop a suitable method for estimating pedestrian LOS. The important factors influencing pedestrian LOS at crosswalks were summarized: turning traffic, through traffic, number of pedestrians, and pedestrian delay. In the Highway Capacity Manual method, pedestrian delay can be calculated by Webster's delay model, which assumes that pedestrians arrive at a uniform rate and comply with the signal at an intersection. However, that assumption is not suitable for the Chinese scenario. A pedestrian delay model was developed by considering nonuniform arrival rates and noncompliant behavior under mixed traffic conditions. The data collected by video and a questionnaire survey include information on 1,257 participants' real-time sense of comfort and safety when crossing five selected intersections and on the operational characteristics of the intersections. With perceived LOS as a dependent variable, Pearson correlation analysis and linear regression techniques were explored to determine the significant factors affecting LOS. To overcome the limitations of linear regression techniques, cumulative logistic regression was done to develop a model that fits mixed traffic conditions in China—a model that can predict the probability of responses within each LOS on the basis of a combination of explanatory variables. The results showed that the cumulative logistic model fit the survey data better than the linear regression model and produces LOS A for the crosswalks.

Modeling Pedestrian Level of Service at Signalized Intersection Under Mixed Traffic Conditions

2017 ◽  
Vol 2634 (1) ◽  
pp. 86-94 ◽  
Author(s):  
S. Marisamynathan ◽  
P. Vedagiri
Keyword(s):  
Linear Regression ◽  
Signalized Intersections ◽  
Level Of Service ◽  
Delay Model ◽  
Mixed Traffic ◽  
Threshold Values ◽  
User Perceptions ◽  
Traffic Conditions ◽  
Fcm Clustering ◽  
Pedestrian Level Of Service

Developing countries such as India need to have the proper pedestrian level of service (PLOS) criteria for various facilities to help in planning, designing, and maintaining pedestrian facilities. Thus, the objective of this study was to develop a suitable method for estimating the PLOS model under mixed traffic conditions and also to define threshold values for PLOS classification at signalized intersections. First, the data were collected with video and a user perceptions survey at eight selected signalized intersections in Mumbai, India. Second, pedestrian crossing behaviors were modeled according to arrival pattern, crossing speed, noncompliance behavior, and pedestrian–vehicular interaction. Third, a pedestrian delay model was proposed by considering crossing behavior variations and subsequent validation with field data. Fourth, significant variables were identified on the basis of the Pearson’s correlation test with user’s perceptions score. Fifth, the conventional linear regression (CLR) technique was explored to determine the PLOS. To overcome the limitations of the CLR technique, fuzzy linear regression (FLR) was done to develop a PLOS model that fits mixed traffic conditions in India. Two models were validated, and their statistical performance results indicate that the FLR model predicts the PLOS score more precisely. Finally, k-means and fuzzy C-means (FCM) clustering techniques were applied to classify the PLOS score, and the results were compared by time complexity value and field values. The performance evaluation results indicate that the k-means method saves time but fails to produce more reliable threshold values, and the FCM method produces more accurate and efficient threshold values for the PLOS score at signalized intersections under mixed traffic conditions.

scholarly journals Analysing Enabling Factors Affecting the On-site Productivity in Indian Construction Industry

2018 ◽  
Vol 49 (2) ◽  
pp. 185-193 ◽  
Author(s):  
Saurav Dixit
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Reliability Analysis ◽  
Construction Industry ◽  
Pearson Correlation ◽  
Linear Regression Analysis ◽  
Research Paper ◽  
Site Productivity ◽  
Factors Affecting ◽  
Construction Productivity

