Factors Influencing Level of Service for Motorized Vehicles at Signalized Intersection under Mixed Traffic Condition

2017 ◽  
Vol 3 (2) ◽  
Author(s):  
Darshana Othayoth ◽  
K. V. Krishna Rao
Keyword(s):  
Signalized Intersection ◽  
Level Of Service ◽  
Mixed Traffic ◽  
Traffic Condition ◽  
Factors Influencing ◽  
Motorized Vehicles

Saturation Flow Model for Signalized Intersection under Mixed Traffic Condition

2018 ◽  
Vol 2672 (15) ◽  
pp. 55-65 ◽  
Author(s):  
Sabyasachi Biswas ◽  
Souvik Chakraborty ◽  
Indrajit Ghosh ◽  
Satish Chandra
Keyword(s):  
Conventional Method ◽  
Detailed Comparison ◽  
Heterogeneous Traffic ◽  
Signalized Intersection ◽  
Percentage Error ◽  
Mixed Traffic ◽  
Kriging Method ◽  
Traffic Condition ◽  
Saturation Flow ◽  
The Impact

Saturation flow is one of the most important functional parameters at signalized intersections. It is to be noted that saturation flow is a functional measure of the intersection operation, which indicates the probable capacity if working in an ideal situation. However, determination of the saturation flow is a challenging task in developing countries like India where vehicles with diverse static and dynamic characteristics use the same carriageway. At the same time, it is influenced by several other factors. In this context, the present research is carried out to examine the effects of traffic composition, approach width and right-turning movements on saturation flow under heterogeneous traffic conditions. This paper proposes a model for computing saturation flow at the signalized intersection under mixed traffic condition based on Kriging approach. A detailed comparison of the mean saturation flow values obtained by the conventional method, regression method, and Kriging method has also been presented. Low mean absolute percentage error values (<5%) have been obtained for saturation flow by Kriging method with respect to the conventional method. Finally, the proposed models are used to evaluate the impact of right-turning vehicles on saturation flow under shared lane condition.

QUANTITATIVE APPROACH TO DETERMINE PEDESTRIAN DELAY AND LEVEL OF SERVICE AT SIGNALIZED INTERSECTION

2018 ◽  
Vol 6 (1) ◽  
pp. 06-13
Author(s):  
Ammu Gopalakrishnan ◽  
Sewa Ram ◽  
Pradip Kumar Sarkar
Keyword(s):  
Empirical Model ◽  
Cycle Time ◽  
Quantitative Approach ◽  
Heterogeneous Traffic ◽  
Signalized Intersection ◽  
Level Of Service ◽  
Physical Parameters ◽  
Linear Regression Models ◽  
Traffic Conditions ◽  
Motorized Vehicles

Purpose: Level of Service is a widely adopted terminology to determine the efficiency of any transport system. From the literature it was studied that the multiple linear regression models established by many researchers to determine PLoS evolved with addition or removal of one or more physical parameters or with respect to the perception of users from different locations. At an intersection, there is little or no established methodology developed so far to determine a quantitative approach for PLoS similar to Vehicular Level of Service (VLoS). It was also pointed out that under heterogeneous traffic conditions, pedestrians are most vulnerable at intersections and they share the same space with motorized vehicles for crossing movements. Methodology: Thus, this study was built on the hypothesis that pedestrian delay of a signalized intersection is quantitatively dependent on pedestrian volume, vehicular volume and cycle time. Two signalized intersections operating as fully actuated and fixed cycle time were considered for study for period of four hours each, covering two hours of morning peak and off-peak hour traffic data. Main Findings: Using various statistical techniques, an empirical model was developed between the pedestrian delay and independent variables namely cycle time, pedestrian volume and vehicular volume. PLoS range was also determined through k-means clustering technique. Implications: The empirical model developed was validated and the application of this research was also explained. Novelty: The study is a new quantitative approach to determine PLoS and was limited to two intersections. Increase in the data may improve the accuracy of the model.

scholarly journals ANALYSIS OF VEHICLE-TYPE-SPECIFIC HEADWAYS ON TWO-LANE ROADS WITH MIXED TRAFFIC

Transport ◽  
2021 ◽  
Vol 35 (6) ◽  
pp. 588-604
Author(s):  
Rupali Roy ◽  
Pritam Saha
Keyword(s):  
Field Data ◽  
Distribution Functions ◽  
Mixed Traffic ◽  
Traffic Condition ◽  
Safety Level ◽  
Vehicle Type ◽  
Specific Distribution ◽  
Conservative Attitude ◽  
Motorized Vehicles ◽  
Lead Vehicle

Time headway is an important microscopic traffic flow parameter, which affects safety, level-of-service, capacity and traffic simulation. It is, therefore, important to know the specific distribution for a particular roadway and traffic condition. Further, headway between two vehicles depends on the type of lead vehicle and is influenced by its size and dynamics. Such impact is considerably high on two-lane roads with mixed traffic composed of a wide variety of vehicle types. This paper identified sixteen combinations of vehicle pairs and analysed vehicle-type-specific headways using field data. Appropriate distribution functions were fitted to field data and predictive models were used in understanding carfollowing behaviour. Observations indicate that quite often bike riders become reluctant in obeying lane discipline. However, car drivers show conservative attitude and usually, keep safe distance from the lead vehicle except the case when they follow another car. In addition, while following Non-Motorized Vehicles (NMV), most of the drivers keep reasonably safe distances. In this paper, a comparison of computed headway probabilities was also made with those obtained from more or less homogeneous traffic. It was found that values obtained in current study are high in most of the instances. This indicates risk-taking behaviour of driver population, which eventually affects safety of such roads. The present study, thus, demonstrates the need of investigating vehicle-type-specific headways under mixed traffic based on comprehensive field data.

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 the Level of Service of the Non-Motorized Vehicle Crossing the Signalized Intersection

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Ye Yao ◽  
Xiaofei Ye ◽  
Zhen Yang ◽  
Qiming Ye ◽  
Chang Yang
Keyword(s):  
Signalized Intersection ◽  
Level Of Service
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