Rural Road Segments Research Articles

IMPACT OF RURAL ROAD PROVISION ON EMPLOYMENT

This article focuses on the impact of rural road provision on the macroeconomic objective of full employment. It deals with the extent to which roads act as direct generators of jobs during their construction and service periods, and the ways in which effective roads could indirectly stimulate employment opportunities quantitatively and, from a skills perspective, qualitatively. The economic impact analysis (ECIA) of road provision indicates the typical worker–hour requirements for the approximate estimation of employment needs. These estimates can be used whenever detailed estimates are not yet available. The estimates are provided for the construction and operation of (1) basic rural road segments, (2) bridges and viaducts, and (3) intersections, roundabouts (traffic circles), and interchanges. Where road projects contain other physical components, such as tunnels and toll plazas, the former three groups of employment rates could be used in combination with worker–hour estimates for the construction and maintenance of tunnels and toll-related components.

Multivariate Regression of Road Segments’ Accident Data in Italian Rural Networks

Increasing traffic flows on road infrastructures and the associated comfort and safety problems have led to an increased risk of accidents for road users. To take the proper corrective actions, it is fundamental to analyze the accident phenomenon in all its aspects. The purpose of the current paper was the development of an accident prediction model for rural road segments of Friuli-Venezia Giulia (FVG) Region. The model predicts the accident frequency as a function of Annual Average Daily Traffic (AADT), segment length, and both geometrical and environmental features related to the targeted road segment. The procedure is based on the Empirical Bayes (EB) method. The statistical model used to express the road segments’ safety was the multivariate regression structure of the Safety Performance Functions. Results of a CURE plots analysis verified that the model is highly reliable in predicting the accident dataset for AADT up to 12500 vehicles per day.

Automatic Rural Road Centerline Detection and Extraction from Aerial Images for a Forest Fire Decision Support System

To effectively manage the terrestrial firefighting fleet in a forest fire scenario, namely, to optimize its displacement in the field, it is crucial to have a well-structured and accurate mapping of rural roads. The landscape’s complexity, mainly due to severe shadows cast by the wild vegetation and trees, makes it challenging to extract rural roads based on processing aerial or satellite images, leading to heterogeneous results. This article proposes a method to improve the automatic detection of rural roads and the extraction of their centerlines from aerial images. This method has two main stages: (i) the use of a deep learning model (DeepLabV3+) for predicting rural road segments; (ii) an optimization strategy to improve the connections between predicted rural road segments, followed by a morphological approach to extract the rural road centerlines using thinning algorithms, such as those proposed by Zhang–Suen and Guo–Hall. After completing these two stages, the proposed method automatically detected and extracted rural road centerlines from complex rural environments. This is useful for developing real-time mapping applications.

Evaluation of the Influence of Road Geometry on Overtaking Cyclists on Two-Lane Rural Roads.

Road cycling, both individually and in groups, is common in Spain, where most two-lane rural roads have no cycle lanes. Due to this, and the difference in speed between drivers and cyclists, the overtaking manoeuvre is one of the most dangerous interactions. This study analyses how road geometry influences the overtaking manoeuvre performance. Field data of 1355 overtaking manoeuvres were collected using instrumented bicycles, riding along different rural road segments, and considering individual, medium and large groups of cyclists. The safety variables that characterise the overtaking manoeuvre are overtaking vehicle speed and lateral clearance. These variables have been correlated to geometric characteristics of the road, such as the type of centre line, the horizontal alignment, the speed limit, and the road cross section. Regression models have been fitted considering each cyclist group size and configuration. For individuals and medium groups, wider roads generate higher lateral clearances and lower overtaking speeds, while for large groups only the solid centre line was significant, generating lower clearances and higher speeds. Results suggest that other factors need to be considered, especially for large groups. Results offer a deeper understanding of the phenomenon by providing key points for improving road geometry design, such as widening the shoulders.

From the Vehicle-Based Concept of Operational Design Domain to the Road-Based Concept of Operational Road Section

Automated vehicles are designed to maintain both longitudinal and transverse control along a road section under certain favorable conditions. The conditions that ensure a safe operation of an automated vehicle are referred to as Operational Design Domain (ODD). So far, the concept of ODD has focused on the automated vehicle and how it is designed to operate autonomously and safely under certain conditions. However, Road Administrations and Operators would be probably more interested in formulating the concept of ODD from the road standpoint, identifying the sections that really allow an optimal and safe operation for all automated vehicles. Hence, this study introduces the concept of Operational Road Section (ORS), that is, defined as a road section, that is, compatible with all automated vehicles’ ODDs. This would result in very low disengagements of SAE Level 2 and 3 vehicles, and no disengagements at all of any SAE Level 4 vehicle, as long as their conditions do not vary. These road sections are determined as the overlapping of all the ODDs corresponding to all the automated vehicles traveling through a road segment. The concept of ORS will play a key role in the identification of the road features that promote a safe automated driving. With this information, Road Administrations and Operators could 1) establish improvement actions for extended automated operation and thus longer ORSs; and 2) manage driving restrictions to certain driving automation systems. Finally, a case study is presented showing the applicability of the ORS concept on a two-lane rural road segment.

