Available sight distance on existing highways: Meeting stopping sight distance requirements of an aging population

Gargoum, Suliman; Tawfeek, Mostafa H.; El-Basyouny, Karim; Koch, James C.

doi:10.1016/j.aap.2018.01.001

Cited by 21 publications

(9 citation statements)

References 22 publications

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“…For example, one study 14 indicated that the maximum highway volume and free flow speed are affected more strongly as the rainfall intensity increases. Compared with the case of normal weather, the maximum flow rate decreases by 15.7%, 19.1%, and 32.5% and the free flow speed decreases by 4.4%, 7.3%, and 10.6% in light rain, moderate rain and heavy rain weather conditions, respectively. Another study 15 conducted research on the impact of rainfall on freeway traffic flow.…”

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confidence: 79%

“…From the data, the average observed free-speed values were 14.68 km/h and 21.44 km/h under high and low water film conditions, respectively. According to the type P205/55R16 tire and passenger car specifications, the total vehicle load W was 1.469 tf (14.4 kN).The width of a car was taken as 2 m, and the height of a car was taken as 1.5 m. The tire-road coefficient of friction under the wet condition f o was set to 0.35 based on the poor driving conditions resulting from wet roads 19 . Poor conditions in this study are defined as conditions where (1) a road is covered by standing water, which results in poor surface traction, and (2) drivers are less likely to apply similar pressure to brake pedals compared to their response in dry conditions.…”

Section: Data Collectionmentioning

confidence: 99%

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Modelling fundamental diagrams according to different water film depths from the perspective of the dynamic hydraulic pressure

Liu

Chiaki

Oeda

et al. 2020

Sci Rep

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In this paper, we propose enhanced fundamental diagrams based on different water film depths by considering the effects of hydroplaning using a physical method. Various factors are calculated to describe the total safe distance headway of main vehicle components. These factors include the driver reaction times, reaction distances, vehicle braking times, and vehicle braking distances corresponding to different water film depths. An excellent match is found between the computed braking distance, the braking time calculated using the proposed numerical model, and the results published in other papers. These calculations are performed to estimate the distance headway and quantitatively analyse the relationships between the speed, density, and water film depth. By using three road-specific parameters estimated by our proposed model, namely, the free-flow speed, jam density, and capacity flow, a link transmission model is developed to analyse the dynamic impact of the water film depth.Urban flooding is one of the most severe types of flooding in terms of economic damage, health impact, and loss of life. It has become a significant challenge for the development and sustainability of coastal cities. Under more frequent extreme weather conditions, floods and inundations become more severe. For example, devastating torrential rains and subsequent flooding in western Japan left over 200 people dead in 2018. Evacuation can be an efficient solution for securing human safety in major disasters. One effective method for handling the consequences of hydrological disasters is to establish a prudent and comprehensive emergency management plan. Recently, several studies 1,2 , have attempted to model potential network capacity losses to estimate evacuation times from a probabilistic perspective. The objective of these studies was to estimate reliable evacuation times under realistic transportation network conditions.Despite the fact that evacuation environments in flood conditions are typically characterised by great risk (road capacities and vehicle speeds may be reduced by water film depth), very few studies in the evacuation literature have explicitly considered this type of risk. A traffic model for representing traffic flow characteristics according to different water film depths is necessary to represent the traffic situation during emergency evacuations accurately. However, research in this field is very limited, especially regarding the evaluation of the influence of the water film depth. Therefore, it is essential to re-evaluate and enhance urban transportation planning models to capture the effects of flooding disasters related to water depth.All traffic situations in the real world can be considered combinations of homogenous states, meaning they can be described by essential traffic flow characteristics (e.g., flow Q, speed V, and density K). Fundamental diagrams capture the relationships between these characteristics and play an essential role in traffic flow theory and transportation engineering. Various models have be...

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confidence: 79%

Section: Data Collectionmentioning

confidence: 99%

Modelling fundamental diagrams according to different water film depths from the perspective of the dynamic hydraulic pressure

Liu

Chiaki

Oeda

et al. 2020

Sci Rep

View full text Add to dashboard Cite

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“…A study by the Kentucky Transportation Cabinet and FHWA (6) found that U-turn design is very effective in reducing the delays and crash rates at stopped controlled median openings; thus, the potential cause of a higher crash rate for a U-turn may be insufficient SD. Other studies on SD include: Awadallah (7), which developed the guidelines for three types of ISDs (i.e., approach SD, sign visibility SD, and stop-line distance); NCHRP Report 650 (8), which developed guidelines on SD for median intersection design for rural high-speed divided highways; and Gargoum et al (9), which pointed out that different age groups have different requirements for SD. None of these studies, however, provide standard SDs for U-turn movements.…”

