scholarly journals Lambert W Based Speed Reduction Model in Presence of Pedestrian Movements: Case Studies on Undivided Streets

2021 ◽  
pp. 1-16
Author(s):  
Sourabh Thakur
Keyword(s):  
Prediction Model ◽  
Lateral Position ◽  
Lambert W Function ◽  
Speed Reduction ◽  
The Road ◽  
Adverse Impacts ◽  
Traffic Stream ◽  
Speed Prediction ◽  
Standard Section ◽  
Pedestrian Infrastructure

Pedestrian movements sharing right-of-way with vehicular traffic have adverse impacts on the mobility of the traffic stream. Pedestrian movements both along and across the road often force drivers of approaching vehicles either to stop completely or to slow down and change the existing lane. It ultimately results in a decrease in stream speed. With the aim of determining the influence of pedestrian movements, the present study collected traffic data at a standard section (without pedestrian movements) and both traffic and pedestrian data at a pedestrian section (with considerable pedestrian movements). To determine the speed at the standard section, this paper presents a novel ‘Lambert W function’-based speed prediction model in the context of a two-lane undivided urban road. When stream speeds of the pedestrian section were compared to the stream speeds obtained through the speed prediction model at the same traffic volume condition in absence of pedestrians, a significant reduction was observed. This reduction in stream speed is governed by pedestrian parameters. A new pedestrian parameter ‘lateral position of pedestrian from the edge while walking along the road’ was conceived in this study along with few other parameters to predict Percent Speed Reduction (PSR). Intensities of these pedestrian parameters were observed varying over time which results in a high fluctuation in PSR within a range of 29% to 62%. Finally, this investigation forwards an empirical model of Percent Speed Reduction (PSR) to predict the stream speed in the presence of on-street pedestrian movements on undivided urban roads. The outcome of this paper will help transport planners to estimate the efficiency of pedestrian infrastructure projects before implementation.

scholarly journals Joint Impact of Rain and Incidents on Traffic Stream Speeds

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Mohammed Elhenawy ◽  
Hesham A. Rakha ◽  
Huthaifa I. Ashqar
Keyword(s):  
Heavy Rain ◽  
Weather Conditions ◽  
Free Flow ◽  
Highway Traffic ◽  
Speed Reduction ◽  
Light Rain ◽  
The Road ◽  
Traffic Stream ◽  
Traffic Speed ◽  
The Relationship

Unpredictable and heterogeneous weather conditions and road incidents are common factors that impact highway traffic speeds. A better understanding of the interplay of different factors that affect roadway traffic speeds is essential for policymakers to mitigate congestion and improve road safety. This study investigates the effect of precipitation and incidents on the speed of traffic in the eastbound direction of I-64 in Virginia. To the best of our knowledge, this is the first study that studies the relationship between precipitation and incidents as factors that would have a combined effect on traffic stream speeds. Furthermore, using a mixture model of two linear regressions, we were able to model the two different regimes that the traffic speed could be classified into, namely, free-flow and congested. Using INRIX traffic data from 2013 through 2016 along a 25.6-mi section of Interstate 64 in Virginia, results show that the reduction of traffic speed only due to incidents ranges from 41% to 75% if the road is already congested. In this case, precipitation was found to be statistically insignificant. However, regardless of the incident impact, the effect of light rain in free-flow conditions ranges from insignificant to a 4% speed reduction while the effect of heavy rain ranges from a 0.6% to a 6.5% speed reduction when the incident severity is low but has a roughly double effect when the incident severity is high.

scholarly journals OPERATING SPEED PREDICTION MODEL AS A TOOL FOR CONSISTENCY BASED GEOMETRIC DESIGN OF FOUR-LANE DIVIDED HIGHWAYS

Transport ◽  
2019 ◽  
Vol 34 (4) ◽  
pp. 425-436 ◽  
Author(s):  
Gourab Sil ◽  
Avijit Maji ◽  
Suresh Nama ◽  
Akhilesh Kumar Maurya
Keyword(s):  
Prediction Model ◽  
Lateral Position ◽  
Geometric Design ◽  
Operating Speed ◽  
Vehicle Speed ◽  
Horizontal Curve ◽  
Passenger Cars ◽  
Horizontal Curves ◽  
Speed Prediction ◽  
Design Consistency