Survey and Design Consistency Evaluation in Two-Lane Rural Road Segments

The present research proposes a time and cost-effective methodology to survey and perform a design consistency evaluation in two-lane rural road segments. The implementation of the proposed methodology carried out in Central Greece and more particularly along the national road Volos-Karditsa, from the local community Mikrothives up to the entrance of the Volos municipal unit. The road survey methodology, the process of creating the terrain model as well as the cross-check between the designed road with the requirements included in the Greek Road Design Guidelines Manual-Chapter X, are analytically presented. Similar checks are also performed for the sight distance throughout the road segments aiming to enable the rehabilitation of existing rural roads and enhance their safety level. The design of the road was followed by the execution of an experiment with the participation of a motorcycle rider aiming at the recording of his trajectory throughout the road which was then compared with its geometry. The experiment carried out by exploiting an instrumented vehicle and GPS technology. Several conclusions were drawn regarding the encroachment of the centerline and the deviation from the theoretical trajectory in the middle of the travelled way. Subsequently, the proposed methodology provides a reliable and simple solution of surveying and evaluating a 2-lane rural road in safety terms.

Influence of built environment and roadway characteristics on the frequency of vehicle crashes caused by driver inattention: A comparison between rural roads and urban roads

Introduction: With prevalent and increased attention to driver inattention (DI) behavior, this research provides a comprehensive investigation of the influence of built environment and roadway characteristics on the DI-related vehicle crash frequency per year. Specifically, a comparative analysis between DI-related crash frequency in rural road segments and urban road segments is conducted. Method: Utilizing DI-related crash data collected from North Carolina for the period 2013–2017, three types of models: (1) Poisson/negative binomial (NB) model, (2) Poisson hurdle (HP) model/negative binomial hurdle (HNB) model, and (3) random intercepts Poisson hurdle (RIHP) model/random intercepts negative binomial hurdle (RIHNB) model, are applied to handle excessive zeros and unobserved heterogeneity in the dataset. Results: The results show that RIHP and RIHNB models distinctly outperform other models in terms of goodness-of-fit. The presence of commercial areas is found to increase the probability and frequency of DI-related crashes in both rural and urban regions. Roadway characteristics (such as non-freeways, segments with multiple lanes, and traffic signals) are positively associated with increased DI-related crash counts, whereas state-secondary routes and speed limits (higher than 35 mph) are associated with decreased DI-related crash counts in rural and urban regions. Besides, horizontal curved and longitudinal bottomed segments and segments with double yellow lines/no passing zones are likely to have fewer DI-related crashes in urban areas. Medians in rural road segments are found to be effective to reduce DI-related crashes. Practical Applications: These findings provide a valuable understanding of the DI-related crash frequency for transportation agencies to propose effective countermeasures and safety treatments (e.g., dispatching more police enforcement or surveillance cameras in commercial areas, and setting more medians in rural roads) to mitigate the negative consequences of DI behavior.

Investigation of Speeding and Centerline Encroachment by Motorcycle Riders on a 2-lane Rural Road

Motorcycle riders are considered as one of the most vulnerable road users group worldwide. This is supported by numerous statistics which reveal that despite the reduction of vehicular fatalities over the last 15 years, the lesser improvement is observed in motorcycle fatal accidents compared to the other road users, either vulnerable or not. Speed and lane departure have been documented as significant contributory factors which precipitate the occurrence of motorcycle accidents. Many researchers attempted to identify and analyze the reasons behind this fact by conducting naturalistic riding studies using instrumented motorcycles and a relatively small number of volunteers. The recent development of multifunctional GPS devices of high positional and speed accuracy has assisted in this direction by allowing the planning of field measurements in a cost and time-effective manner. A similar practice has been adopted to the present study which aims to record and process the recorded data of a mid-scale naturalistic riding study in a two-lane rural road segment in an effort to investigate whether the motorcycle riders follow the posted speed limits. Apart from the investigation of the traveling speed, the high accuracy of the recorded positional data permitted us to compare the trajectory of the riders with the one that is determined by the theoretical model. The latter assumes that the road users travel along the midline of the travel lane and hence the curvature of the horizontal alignment coincides with the actual trajectories. The findings of the paper reveal that the riders do not comply with the posted speed limits to a large extent and follow a trajectory different from the theoretical one. Both findings pose a great risk to motorcycle riders’ safety, which strengthening is the main contribution of the present paper.

