Effect of Side Frictions on Traffic Characteristics of Urban Arterials

Salini, Silvia; George, Sherin; Ashalatha, R.

doi:10.1016/j.trpro.2016.11.118

Cited by 39 publications

(25 citation statements)

References 2 publications

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“…(2014) used various parameters such as lane width, nonmotorized vehicles and side friction elements to find capacity of urban arterials. Salini et al (2016) also quantified the factors for estimating side friction with the effect of bus stops, pedestrians and on street parking. They found that the effect of side friction of combined factors is significant on reduction in average speed of the traffic stream.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Side Friction on Urban Arterials

Gulivindala

Mehar

2018

Transport and Telecommunication Journal

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The influence of the side friction activities on the speed has been analyzed in the present study by conducting series of traffic field surveys. Pedestrian movements, parked vehicles and entry-exit of vehicles from surroundings, and wrong way movements are observed from videos and analyzed to estimate weighing factors. To examine the combined effects of all the activities the weighing factors are used to determine total value of side friction on the road. The study suggests model to estimate average speed of vehicular stream with the effect of side friction and volume on the roads section. It was found that the vehicular speed decreases as side friction increases at all the levels of traffic volume. However, no change in the speed was observed at lower level side friction. Capacity value obtained for combined data based on Greenshield’s theory that showed 9% reduction in the value considering with and without side friction.

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Section: Introductionmentioning

confidence: 99%

Analysis of Side Friction on Urban Arterials

Gulivindala

Mehar

2018

Transport and Telecommunication Journal

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“…Also, this equation shows well in correlating the speed value with density, bicycle rate and pedestrians crossing road carriageway rate. All models above provide how well future outcomes are likely to be predicted as depicted by the R 2 -& R 2 -Adjusted value, and other ANOVA statistics compared to the models developed in India and Tanzania (with R 2 values are 0.75 and 0.691respectively) (Chiguma, 2007;Salini et al, 2014).…”

Section: Evaluation Of the Density Speed Relationshipsmentioning

confidence: 99%

“…Roadside friction (RSF) elements have become a serious factor causing congestion and poor traffic operation in urban and rural road networks in developing countries (Salini et al, 2014;Harison et al, 2016;Pal and Roy, 2016). Many urban roads in developing countries cities have a low level of service (LOS) and hence poor performance due to some activities that take place on and alongside roads (Rao et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…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%

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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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“…Generally, the capacity loss of road links decreases with the decrease of the on-street parking intensity. The frequency of parking manoeuvre events (entering or leaving an on-street parking spot) is most momentous parking parameter that influence the link travel speed (Salini et al, 2016). Previous study resulted in that 35% of on-street parking manoeuvres can limit the capacity of the link to about 35% of the full capacity (Bulactial et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Estimate Passenger Car Equivalent of Vehicles Performing Manoeuvre to Enter or Leave Legal and Illegal on-Street Parking

Elkafoury¹,

El-Naga²

2020

IJTTE

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For transportation and traffic designers, the existence of a method to convert effective vehicles into reference Passenger Car Equivalent (PCE) is an essence. Both legal and illegal on-street parking events are associated with manoeuvre during entering or leaving the parking spot. This manoeuvre is highly affecting the traffic performance of the street link. This paper introduces a method for determining the Passenger Car Equivalent (PCE) for vehicles that perform a manoeuvre for on-street parking. The M/M/∞ queuing model together with the Greenshield traffic state model are used to estimate the effect of the delay and the capacity drop caused by a manoeuvring event on the traffic flow continuity in case of entering or leaving a legal and illegal on-street parking space. Two design charts are introduced to show the values of the average passenger car equivalent for different manoeuvre times and manoeuvring frequencies combinations for both legal and illegal parking types. PCE values of vehicles manoeuvre for legal parking experience fluctuation throughout the link's volume to capacity (D-C) ranges. It is found that, for lower D-C ratios and up to D-C of about 0.33, PCE of vehicles manoeuvre for legal parking types shows a slight upward trend. The smallest PCE of vehicles manoeuvre for legal parking is noticed at D-C of nearly 0.41. Then, the increase of D-C is accompanied with an increase of PCE supported by the increase of the link's average travel time. During manoeuvring for illegal on-street parking, the section loses one more lane capacity for the duration of the manoeuvre. Thus, the traffic demand outrace the capacity at D-C of about 0.69 which is earlier than the case of legal parking which influences the PCE value. Sensitivity analysis indicated that the time of the manoeuvring event is the major cause of uncertainty in the predicted PCE of a parking manoeuvring vehicle.

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Effect of Side Frictions on Traffic Characteristics of Urban Arterials

Cited by 39 publications

References 2 publications

Analysis of Side Friction on Urban Arterials

Analysis of Side Friction on Urban Arterials

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

Estimate Passenger Car Equivalent of Vehicles Performing Manoeuvre to Enter or Leave Legal and Illegal on-Street Parking

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