Researchers have studied two-lane rural highways to predict the operating speed on horizontal curves and correlated it with safety. However, the driving characteristics of four-lane-divided highways are different. Weak lane discipline is observed in these facilities, which influences vehicle speed in adjacent lane or space. So, irrespective of its lane or lateral position, vehicles in four-lane divided highways are considered free flowing only when it maintains the minimum threshold headway from any lead vehicle. Examination of two conditions is proposed to ensure the free flow. Vehicles meeting both conditions, when tracked from the preceding tangent section till the centre of the horizontal curve, are considered as free flowing. The speed data of such free flowing passenger cars at the centre of eighteen horizontal curves on four-lane divided highways is analysed to develop a linear operating speed prediction model. The developed model depends on curve radius and preceding tangent length. The operating speed of passenger car in four-lane divided highways is influenced by horizontal curve of radius 360 m or less. Further, longer tangent would yield higher operating speed at the centre of the curve. Finally, two nomograms are suggested for conventional design, consistency based design and geometric design consistency evaluation of four-lane divided horizontal curves.

Speed Prediction Model of Trucks on Gradient Sections Considering Vertical Curve

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Qianqian Liang ◽  
Xiaodong Zhang ◽  
Jinliang Xu ◽  
Yang Zhang
Keyword(s):  
Prediction Model ◽  
Speed Prediction

An application of backtracking search optimization–based least squares support vector machine for prediction of short-term wind speed

2019 ◽  
Vol 44 (3) ◽  
pp. 266-281 ◽  
Author(s):  
Zhongda Tian ◽  
Yi Ren ◽  
Gang Wang
Keyword(s):  
Support Vector Machine ◽  
Wind Speed ◽  
Prediction Model ◽  
Least Squares ◽  
Support Vector ◽  
Short Term ◽  
Backtracking Search ◽  
Wind Speed Prediction ◽  
Search Optimization ◽  
Speed Prediction

Wind speed prediction is an important technology in the wind power field; however, because of their chaotic nature, predicting wind speed accurately is difficult. Aims at this challenge, a backtracking search optimization–based least squares support vector machine model is proposed for short-term wind speed prediction. In this article, the least squares support vector machine is chosen as the short-term wind speed prediction model and backtracking search optimization algorithm is used to optimize the important parameters which influence the least squares support vector machine regression model. Furthermore, the optimal parameters of the model are obtained, and the short-term wind speed prediction model of least squares support vector machine is established through parameter optimization. For time-varying systems similar to short-term wind speed time series, a model updating method based on prediction error accuracy combined with sliding window strategy is proposed. When the prediction model does not match the actual short-term wind model, least squares support vector machine trains and re-establishes. This model updating method avoids the mismatch problem between prediction model and actual wind speed data. The actual collected short-term wind speed time series is used as the research object. Multi-step prediction simulation of short-term wind speed is carried out. The simulation results show that backtracking search optimization algorithm–based least squares support vector machine model has higher prediction accuracy and reliability for the short-term wind speed. At the same time, the prediction performance indicators are also improved. The prediction result is that root mean square error is 0.1248, mean absolute error is 0.1374, mean absolute percentile error is 0.1589% and R2 is 0.9648. When the short-term wind speed varies from 0 to 4 m/s, the average value of absolute prediction error is 0.1113 m/s, and average value of absolute relative prediction error is 8.7111%. The proposed prediction model in this article has high engineering application value.

scholarly journals A Novel Self-Adaptive Wind Speed Prediction Model Considering Atmospheric Motion and Fractal Feature