Applying hierarchical logistic models to compare urban and rural roadway modeling of severity of rear-end vehicular crashes

A rear-end crash is a widely studied type of road accident. The road area at the crash scene is a factor that significantly affects the crash severity from rear-end collisions. These road areas may be classified as urban or rural and evince obvious differences such as speed limits, number of intersections, vehicle types, etc. However, no study comparing rear-end crashes occurring in urban and rural areas has yet been conducted. Therefore, the present investigation focused on the comparison of diverse factors affecting the likelihood of rear-end crash severities in the two types of roadways. Additionally, hierarchical logistic models grounded in a spatial basis concept were applied by determining varying parameter estimations with regard to road segments. Additionally, the study compared coefficients with multilevel correlation model and those without multilevel correlation. Four models were established as a result. The data used for the study pertained to rear-end crashes occurring on Thai highways between 2011 and 2015. The results of the data analysis revealed that the model parameters for both urban and rural areas are in the same direction with the larger number of significant parameter values present in the rural rear-end crash model. The significant variables in both the urban and rural road segment models are the seat belt use, and the time of the incident. To conclude, the present study is useful because it provides another perspective of rear-end crashes to encourage policy makers to apply decisions that favor rules that assure safety.

Influence of peloton configuration on the interaction between sport cyclists and motor vehicles on two-lane rural roads

Cycling is a common activity on Spanish two-lane rural roads, mainly associated to sport and leisure, which resulted in 54 deaths in 2014. There is no scientific evidence about the risks associated to the interaction with motor vehicles of cyclists riding in a peloton. According to Spanish regulations, up to two cyclists can ride in parallel. This study compared different peloton configurations riding on a two-lane rural road segment. Three amateur cyclists rode along a road segment individually and grouped in pelotons with preset configurations: single bicycles, two bicycles in parallel, two in line, and different groups of three cyclists. Motor vehicle overtaking was observed and characterised from video cameras installed in the bicycles; speed and clearance were measured thanks to laser rangefinders on board. Moreover, the subjective risk perception at every overtaking event was recorded. Objective and subjective measures identified risky overtaking manoeuvres (low lateral clearance, high speed of vehicles, or high-risk perception). When cyclists rode in parallel, lower lateral clearances were found. At the same time, the overtaking vehicle speed was higher when individual cyclists were passed. These provided scientific support for criteria to ride in a peloton on two-lane rural roads.

Design Consistency Index for Two-lane Roads based on Continuous Speed Profiles

It is well known that road accidents tend to be more frequent in locations where a sudden change in road characteristics violates the driver's expectations. Most methods used to assess the design consistency are based on simplified speed profiles that give a coarse description of the vehicle dynamics along the road. This paper presents a new approach to quantify the road design consistency, based on continuous operating speed profiles. These profiles are based on the Gipps’ car-following equations, adapted to simulate the driver behaviour in the vicinity of horizontal curves under free-flow conditions. A methodology to calibrate and validate the Gipps’ behavioural parameters from field data is presented and applied to predict the speed profiles of three drivers for a set of rural road segments. The calibration is based on trajectory data collected with an instrumented vehicle and it follows an automated procedure that aims to minimize the differences between the predicted and observed speed profiles. The new consistency index is based on the deceleration distances and it allows to overcome some limitations of the existing methods.

Integrated American-European protocol for safety interventions on existing two-lane rural roads

PurposeThe main purpose was to integrate two strategies for road safety analyses (qualitative: audits, inspections; and quantitative: accident predictions) and develop a possible protocol for the safety interventions on existing two-lane rural road segments. Those road sections do not typically belong to the TEN-network, to which the 2008/96/EC Directive is mainly oriented. Hence, they could lack of methods for designing safety-based interventions. The main research questions were:Which possible problems can arise from the application of this protocol to real cases?Which data are practically needed?Which possible solutions can be provided for the highlighted problems?MethodsThe integrated protocol, including: 1) the HSM predictive method, 2) the EU Regulations, 3) the local road design standards, 4) some research developments; is applied to real two-lane rural road segments requiring safety-based interventions. Its application is divided in the typical road safety analysis stages.ResultsA wide list of possible problems was highlighted and addressed: 1) lack of data, 2) difficult comparison with current road standards in order to identify safety problems, 3) lack of methods for evaluating the skidding risk along the layout, 4) setting speed limits, 5) need for optimizing the selection of countermeasures based on their aims and their timely application, in different recurrent situations, 6) availability and comparison of predictive methods.ConclusionsBased on the problems and solutions discussed, main advantages (1) the systematic approach, 2) the quantitative assessment of benefits, 3) the possible transferability) and disadvantages (difficulties in overcoming the lack of data and calibrated accident prediction models) of the method were remarked.

