Evaluating Relationships between Perception-Reaction Times, Emergency Deceleration Rates, and Crash Outcomes using Naturalistic Driving Data

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198120966602 ◽

2020 ◽

pp. 036119812096660

Author(s):

Jonathan S. Wood ◽

Shaohu Zhang

Keyword(s):

Real World ◽

Predictive Models ◽

Prediction Models ◽

Reaction Times ◽

Deceleration Rate ◽

Sight Distance ◽

Naturalistic Driving ◽

Design Speed ◽

Stopping Sight Distance ◽

Roadway Design

Perception-reaction time (PRT) and deceleration rate are two key components in geometric design of highways and streets. Combined with a design speed, they determine the minimum required stopping sight distance (SSD). Current American Association of Highway Transportation Officials (AASHTO) SSD guidance is based on 90th percentile PRT and 10th percentile deceleration rate values from experiments completed in the mid-1990s. These experiments lacked real-world distractions, and so forth. Thus, the values from these experiments may not be applicable in real-world scenarios. This research evaluated (1) differences in PRTs and deceleration rates between crash and near-crash events and (2) developed predictive models for PRT and deceleration rate that could be used for roadway design. This was accomplished using (1) genetic matching (with Rosenbaum’s sensitivity analysis) and (2) quantile regression. These methods were applied to the Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study (NDS) data. The analysis results indicated that there were differences in PRT and deceleration rates for crash and near-crash events. The specific estimates were that, on average, drivers involved in crash events took 0.487 s longer to react and decelerated at 0.018 g’s (0.58 ft/s2) slower than drivers in equivalent near-crashes. Prediction models were developed for use in roadway design. These models were used to develop tables comparing existing SSD design criteria with SSD criteria based on the results of the predictive models. These predicted values indicated that minimum design SSD values would increase by 10.5–129.2 ft, dependent on the design speed and SSD model used.

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Location-based analysis of car-following behavior during braking using naturalistic driving data

Canadian Journal of Civil Engineering ◽

10.1139/cjce-2019-0314 ◽

2020 ◽

Vol 47 (5) ◽

pp. 498-505 ◽

Cited By ~ 2

Author(s):

Mostafa H. Tawfeek ◽

Karim El-Basyouny

Keyword(s):

Driver Assistance Systems ◽

Behavioral Measures ◽

Car Following ◽

Sight Distance ◽

Influence Area ◽

Data Source ◽

Naturalistic Driving ◽

Stopping Sight Distance ◽

Microscopic Modeling ◽

Rich Data

This study investigates the car-following behavior during braking at intersections and segments. Car-following events were extracted from a naturalistic driving dataset, mapped using ArcGIS, and analyzed to differentiate between the intersection- and segment-related events. The intersection-related events were identified according to an intersection influence area, which was estimated based on the stopping sight distance and the speed limit. Five behavioral measures were quantified based on exploring the probability density functions (PDF) for intersection- and segment-related events. The results showed that there were significant differences between the PDFs of the measures for both cases. Moreover, it was indicated that drivers tend to be more aggressive at intersections compared with segments. Thus, it is crucial to consider the driver’s location when investigating driver behavior. The quantified behavioral measures are a rich data source that can be used for car-following microscopic modeling, surrogate safety analysis, and driver assistance systems development.

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Driver Perception–Brake Response in Stopping Sight Distance Situations

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1628-01 ◽

1998 ◽

Vol 1628 (1) ◽

pp. 1-7 ◽

Cited By ~ 34

Author(s):

Daniel B. Fambro ◽

Rodger J. Koppa ◽

Dale L. Picha ◽

Kay Fitzpatrick

Keyword(s):