The growth in construction productivity is low and do not continue for a long span of time. The purpose of the present research paper is to analyse the factors affecting on-site construction productivity in Indian construction industry. The tools used for the analysis are reliability analysis to check the consistency of the data, Pearson correlation analysis to mathematically validate the factor analysis, and linear regression analysis to propose a framework of factors affecting construction productivity. The findings of the reliability analysis concludes that the all the factors having a value of more than 0.67, which is considered to be good for the study, and the findings of the study conclude that the most significant 3 attributes grouped in linear regression analysis change in scope (R2), revision in drawings (R15), and response to change orders (R3) having maximum impact over the construction productivity. The research paper attempts to provide an insight and better understanding of the factors affecting on-site construction productivity in India and the ways and means to control and improve construction productivity of construction projects."This paper is the revised version of the paper that has been published in the proceedings of the Creative Construction Conference 2018: Dixit, S., Mandal, S. N., Thanikal, J. V, & Saurabh, K. (2018). Critical Analysis of Factors Affecting the on-site Productivity in Indian Construction Industry, (July), 38–45. https://doi.org/10.3311/CCC2018-006"

scholarly journals Passenger Car Unit Estimation at Signalized Intersection for Non-lane Based Mixed Traffic Using Microscopic Simulation Model

2017 ◽  
Vol 45 (1) ◽  
pp. 12 ◽  
Author(s):  
Gowri Asaithambi ◽  
Hayjy Sekar Mourie ◽  
Ramaswamy Sivanandan
Keyword(s):  
Simulation Model ◽  
Signalized Intersection ◽  
Accurate Estimation ◽  
Mixed Traffic ◽  
Passenger Car ◽  
Traffic Conditions ◽  
Passenger Car Unit ◽  
Road Width ◽  
On The Road ◽  
Chennai City

In India, traffic on roads is mixed in nature with widely varying static and dynamic characteristics of vehicles. At intersections, vehicles do not follow ordered queue and lane discipline. Different vehicle types occupy different spaces on the road, move at different speeds, and start at different accelerations. The problem of measuring volume of such mixed traffic has been addressed by converting different vehicles categories into equivalent passenger cars and expressing the volume in terms of Passenger Car Unit (PCU) per hour. The accurate estimation of PCU values for different roadway and traffic conditions is essential for better operation and management of roadway facilities. Hence, the objective of the present study is to estimate the PCU values at signalized intersection in mixed traffic and to study the influence of traffic volume, traffic composition and road width on PCU values.For this purpose, a mixed traffic simulation model developed specifically for a signalized intersection was used. The model was calibrated and validated with the traffic data collected from a signalized intersection in Chennai city. Simulation runs were carried out for various combinations of vehicular composition, volume levels and road width. It was observed that presence of heavy vehicles and increase in road width affects the PCU values. The obtained PCU values were statistically checked for accuracy and proven to be satisfied. The PCU values obtained in this study can be used as a guideline for the traffic engineers and practitioners in the design and analysis of signalized intersections where mixed traffic conditions exist.

scholarly journals Method to Determine Pedestrian Level of Service for the Overall Unsignalized Midblock Crossings of Road Segments

2014 ◽  
Vol 6 ◽  
pp. 652986 ◽  
Author(s):  
Lin Zhao ◽  
Yang Bian ◽  
Jian Lu ◽  
Jian Rong
Keyword(s):  
Urban Areas ◽  
Motor Vehicle ◽  
Pearson Correlation ◽  
Level Of Service ◽  
Perception Of Safety ◽  
Operational Characteristics ◽  
Traffic Conflicts ◽  
Pedestrian Level Of Service ◽  
Broad Cross Section ◽  
Road Segments

This paper aims at developing a pedestrian level of service (LOS) model for the overall unsignalized midblock crossings of road segments from the perspective of the pedestrian's perception of safety and convenience in Chinese midblock crossing environment. Firstly, the potential primary factors influencing pedestrian LOS at unsignalized midblock crosswalks were summarized from four respects: traffic conflicts, the distance between crosswalks, crossing facilities, and delay. Secondly, 948 participants’ real-time sense of safety and convenience when they were crossing the 30 selected unsignalized midblock crosswalks and the design and operational characteristics of the selected road segments were collected. The selected midblock crosswalks were typical of those prevalent in the medium-sized urban areas of China, and the participants of questionnaire survey covered a broad cross section of Chinese population of pedestrians. Finally, Pearson correlation analysis and stepwise regression analysis were carried out to develop pedestrian LOS model for the overall unsignalized midblock crossings of road segments. The results revealed that the factors significantly influencing pedestrian LOS of the overall unsignalized midblock crossings of road segments included volume of two-way motor vehicle, the distance between marked midblock crosswalks, and the distance between unmarked crosswalks. A reliable, statistically calibrated pedestrian LOS model was developed ( R2 = 0.80).