Developing Updatable Crash Prediction Model for Network Screening: Case Study of Czech Two-Lane Rural Road Segments

This paper focuses on application of crash prediction models in network screening. The two main questions were ( a) What variables should be involved in the model? and ( b) What length should the modeled period be? Answers to these questions should provide guidelines for developing an updatable crash prediction model (i.e., a model that is both reliable and simple so that its updating for periodical network screening is not highly demanding). Data on approximately 1,000 km (600 mi) of a two-lane rural-road network from South Moravia, Czech Republic, were used. On the basis of 8 years of annual crash frequencies, together with exposure and geometrical variables, several variants of prediction models were developed. To study the quality of the models, a series of consistency tests was applied relative to comparison of the models themselves as well as to their diagnostic performance. As a result, simple crash prediction models (that included traffic volume, segment length, and curvature change rate) were found sufficient for network screening. If one supposes that length and curvature are unlikely to change often, only traffic volume data need to be periodically updated. Consistency analyses indicate that this period should be 4 years. Under these conditions, models are being applied in the studied region. Further planned activities include extensions to intersections and also to other Czech regions.

Motor vehicles overtaking cyclists on two-lane rural roads: Analysis on speed and lateral clearance

Two-lane rural roads in Spain accommodate significant bicycle traffic volumes, mainly associated to sport and leisure activities. Motor vehicles’ higher speed, weight and volume, compared to cyclists, represent a serious safety concern when overtaking a bicycle. Spanish traffic rules determine a minimum 1.5m lateral distance.This research characterised 2928 overtaking manoeuvres in the overtaking lateral clearance between motor vehicle and bicycle, as well as in the motor vehicle speed, in contrast with previous research. Two instrumented bicycles were equipped with laser rangefinders, a GPS tracker and three video cameras. They rode along seven rural road segments at a speed between 15 and 25km/h, centred on the paved shoulder, or as close as possible to the outer edge. Besides, this methodology allowed the characterisation of the overtaken vehicle type, its left lane occupation as well as its interaction with opposing traffic flow. For each session, rider’s general risk perception was also registered.The analysis suggested that lateral clearance is not the only factor that influenced rider’s risk perception, although current standards are only related to it. On the contrary, a combined factor of lateral clearance, vehicle type and vehicle speed had a more significant correlation with the perceived risk. This agreed with literature models of transient aerodynamic forces between overtaking and overtaken vehicles. Results showed that effect of heavy vehicles on bicyclists was also strong. In addition to this, the combined factor of clearance and speed was higher on tangent sections where overtaking was permitted.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots

Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.

지방부 도로구간의 사고수정계수 개발에 관한 연구

PURPOSES : Although numerous researches have been studied to reveal accident causations for road intersections, there are still many research gaps for road segments. It is mainly because of difficulty of data and lack of analytical method. This study aims to study accident causations for rural road segments and develop accident modification factors for safety evaluation. The accident modification factors can be used to improve road safety. METHODS : Methods for developing AMF are diverse. This study developed AMFs using accident prediction models and selected explanatory variables from the accident models. In order to select final AMFs, three different methods were applied in the study. RESULTS : As a result of the study, many AMFs such as horizontal curves or vertical curves were developed and explained the meanings of the results. CONCLUSIONS : This study introduced meaningful methods for developing significant AMFs and also showed several AMFs. It is expected that traffic or road engineers will be able to use the AMFs to improve road segment safety.

Application of global positioning system and questionnaires data for the study of driver behaviour on two‐lane rural roads

Methodologies based on naturalistic observation provide the most accurate data for studying drivers' behaviour. This study presents a new methodology to obtain naturalistic data related to drivers' behaviour in a road segment. It is based on the combination of using global positioning system data and drivers' questionnaires. The continuous speed profiles along a road segment and the characteristics of drivers, of their trips and the type of their vehicles can be obtained for a great amount of drivers. It has already been successfully used for several studies, such as the development of models to estimate operating speed profile in two-lane rural road segments; or the characterisation of driving styles. These operating speed models have been the key for the development of a new geometric design consistency model, allowing an easier road safety evaluation. Besides, knowledge on the human factors that influence speed choice may be useful for road safety media campaigns and education programs designers, and also for the improvement of intelligent driver assistance systems.