Response Time ◽

Performance Studies ◽

Response Times ◽

Highway Design ◽

Braking Performance ◽

Reaction Distance ◽

State Highway ◽

Sight Distance ◽

Design Speed ◽

Stopping Sight Distance

One of the most important requirements in highway design is the provision of adequate stopping sight distance at every point along the roadway. At a minimum, this sight distance should be long enough to enable a vehicle traveling at or near the design speed to stop before reaching a stationary object in its path. Stopping sight distance is the sum of two components–brake reaction distance and braking distance. Brake reaction distance is based on the vehicle’s speed and the driver’s perception–brake reaction time (PBRT). Four separate, but coordinated, driver braking performance studies measured driver perception–brake response to several different stopping sight distance situations. The results from the driver braking performance studies suggest that the mean perception–brake response time to an unexpected object scenario under controlled and open road conditions is about 1.1 s. The 95th percentile perception–brake response times for these same conditions was 2.0 s. The findings from these studies are consistent with those in the literature: that is, most drivers are capable of responding to an unexpected hazard in the roadway in 2.0 s or less. Thus, the American Association of State Highway and Transportation Officials’ perception–brake response time of 2.5 s encompasses most of the driving population and is an appropriate value for highway design.

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Operating Speed on Crest Vertical Curves with Limited Stopping Sight Distance

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1701-04 ◽

2000 ◽

Vol 1701 (1) ◽

pp. 25-31 ◽

Cited By ~ 7

Author(s):

Daniel B. Fambro ◽

Kay Fitzpatrick ◽

Charles W. Russell

Keyword(s):

Operating Speed ◽

Design Elements ◽

Geometric Data ◽

A Value ◽

Sight Distance ◽

The Mean ◽

The Difference ◽

Design Speed ◽

Stopping Sight Distance ◽

The Relationship

Horizontal and vertical elements of a highway are designed based on an assumed design speed. This concept was developed in the 1930s as a mechanism for designing rural alignments to permit most drivers to operate uniformly at their desired speed. In 1938, AASHO recognized that drivers select a speed influenced by the roadway environment instead of an assumed design speed. Recent research suggests that design speed is no longer the speed adopted by the faster group of drivers but that it has become a value used to establish the sharpness of horizontal and vertical design elements. The objective of this study was to establish the relationship between design and operating speeds for crest vertical curves with limited sight distance. Geometric data and 3,500 paired speeds (speeds at control and crest sections) were collected at 36 sites in 3 states. The results indicated that both the 85th percentile and the mean operating speeds were well above the inferred design speeds of the crest vertical curves for the range of conditions studied and that the lower the design speed the larger the difference between the 85th percentile speed and the design speed. The mean reductions in speed between the control and crest sections tend to increase as available sight distance is decreased; however, the reduction in speed is less than that suggested by current AASHTO criteria.

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Building an Integrated Database of Road Design Elements

Geographic Information Systems in Geospatial Intelligence ◽

10.5772/intechopen.88678 ◽

2020 ◽

Author(s):

Ali Dhafer Abed

Keyword(s):

Road Network ◽

Design Elements ◽

Northern Iraq ◽

The Road ◽

Sight Distance ◽

Sensing Technology ◽

Design Speed ◽

Stopping Sight Distance ◽

City Structure ◽

The City

The road network is the main artery within the city structure, which requires designing of routes and classification within the standards. Hence, the importance of this chapter, which will focus on the standards and design elements of the engineering design of road in terms of road type system, functional classification system, traffic volume system, number of traffic lane system, road width design, side slopes and elevations of road layers, super elevation, design speed, overtaking and stopping sight distance, longitudinal and cross sections of the road path, design elements of horizontal and vertical curves, and intersections. The Civil 3D Land Desktop, GIS programs, and remote sensing technology will be used to design the path of major highway linking two urban areas in Mosul (Northern Iraq), which will be considered a case study. The path of the road and its elements will be designed according to special criteria that are compatible with the topography and nature of the area. The geometric data of the road will then be exported with all the design elements to the GIS program to build an integrated road database. The database is capable of spatial analysis and connectivity with other parts of the road network in the city.

