Familiar versus Unfamiliar Drivers on Curves: Naturalistic Data Study

2019 ◽  
Vol 2673 (6) ◽  
pp. 225-235 ◽  
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.

Studying Driving Behavior on Horizontal Curves using Naturalistic Driving Study Data

2018 ◽  
Vol 2672 (17) ◽  
pp. 83-95 ◽  
Author(s):  
Bashar Dhahir ◽  
Yasser Hassan
Keyword(s):  
Data Collection ◽  
Weather Conditions ◽  
Driving Behavior ◽  
Study Data ◽  
Output Analysis ◽  
Horizontal Curves ◽  
Naturalistic Driving Study ◽  
Naturalistic Driving ◽  
Design Consistency ◽  
Favorable Weather

Many studies have been conducted to develop models to predict speed and driver comfort thresholds on horizontal curves, and to evaluate design consistency. The approaches used to develop these models differ from one another in data collection, data processing, assumptions, and analysis. However, some issues might be associated with the data collection that can affect the reliability of collected data and developed models. In addition, analysis of speed behavior on the assumption that vehicles traverse horizontal curves at a constant speed is far from actual driving behavior. Using the Naturalistic Driving Study (NDS) database can help overcome problems associated with data collection. This paper aimed at using NDS data to investigate driving behavior on horizontal curves in terms of speed, longitudinal acceleration, and comfort threshold. The NDS data were valuable in providing clear insight on drivers’ behavior during daytime and favorable weather conditions. A methodology was developed to evaluate driver behavior and was coded in Matlab. Sensitivity analysis was performed to recommend values for the parameters that can affect the output. Analysis of the drivers’ speed behavior and comfort threshold highlighted several issues that describe how drivers traverse horizontal curves that need to be considered in horizontal curve design and consistency evaluation.

The Sooner the Better: Drivers’ Reactions to Two-Step Take-Over Requests in Highly Automated Driving

2018 ◽  
Vol 62 (1) ◽  
pp. 1883-1887 ◽  
Author(s):  
Sandra Epple ◽  
Fabienne Roche ◽  
Stefan Brandenburg
Keyword(s):  
Human Factors ◽  
Situational Awareness ◽  
Driver Behavior ◽  
Reaction Times ◽  
Vehicle Control ◽  
Driving Behavior ◽  
Second Step ◽  
Automated Driving ◽  
One Step ◽  
Highly Automated Driving

Driving behavior after take-over requests (TORs) is one of the most popular subjects in human factors re-search on highly automated driving. Many studies utilized one-step TOR procedures to prompt drivers to resume vehicle control. The present paper examines driver behavior when experiencing a two-step TOR procedure in different modalities. A two-step TOR gives drivers a choice to resume vehicle controls be-tween a warning (first step) and an alarm (second step). Our findings indicate that a substantial number of drivers resumes vehicle controls after the second step, resulting in a higher number of crashes. More generally, criticality of the driving situation increases with increasing reaction times. Driving and interview data suggest that step two of the TOR should be presented earlier. Alternatively, a multi-step TOR could be used to increase drivers’ situational awareness. Auditory TORs are associated with shorter reaction times than visual-auditory TORs. Implications on TOR design are discussed.

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

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.

Operating speed models for two-lane rural roads in Pakistan

2008 ◽  
Vol 35 (5) ◽  
pp. 443-453 ◽  
Author(s):  
Rizwan A. Memon ◽  
G. B. Khaskheli ◽  
A. Sami Qureshi
Keyword(s):  
Global Positioning System ◽  
Prediction Models ◽  
Geometric Design ◽  
Operating Speed ◽  
Rural Roads ◽  
Horizontal Curves ◽  
Measuring Devices ◽  
Global Positioning ◽  
Speed Prediction ◽  
Design Consistency