Daytime and Nighttime Passing Maneuvers on a Two-Lane Rural Road in Spain

Passing is one of the most complex driving maneuvers performed on two-lane rural roads and has important effects on road safety and traffic operation. Passing is affected by driving behavior, road geometry, traffic volume, and traffic composition as well as external factors. Research was developed to compare the passing process under daytime and nighttime conditions. An experimental method was designed to collect video data of passing maneuvers on a two-lane rural road segment located near Valencia, Spain. Two methods were used: (a) external observations of four passing zones with six video cameras and (b) an instrumented vehicle equipped with video cameras and laser rangefinders, driven slightly below the operating speed along a segment of the same road so it would be passed by other vehicles. A total of 291 maneuvers were observed, up to 20% of which were at night. Macroscopic analysis results indicated that approximately 17% of passes were at night, even though passing frequency and passing demand decreased at night. Also, the behaviors of individual drivers who passed other vehicles were different at night and during the day. Maneuvers limited by the presence of an opposing vehicle were performed more quickly at night, even if the accepted gaps were longer. In this case, a more difficult perception of distances to opposing vehicles and of vehicle speeds explained the differences. In contrast, maneuvers limited by sight distance (without a visible opposing vehicle) were slower at night. This observation matched a traditional hypothesis: passing at night is safer because the headlights of an opposing vehicle allow a driver to anticipate the vehicle's position before it becomes visible.

New geometric design consistency model based on operating speed profiles for road safety evaluation

To assist in the on-going effort to reduce road fatalities as much as possible, this paper presents a new methodology to evaluate road safety in both the design and redesign stages of two-lane rural highways. This methodology is based on the analysis of road geometric design consistency, a value which will be a surrogate measure of the safety level of the two-lane rural road segment. The consistency model presented in this paper is based on the consideration of continuous operating speed profiles. The models used for their construction were obtained by using an innovative GPS-data collection method that is based on continuous operating speed profiles recorded from individual drivers. This new methodology allowed the researchers to observe the actual behavior of drivers and to develop more accurate operating speed models than was previously possible with spot-speed data collection, thereby enabling a more accurate approximation to the real phenomenon and thus a better consistency measurement.Operating speed profiles were built for 33 Spanish two-lane rural road segments, and several consistency measurements based on the global and local operating speed were checked. The final consistency model takes into account not only the global dispersion of the operating speed, but also some indexes that consider both local speed decelerations and speeds over posted speeds as well.For the development of the consistency model, the crash frequency for each study site was considered, which allowed estimating the number of crashes on a road segment by means of the calculation of its geometric design consistency. Consequently, the presented consistency evaluation method is a promising innovative tool that can be used as a surrogate measure to estimate the safety of a road segment.

Property Damage Crash Equivalency Factors to Solve Crash Frequency–Severity Dilemma: Case Study on South Korean Rural Roads

Safety interventions (e.g., median barriers, photo enforcement) and road features (e.g., median type and width) can influence crash severity, crash frequency, or both. Both dimensions—crash frequency and crash severity—are needed to obtain a full accounting of road safety. Extensive literature and common sense both dictate that crashes are not created equal, with fatalities costing society more than 1,000 times the cost of property damage crashes on average. Despite this glaring disparity, the profession has not unanimously embraced or successfully defended a nonarbitrary severity weighting approach for analyzing safety data and conducting safety analyses. It is argued here that the two dimensions (frequency and severity) are made available by intelligently and reliably weighting crash frequencies and converting all crashes to property-damage-only crash equivalents (PDOEs) by using comprehensive societal unit crash costs. This approach is analogous to calculating axle load equivalents in the prediction of pavement damage: for instance, a 40,000-lb truck causes 4,025 times more stress than does a 4,000-lb car and so simply counting axles is not sufficient. Calculating PDOEs using unit crash costs is the most defensible and nonarbitrary weighting scheme, allows for the simple incorporation of severity and frequency, and leads to crash models that are sensitive to factors that affect crash severity. Moreover, using PDOEs diminishes the errors introduced by underreporting of less severe crashes—an added benefit of the PDOE analysis approach. The method is illustrated with rural road segment data from South Korea (which in practice would develop PDOEs with Korean crash cost data).