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Empirical modeling of the relationship between decision sight distance and stopping sight distance based on AASHTO

Archives of Transport ◽

10.5604/01.3001.0012.8362 ◽

2018 ◽

Vol 4 (48) ◽

pp. 7-25

Author(s):

Shy BASSAN

Keyword(s):

Friction Coefficient ◽

Empirical Relationship ◽

Design Guidelines ◽

Empirical Modeling ◽

Highway Design ◽

Deceleration Rate ◽

Sight Distance ◽

Rough Approximation ◽

Stopping Sight Distance ◽

The Relationship

The paper introduces implementation of highways' stopping sight distance (SSD) and decision sight distance (DSD) based on AASHTO modeling assumptions. SSD characterizes the necessary distance for highway vehicles to stop safely in front from an obstacle. SSD is a function of vehicle speed, perception reaction time, deceleration rate, and grade based on AASHTO and most highway design international guidelines. The deceleration rate which is assumed constant (3.4 m/sec2) based on AASHTO 2011 is generally controlled by the friction coefficient depending on the road surface conditions. A driver's demanded deceleration rate may not exceed the range of friction coefficient according to various pavement conditions. Although SSD is generally sufficient to allow skilled and alert drivers to the stop their vehicles under regular situations, this distance is insufficient when information is difficult to comprehend. A DSD should be provided in highways geometric design when the driver is required to detect an unexpected or difficult to perceive information source. Interchanges (specifically exit ramps) and intersections, and required changing in driver direction of travel, changes in the basic cross section such as toll plaza, lane drop, are typical scenarios where driver needs DSD in the safety manner. The introduction of the two sight distance types (SSD and DSD) is a perquisite for empirical modeling of the relationship between DSD and SSD. The modeling refers to DSD for rural highways, suburban roads, and urban roads based on AASHTO models. Specifically the paper covers DSD three avoidance maneuver types of stopping (types A, A1, B) and three maneuver types of speed, path, and direction changing (types C,D, E) for the three roadway categories. The major parameters that control these avoidance types are pre-maneuver times, and pre-maneuver plus maneuver times. The empirical relationship proposed in this study simplifies the process of evaluating the decision sight distance based on stopping sight distance record, based on AASHTO models, without the need of strenuous estimation of the DSD model maneuver and deceleration parameters. Such a simplified correlation has not been found in the literature except a rough approximation documented in the British highway design guidelines.

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Familiar versus Unfamiliar Drivers on Curves: Naturalistic Data Study

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198119846481 ◽

2019 ◽

Vol 2673 (6) ◽

pp. 225-235 ◽

Cited By ~ 1

Author(s):

Michael P. Pratt ◽

Srinivas R. Geedipally ◽

Bahar Dadashova ◽

Lingtao Wu ◽

Mohammadali Shirazi

Keyword(s):

Human Factors ◽

Peripheral Vision ◽

Driver Behavior ◽

Reaction Times ◽

Horizontal Curves ◽

Speed Prediction ◽

Naturalistic Driving ◽

Design Consistency ◽

Roadway Design ◽

Rural Highway

Human factors studies have shown that route familiarity affects driver behavior in various ways. Specifically, when drivers become more familiar with a roadway, they pay less attention to signs, adopt higher speeds, cut curves more noticeably, and exhibit slower reaction times to stimuli in their peripheral vision. Numerous curve speed models have been developed for purposes such as predicting driver behavior, evaluating roadway design consistency, and setting curve advisory speeds. These models are typically calibrated using field data, which gives information about driver behavior in relation to speed and sometimes lane placement, but does not provide insights into the drivers themselves. The objective of this paper is to examine the differences between the speeds of familiar and unfamiliar drivers as they traverse curves. The authors identified four two-lane rural highway sections in the State of Indiana which include multiple horizontal curves, and queried the Second Strategic Highway Research Program (SHRP2) database to obtain roadway inventory and naturalistic driving data for traversals through these curves. The authors applied a curve speed prediction model from the literature to predict the speed at the curve midpoints and compared the predicted speeds with observed speeds. The results of the analysis confirm earlier findings that familiar drivers choose higher speeds through curves. The successful use of the SHRP2 database for this analysis of route familiarity shows that the database can facilitate similar efforts for a wider range of driver behavior and human factors issues.

