Analysis of Side Friction on Urban Arterials

Gulivindala, Pallavi; Mehar, Arpan

doi:10.2478/ttj-2018-0003

Cited by 17 publications

(13 citation statements)

References 7 publications

(4 reference statements)

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“…However, the authors considered only 90% confidence level (CI) to infer about the statistical significance of coefficients through p values, and it was found that many side friction variables become insignificant when the usual 95% CI is considered. In Gulivindala and Mehar [9] study, the R 2 values were not at all reported and some of the variables like frequency of pedestrians, parked vehicles and wrong movement had p values more than 0.05, but still they have been considered. The review of existing studies leads to the following gaps as explained below.…”

Section: Introductionmentioning

confidence: 87%

“…Many studies have reported the impact of side friction on speed-flow characteristics since 1980s [2][3][4][5], and they can be broadly divided into two groups. One is relating friction parameters with the speed observed at stretches where side friction elements are present [1,3,[6][7][8][9]. Regression models were developed to quantify the relationship, and with the developed models it would be easy to predict the speed for varying levels of side friction.…”

Section: Introductionmentioning

confidence: 99%

“…In most of the studies, one common thing observed is importance to statistical significance was not given that much. For example, some studies [7,9] have not even reported the R 2 and p values and only regression model was given. Even if R 2 is reported, it is very less in most of the studies [4,8].…”

Section: Introductionmentioning

confidence: 99%

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Dealing with Multicollinearity Problem in Analysis of Side Friction Characteristics Under Urban Heterogeneous Traffic Conditions

Singh

Kumar

2021

Arab J Sci Eng

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Disturbance to the moving traffic, such as on-street parking and bus stop on carriageway normally called as side friction in the literature, is one of the major problems that impact the vehicular speed on urban arterials in developing countries like India. Regression model to study the mode-wise vehicular speeds using side friction and other influencing variables faces the problem of multicollinearity as there is a strong correlation between the independent variables which results in high R2 and high p values. Instead of dropping the highly correlated variables which is the conventional practice to deal with multicollinearity, we proposed an approach of taking a linear combination and ratio of independent variables. To test the applicability of the proposed approach, traffic data from five locations in Hyderabad and Vellore in India having a wide variety of geometric and traffic characteristics with one or more side frictions were collected and regression models were built. It was found that the proposed approach of taking linear combination and ratio worked very well as the models exhibited a high R2, low p values and low variance inflation factor. The regression models also forecast speeds with good and reasonable accuracy. For better understanding of the impact of side friction, the present study proposed an index called side friction index and it was found that the number of side friction elements and their impact are directly proportional. Also, the impact is not uniform across the different vehicle types. Though the present study focussed on side friction problem, the approach that we proposed in this paper to deal with multicollinearity can be applied in other fields as well.

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Section: Introductionmentioning

confidence: 87%

Section: Introductionmentioning

confidence: 99%

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Dealing with Multicollinearity Problem in Analysis of Side Friction Characteristics Under Urban Heterogeneous Traffic Conditions

Singh

Kumar

2021

Arab J Sci Eng

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“…The distance a vehicle maintains with adjacent vehicles is called the lateral distance headway. A small lateral distance headway tends to reduce traffic flow and vice versa [3]. Thus, traffic models should consider both the lateral and forward distance headways to adequately characterize traffic flow.…”

Section: Introductionmentioning

confidence: 99%

Macroscopic Traffic Flow Characterization for Stimuli Based on Driver Reaction

et al. 2021

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The design and management of infrastructure is a significant challenge for traffic engineers and planners. Accurate traffic characterization is necessary for effective infrastructure utilization. Thus, models are required that can characterize a variety of conditions and can be employed for homogeneous, heterogeneous, equilibrium and non-equilibrium traffic. The Lighthill-Whitham-Richards (LWR) model is widely used because of its simplicity. This model characterizes traffic behavior with small changes over a long idealized road and so is inadequate for typical traffic conditions. The extended LWR model considers driver types based on velocity to characterize traffic behavior in non lane discipline traffic but it ignores the stimuli for changes in velocity. In this paper, an improved model is presented which is based on driver reaction to forward traffic stimuli. This reaction occurs over the forward distance headway during which traffic aligns to the current conditions. The performance of the proposed, LWR and extended LWR models is evaluated using the first order upwind scheme (FOUS). The numerical stability of this scheme is guaranteed by employing the Courant, Friedrich and Lewy (CFL) condition. Results are presented which show that the proposed model can characterize both small and large changes in traffic more realistically. Doi: 10.28991/cej-2021-03091632 Full Text: PDF

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“…Recent studies in India developed speed prediction models taking into account roadside friction factors. For instance, (Gulivindala and Mehar, 2018) incorporated into the model events/hr to represent the effects of roadside friction, while Salini et al (2014) considered the effects of the number of cars, two-wheelers, and three-wheelers as well as dwell times, number of pedestrians per minute, number of parking maneuvers, number of vehicles parked on sides of the carriageway, and influence of time of parking and un-parking vehicles. In (Dar es Salam and Chiguma, 2007) developed a speed prediction model that considered roadside friction factors during actual conditions.…”

Section: Introductionmentioning

confidence: 99%

Ffects of Roadside Friction Elements on Travel Performance and Level of Service in Kigali

2020

IJTTE

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Providing efficient mobility is the cornerstone of the socioeconomic development, however, the performance of the road transport systems in the developing countries' cities has been reduced and affected continuously due to the increase in road users both motorized and non-motorized and roadside friction elements. Recent researches revealed that efficiency in urban transport is affected by different factors associated with roadside activities. In most developing countries, cities, including Kigali City, a proliferation of roadside friction elements affect travel performance measures in the locations where these elements occur. This study attempts to analyze the effect of dynamic roadside friction factors on traffic performance measures such as speed and level of service using data collected from Kigali urban roads. Data collected included spot speed data, road condition data, traffic, and roadside elements data. All data were collected in the field over six road-stretches covering different functional classes of roads in Kigali City. Key roadside friction (RSF) elements that affect traffic performance were selected based on ANOVA results and a sensitivity analysis was carried out to quantify the impact of roadside friction factors on speed and level of service. Moreover, relationships of speed, density, and flow were developed taking into account typical dynamic roadside friction elements. Overall, it was found that roadside friction factors affect travel performance in the locations where they occur and their effects are not only on two-lane roads but also on four-lane roads. The models developed in this study take into consideration roadside friction factors, and therefore they can be used to predict operating mean vehicle speed and density. To minimize the effects of roadside friction factors on traffic performance, the research-based information and findings from this study can be used in setting out guidelines while imposing some restrictions to eradicate an occurrence and the proliferation of roadside friction elements.

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Analysis of Side Friction on Urban Arterials

Cited by 17 publications

References 7 publications

Dealing with Multicollinearity Problem in Analysis of Side Friction Characteristics Under Urban Heterogeneous Traffic Conditions

Dealing with Multicollinearity Problem in Analysis of Side Friction Characteristics Under Urban Heterogeneous Traffic Conditions

Macroscopic Traffic Flow Characterization for Stimuli Based on Driver Reaction

Ffects of Roadside Friction Elements on Travel Performance and Level of Service in Kigali

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