One of the suitable techniques used to improve safety on roads is to check the consistency of geometric design. The concept of design consistency has emerged worldwide, but no research has been found to date on design consistency in Pakistan. The most common parameter for the evaluation of design consistency is operating speed. Several models have been developed to predict operating speed on two-lane rural roads. However, these models were based on spot speed data collected through traditional speed measuring devices. This study uses continuous speed profile data collected using a vehicle equipped with a VBox (a global positioning system based device). Eleven test sections were selected in two provinces of Pakistan (i.e., Sindh and Balochistan). Driver behavior is also studied in the present research. Models were developed for prediction of operating speed on horizontal curves and on tangents. Validation of the developed models shows compatibility with the experimental data; hence, the developed speed prediction models can be used to evaluate the geometric design consistency of two-lane rural roads in Pakistan.

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.

scholarly journals Driver Behavior on Combination of Vertical and Horizontal Curves of Mountainous Freeways

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Tao Chen ◽  
Miao Zhang ◽  
Lang Wei
Keyword(s):  
Prediction Model ◽  
Traffic Safety ◽  
Driver Behavior ◽  
Free Flow ◽  
Test Results ◽  
Horizontal Curves ◽  
Speed Measurement ◽  
Speed Prediction ◽  
Verification Test ◽  
Vehicle Size

The study of driver behavior is of great importance to the traffic safety of mountainous freeways. In order to study the characteristics of driver behavior on combination of vertical and horizontal curves (CVHCs) of mountainous freeways in free flow conditions, designated speed measurement tests of two typical segments of the upgrade direction of Xi’an-Hanzhong freeway were carried out. After data processing, vehicles in free flow were screened out and classified into two groups by K-means clustering method, and then the driver behavior with different lanes, different size vehicles, and different CVHCs was analyzed, respectively. Finally, a vehicle distribution prediction model and a speed prediction model were built which were applied to CVHCs, and a verification test was made to test the accuracy of the models. Research results show that the driver behavior is mainly different among vehicle size, longitudinal slopes, and horizontal curves, and the characteristics of speed control and lane distribution on CVHCs vary according to lanes and combination of road alignment. Also, the prediction results of the models are highly consistent with the measured test results.

Speed Prediction Models for Trucks on Horizontal Curves of Two-Lane Rural Roads

2018 ◽  
Vol 2672 (17) ◽  
pp. 72-82 ◽  
Author(s):  
David Llopis-Castelló ◽  
Brayan González-Hernández ◽  
Ana María Pérez-Zuriaga ◽  
Alfredo García
Keyword(s):  
Road Safety ◽  
Prediction Models ◽  
Gps Tracking ◽  
Heavy Vehicle ◽  
Heavy Vehicles ◽  
Passenger Cars ◽  
Rural Roads ◽  
Horizontal Curves ◽  
Speed Prediction ◽  
Design Consistency

Road safety is closely related to geometric design consistency, which is usually assessed by examining operating speed. Most consistency models only consider passenger car speeds, even though the interaction between passenger cars and heavy vehicles plays a pivotal role in road safety. This is due to the fact that there are too few models to estimate heavy vehicle speeds. This study aims to develop speed prediction models for heavy vehicles on horizontal curves of two-lane rural roads. To do this, continuous speed profiles were collected by using Global Positioning System (GPS) tracking devices on 11 road sections. Truck speeds were analyzed on 105 horizontal curves. The results showed that the radius of the horizontal curve and the grade at the point of curvature have a significant influence on heavy vehicle speeds. In this regard, vertical alignment only has a significant effect on truck speeds along upgrades. In addition, different trends were identified for loaded and unloaded trucks, so different speed models were calibrated for each of them. As a result, heavy vehicle speeds were adversely affected by grades greater than 3%. This phenomenon was larger for loaded trucks than for unloaded ones. Finally, the calibrated 85th and 15th percentile speed models were compared with those developed previously. As a conclusion, the use of the proposed models in this study was recommended on Spanish two-lane rural roads due mainly to the different characteristics of heavy vehicles around the world.

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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