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The variability of urban safety performance functions for different road elements: an Italian case study

European Transport Research Review ◽

10.1186/s12544-021-00490-6 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Paolo Intini ◽

Nicola Berloco ◽

Gabriele Cavalluzzi ◽

Dominique Lord ◽

Vittorio Ranieri ◽

...

Keyword(s):

Negative Binomial ◽

Prediction Models ◽

Safety Performance ◽

Common Trends ◽

Main Research ◽

Pavement Markings ◽

Italian Case ◽

Sight Distance ◽

Safety Performance Functions ◽

Urban Safety

Abstract Background Urban safety performance functions are used to predict crash frequencies, mostly based on Negative Binomial (NB) count models. They could be differentiated for considering homogeneous subsets of segments/intersections and different predictors. Materials and methods The main research questions concerned: a) finding the best possible subsets for segments and intersections for safety modelling, by discussing the related problems and inquiring into the variability of predictors within the subsets; b) comparing the modelling results with the existing literature to highlight common trends and/or main differences; c) assessing the importance of additional crash predictors, besides traditional variables. In the context of a National research project, traffic volumes, geometric, control and additional variables were collected for road segments and intersections in the City of Bari, Italy, with 1500 fatal+injury related crashes (2012–2016). Six NB models were developed for: one/two-way homogeneous segments, three/four-legged, signalized/unsignalized intersections. Results Crash predictors greatly vary within the different subsets considered. The effect of vertical signs on minor roads/driveways, critical sight distance, cycle crossings, pavement/markings maintenance was specifically discussed. Some common trends but also differences in both types and effect of crash predictors were found by comparing results with literature. Conclusion The disaggregation of urban crash prediction models by considering different subsets of segments and intersections helps in revealing the specific influence of some predictors. Local characteristics may influence the relationships between well-established crash predictors and crash frequencies. A significant part of the urban crash frequency variability remains unexplained, thus encouraging research on this topic.

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Determination of minimum horizontal curve radius for safe stopping sight distance of vehicles overpassing truck platoons

Computer-Aided Civil and Infrastructure Engineering ◽

10.1111/mice.12758 ◽

2021 ◽

Author(s):

Alfredo Garcia ◽

Daniel Pastor‐Serrano

Keyword(s):

Horizontal Curve ◽

Sight Distance ◽

Stopping Sight Distance ◽

Curve Radius

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Sight distance red zones on combined horizontal and sag vertical curves

Canadian Journal of Civil Engineering ◽

10.1139/l97-127 ◽

1998 ◽

Vol 25 (4) ◽

pp. 621-630 ◽

Cited By ~ 3

Author(s):

Yasser Hassan ◽

Said M Easa

Keyword(s):

Quantitative Analysis ◽

Three Dimensional ◽

The Other ◽

Two Dimensional ◽

Horizontal Curve ◽

Sight Distance ◽

Stopping Sight Distance ◽

Three Dimensional Models ◽

Highway Alignment ◽

Current Standards

Coordination of highway horizontal and vertical alignments is based on subjective guidelines in current standards. This paper presents a quantitative analysis of coordinating horizontal and sag vertical curves that are designed using two-dimensional standards. The locations where a horizontal curve should not be positioned relative to a sag vertical curve (called red zones) are identified. In the red zone, the available sight distance (computed using three-dimensional models) is less than the required sight distance. Two types of red zones, based on stopping sight distance (SSD) and preview sight distance (PVSD), are examined. The SSD red zone corresponds to the locations where an overlap between a horizontal curve and a sag vertical curve should be avoided because the three-dimensional sight distance will be less than the required SSD. The PVSD red zone corresponds to the locations where a horizontal curve should not start because drivers will not be able to perceive it and safely react to it. The SSD red zones exist for practical highway alignment parameters, and therefore designers should check the alignments for potential SSD red zones. The range of SSD red zones was found to depend on the different alignment parameters, especially the superelevation rate. On the other hand, the results showed that the PVSD red zones exist only for large values of the required PVSD, and therefore this type of red zones is not critical. This paper should be of particular interest to the highway designers and professionals concerned with highway safety.Key words: sight distance, red zone, combined alignment.

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