Section: Definition Of Sdmentioning

confidence: 99%

Developing a Google Earth-Based Method to Measure Sight Distance for U-Turns at Unsignalized Intersections on Multilane Divided Highways

Zhang

Zhou

et al. 2021

Transportation Research Record

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The median U-turn is one of the most popular access management techniques implemented by state transportation agencies. Sight distance (SD) is among the key elements for the safe operation of median U-turns. The traditional method of measuring SD is using sight rods in the field, which is inconvenient and unsafe; thus, it is important to develop a convenient and safer method to measure SD for U-turn movement. The objective of this study is to develop a safe and cost-effective method to measure SD for U-turn vehicles, without going into the field, using existing tools in Google Earth and a perspective grid method that can be generated by Kinovea software. The method can be used in two different road geometric conditions: (i) a straight segment with crest curves; (ii) a roadway with a combination of crest curves and horizontal curves. For Condition (i), an empirical equation was developed to estimate SD as a function of distance and elevation along the sight line measured using Google Earth. For Condition (ii), a perspective grid was first applied using Google Earth ground-level view; then the number of broken lines and gaps in each perspective grid cell was used to measure the SD. All inputs can be collected using Google Earth. Field measurements of SD for U-turns at 10 selected locations were conducted to verify the validity of the method. The results show that the differences between the model estimates and field measurements are all less than 10%.

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“…Charbonnier et al (2010) compared a method for sight-distance evaluation using LiDAR with another method that was based on photogrammetric restitution of roadway perspectives and with field verification using vehicles. To model the terrain and landscape features, a raster elevation model may be used (Castro et al 2011;Gargoum et al 2018). Otherwise, a triangular irregular network (TIN) could be created from the point clouds, thereby building a surface of nonoverlapping triangles that connected the points.…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Virtual Highway Model for Sight-Distance Evaluation of Highway Underpasses

Santos-Berbel

Castro

2018

J. Surv. Eng.

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When it comes to the safe design and operation of highways, sight distance is of utmost importance. The estimation of sight distance must be performed taking the three-dimensional (3D) nature of roadways and related features into account. Horizontal curves and crest vertical curves were the common sight restrictions considered in highway design. However, overhanging features may also affect sight distance. This paper presents a 3D virtual model for evaluating sight distance on sites where overpass structures restrict sight distance and for detecting sight-distance-related issues. The procedure and inputs for the computation of sight distance are described as are the results, which were validated and applied to a case study of an in-service highway underpass. Stopping sight distance and passing sight distance were evaluated for a section of highway with specific sight-distance characteristics of overpasses. The effect of the observer and target heights on sight distance for underpasses proved the opposite of those on horizontal curves and crests. Near an overpass, the heights should be switched from those used on curves and crests to evaluate stopping and passing sight distance according to operational and safety criteria. Finally, the currently existing passing zones were evaluated by means of the results obtained, revealing possible deficiencies in the establishment of passing zones. individual papers. This paper is part of the Journal of Surveying Engineering, © ASCE, ISSN 0733-9453. © ASCE 05018003-1 J. Surv. Eng. J. Surv. Eng., 2018, 144(4): 05018003 Downloaded from ascelibrary.org by 44.224.250.200 on 07/10/20. Copyright ASCE. For personal use only; all rights reserved. © ASCE 05018003-4 J. Surv. Eng. J. Surv. Eng., 2018, 144(4): 05018003 Downloaded from ascelibrary.org by 44.224.250.200 on 07/10/20. Copyright ASCE. For personal use only; all rights reserved. © ASCE 05018003-6 J. Surv. Eng. J. Surv. Eng., 2018, 144(4): 05018003 Downloaded from ascelibrary.org by 44.224.250.200 on 07/10/20. Copyright ASCE. For personal use only; all rights reserved. © ASCE 05018003-8 J. Surv. Eng.

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Available sight distance on existing highways: Meeting stopping sight distance requirements of an aging population

Cited by 21 publications

References 22 publications

Modelling fundamental diagrams according to different water film depths from the perspective of the dynamic hydraulic pressure

Modelling fundamental diagrams according to different water film depths from the perspective of the dynamic hydraulic pressure

Developing a Google Earth-Based Method to Measure Sight Distance for U-Turns at Unsignalized Intersections on Multilane Divided Highways

Three-Dimensional Virtual Highway Model for Sight-Distance Evaluation of Highway Underpasses

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