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 215892-215903
Author(s):  
Ji Jin ◽  
Bin Wang ◽  
Min Yu ◽  
Jiang Liu ◽  
Wenbo Wang
Keyword(s):  
Wind Speed ◽  
Prediction Model ◽  
Wind Speed Prediction ◽  
Speed Prediction ◽  
Atmospheric Motion ◽  
Self Adaptive

scholarly journals Wind Speed Prediction Model Using LSTM and 1D-CNN

2018 ◽  
Vol 22 (4) ◽  
pp. 207-210 ◽  
Author(s):  
Rui Fukuoka ◽  
Hiroshi Suzuki ◽  
Takahiro Kitajima ◽  
Akinobu Kuwahara ◽  
Takashi Yasuno
Keyword(s):  
Wind Speed ◽  
Prediction Model ◽  
Wind Speed Prediction ◽  
Speed Prediction

scholarly journals Traffic calming measures and their effect on the variation of speed

2016 ◽  
Author(s):  
Hernán Gonzalo Orden
Keyword(s):  
Urban Areas ◽  
Field Measurements ◽  
Speed Reduction ◽  
The Road ◽  
The North ◽  
Traffic Calming ◽  
Road Users ◽  
Technical Basis ◽  
Serious Injuries ◽  
North Of Spain

In recent years the number of deaths and serious injuries is decreasing in Spain, but, although the reduction outside the cities has been very strong, inside the urban areas, it has been smaller. This is especially hard if you look at the most vulnerable road users such as pedestrians and cyclists. In many accidents the speed factor appears closely linked not only to the number, but also to the severity of the accidents suffered inside the urban areas. Therefore, a reduction in the speed would improve the road safety. There are different measures known as "traffic calming measures" whose objectives are to reduce both the number and severity of accidents that occur on urban areas, by reducing the traffic flow through the streets, as well as the speed of the vehicles. However, the efficiency in speed reduction of each measure is not entirely known. That's the reason why they are implanted, in many cases, with no technical basis. The aim of this article is to show the effectiveness in reducing speed of some of the traffic calming measures. To this effect, field measurements were done on street sections with different types of traffic calming measures, in different places of a city of Burgos, in the north of Spain. These measurements were compared with other ones sited on other streets sections of similar characteristics but without traffic calming measures. Finally the conclusions are shown and some recommendations for improving their effectiveness are given.DOI: http://dx.doi.org/10.4995/CIT2016.2016.4217

scholarly journals Speed Models for Motorcycle Riders for Two-lane Rural Roads

2021 ◽  
Vol 17 ◽  
pp. 595-603
Author(s):  
Panagiotis Lemonakis ◽  
George Botzoris ◽  
Athanasios Galanis ◽  
Nikolaos Eliou
Keyword(s):  
Prediction Models ◽  
Flow Speed ◽  
Operating Speed ◽  
Rural Roads ◽  
The Road ◽  
Horizontal Curves ◽  
Road Geometry ◽  
Speed Prediction ◽  
The Subject ◽  
On The Road

The development of operating speed models has been the subject of numerous research studies in the past. Most of them present models that aim to predict free-flow speed in conjunction with the road geometry at the curved road sections considering various geometric parameters e.g., radius, length, preceding tangent, deflection angle. The developed models seldomly take into account the operating speed profiles of motorcycle riders and hence no significant efforts have been put so far to associate the geometric characteristics of a road segment with the speed behavior of motorcycle riders. The dominance of 4-wheel vehicles on the road network led the researchers to focus explicitly on the development of speed prediction models for passenger cars, vans, pickups, and trucks. However, although the motorcycle fleet represents only a small proportion of the total traffic volume motorcycle riders are over-represented in traffic accidents especially those that occur on horizontal curves. Since operating speed has been thoroughly documented as the most significant precipitating factor of vehicular accidents, the study of motorcycle rider's speed behavior approaching horizontal curves is of paramount importance. The subject of the present paper is the development of speed prediction models for motorcycle riders traveling on two-lane rural roads. The model was the result of the execution of field measurements under naturalistic conditions with the use of an instrumented motorcycle conducted by experienced motorcycle riders under different lighting conditions. The implemented methodology to determine the most efficient model evaluates a series of road geometry parameters through a comprehensive literature review excluding those with an insignificant impact to the magnitude of the operating speeds in order to establish simple and handy models.

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