scholarly journals PEDESTRIAN SAFETY EVALUATION OF SIGNALIZED INTERSECTIONS USING SURROGATE SAFETY MEASURES

Transport ◽  
2020 ◽  
Vol 35 (1) ◽  
pp. 48-56
Author(s):  
Sankaran Marisamynathan ◽  
Perumal Vedagiri
Keyword(s):  
Safety Evaluation ◽  
Pedestrian Safety ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Mixed Traffic ◽  
Model Framework ◽  
Safety Measures ◽  
Severity Level ◽  
Traffic Conditions ◽  
Surrogate Safety Measures

The large proportions of pedestrian fatalities led researchers to make the improvements of pedestrian safety at intersections. Thus, this paper proposes a methodology to evaluate crosswalk safety at signalized intersections using Surrogate Safety Measures (SSM) under mixed traffic conditions. The required pedestrian, traffic, and geometric data were extracted based on the videographic survey conducted at signalized intersections in Mumbai (India). Post Encroachment Time (PET) for each pedestrian were segregated into three categories for estimating pedestrian–vehicle interactions and Cumulative Frequency Distribution (CDF) was plotted to calculate the threshold values for each interaction severity level. The Cumulative Logistic Regression (CLR) model was developed to predict the pedestrian mean PET values in the cross-walk at signalized intersections. The proposed model was validated with a new signalized intersection and the results were shown that the proposed PET ranges and model appropriate for Indian mixed traffic conditions. To assess the suitability of model framework, model transferability was carried out with data collected at signalized intersection in Kolkata (India). Finally, this study can be helpful to rank the severity level of pedestrian safety in the crosswalk and improve the existing facilities at signalized intersections.

Research of Signalized Intersection Delay Problem by Time Series and Queuing Theory

2012 ◽  
Vol 253-255 ◽  
pp. 1623-1626 ◽  
Author(s):  
Lian Xue
Keyword(s):  
Time Series ◽  
Queuing Theory ◽  
Reference Value ◽  
Signalized Intersection ◽  
Complete Analysis ◽  
Level Of Service ◽  
Signal Timing ◽  
Delay Model ◽  
Scientific Model ◽  
Operation Characteristics

Signalized intersection delay is an important evaluation index of the signalized intersection capacity and level of service. This paper presents a signalized intersection delay model for signalized intersection. The model uses time series and queuing theory. It discusses the operation characteristics of the process of arrival and leaving and optimizes the intersection signal timing and gets the best signal cycle time. A scientific model and a more complete analysis are founded in the paper. These methods have a good reference value to the relevant departments.

Analysis and Application of Delay Survey in Signalized Intersection

2014 ◽  
Vol 1030-1032 ◽  
pp. 2178-2181
Author(s):  
Meng Jiao Yang ◽  
Da Lin Qian ◽  
Yi Luo
Keyword(s):  
Traffic Flow ◽  
Signalized Intersection ◽  
Delay Analysis ◽  
Delay Model ◽  
Mixed Traffic ◽  
Mixed Traffic Flow ◽  
Control Delay ◽  
Actual Operation ◽  
The Common ◽  
Sample Method

This paper introduces the common methods of delay analysis in signalized intersection. Focuses on point sample method (PSM), and puts forward the improved point sample method (IPSM) that is easier to actual operation and accurate. Because the control delay takes the place of the stop delay and the statistics of period takes the place of the statistics of moment. Apply the IPSM and the HCM delay model to analysis delay of signalized intersection in Hohhot. It is a linear relationship between the two results. And the applicability of the IPSM is verified. The IPSM is more applicable and accurate to the mixed-traffic flow in China.

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