Road Classification Research Articles

Spatial characteristics of bicycle–motor vehicle crashes in Christchurch, New Zealand: A case-control approach

This paper aims to examine the risk of bicycle-motor vehicle crashes occurring on a network-wide level in Christchurch, New Zealand, based on the spatial characteristics present in the road environment. To achieve this, logistic regression was undertaken with a binary dependent variable (crash/non-crash) using a case-control strategy, with case sites being locations of reported crashes, while control sites were sampled from the road network in proportion to where people cycle. Due to the uncertainty of cycling flows in Christchurch, four logistic regression models were undertaken based on different route selection preferences.
 
 The results identified that the odds of a crash increased across all four models due to the presence of driveways or intersections, identifying that these characteristics are associated with an increase in crash risk. All of the models identified that the risk of a crash decreases with the presence of on-road cycle lanes, while crash risk due to the presence of specific planning zones or road classification varied across all of the models.

Parametric analysis of the potential of energy harvesting from commercial vehicle suspension system

An accurate estimation of the harvestable energy from a vehicle suspension under typical operating conditions is vital for design and implementation of efficient energy harvesters in vehicles. In this study, a generic three-dimensional model of a commercial vehicle is formulated by integrating nonlinear models of suspension components and tires to determine the harvestable power considering the effects of suspension parameters and road characteristics. The component characteristics of the suspension system and tires are obtained through the reported laboratory-measured data acquired under an extensive range of loading conditions. The vehicle model is subsequently employed to investigate the harvestable energy potential considering variations in the driving speed, chassis load, road waviness and roughness, suspension and tire stiffness, compression mode damping ratio, and asymmetric suspension damping over the most possible ranges of running conditions. The results suggested significant influences of these parameters, while the driving speed, damping asymmetry factor, compression mode damping ratio, and road condition revealed the most pronounced effect on the harvestable power. The results obtained in terms of root mean square and power spectral density of harvestable power are also indicative that rough terrains yield incomparably larger magnitudes of energy dissipation than relatively smooth road classes defined in ISO 8608:1995, and thereby suggestive of the greater potential of energy recovery from commercial vehicles on off-road surfaces.

Vibration-Based Damaged Road Classification Using Artificial Neural Network

It is necessary to develop an automated method to detect damaged road because manually monitoring the road condition is not practical. Many previous studies had demonstrated that the vibration-based technique has potential to detect damages on roads. This research explores the potential use of Artificial Neural Network (ANN) for detecting road anomalies based on vehicle accelerometer data. The vehicle is equipped with a smart-phone that has a 3D accelerometer and geo-location sensors. Then, the vehicle is used to scan road network having several road anomalies, such as, potholes, speedbump, and expansion joints. An ANN model consisting of three layers is developed to classify the road anomalies. The first layer is the input layer containing six neurons. The numbers of neurons in the hidden layer is varied between one and ten neurons, and its optimal number is sought numerically. The prediction accuracy of 84.9% is obtained by using three neurons in conjunction with the maximum acceleration data in x, y, and z-axis. The accuracy increases slightly to 86.5%, 85.2%, and 85.9% when the dominant frequencies in x, y, and z-axis, respectively, are taken into account beside the previous data.

Safety Performance Functions for Rural Two-Lane County Road Segments

Safety performance functions (SPFs) were developed for rural two-lane county roadway segments in Michigan. Five years of crash data (2011 to 2015) were analyzed for greater than 6,500 mi of rural county roadways, covering 29 of Michigan’s 83 counties and representing all regions of the state. Three separate models were developed to estimate annual deer-excluded total and injury crashes on rural county roadways: 1) paved federal-aid segments, 2) paved non-federal-aid segments, and 3) paved and gravel non-federal-aid segments with fewer than 400 vpd. To account for the unobserved heterogeneity associated with differing county design standards, mixed effects negative binomial models with a county-specific random effect were utilized. Not surprisingly, the county segment SPFs generally differed from traditional models generated using data from state-maintained roadways. County federal-aid roadways general showed greater crash occurrence than county non-federal-aid roadways, the Highway Safety Manual (HSM) two-lane rural roadways model, and rural state highways in Michigan. County non-federal-aid paved roadways showed crash occurrence rates that were remarkably similar to the HSM base rural two-lane roadway model, whereas gravel roadways showed greater crash occurrence rates. The presence of horizontal curves with design speeds below 55 mph had a strong association with the occurrence of total and injury crashes across all county road classes. Increasing driveway density was also found to be associated with increased crash occurrence. However, lane width, roadway surface width, and paved shoulder width had little to no impact on total or injury crashes.

Longer afterschool active commutes and the travel environment of middle schools in Shenzhen, China.

The afterschool commute is a major part of children's daily activity. This study examines the relationship between student extended active travel routes and route environment characteristics. Route environment characteristics may be related to an extended route for students who walk or bike home. Self-reported itineraries were collected from 12 to 15-year old students in 3 middle schools in Shenzhen in May and June (n = 1257). Itineraries involving a detour from the shortest possible route home (n = 437) were compared with the shortest route. A field study coded all possible routes within the school districts by playable open spaces, sidewalk width, controlled crossings, road category, and public transit stops. Binary logistic regression reveals that routes with greater intersection density and number of open spaces are related to active travel choice. Sidewalk width, number of traffic lights and proportion of arterial roads are positively related to motorized travel. Linear regression reveals that travel distance, sidewalk width, number of open spaces and street crossings, as well as the proportion of secondary roads and pathways are positively related to detour distance. Higher numbers of public transit stops and traffic lights are related to shorter detours. Attending cram school is also negatively associated with active travel and detour. Younger students, females and students with longer moderate-to-vigorous physical activity time have extended active travel. Specific route environment characteristics are associated with longer and more active middle school student commutes and may be implemented to raise overall activity levels in children.

COMPARISON OF METHODS TO MAP SELECTED TRAFFIC MARKINGS ON FIRST CLASS ROADS IN THE CZECH REPUBLIC

Abstract. The article presents conclusions of a comprehensive analysis of pilot data collection using four mapping methods. To validate mapping methods and procedures, we selected three ten-kilometer sections of the first class roads with different geomorphological, vegetative and transportation properties. All sections were measured by aerial photogrammetry using GSD = 4 cm, mobile laser scanning equipment linked with cameras, by geodetic surveying methods, and one section was also measured by UAV. The tested methods mapped selected features of vertical and horizontal traffic markings on the first class roads. The traffic marking measuring sets were analyzed from the perspectives of personnel, time, data, costs, and technological and organizational aspects. All the mapping methods were verified as mentioned above starting from work preparation phase, its terrain realization, captured data processing and detailed analysis, concluding with stating the advantages and disadvantages for each mapping method. One of the analysis outputs was proposals to change and refine road administrator’s regulations. The mapping methods were compared with geodetic measurements. Analyses were also carried out in the context of creating digital data in 3D for the realization of BIM (Building Information Modeling) digital data in connection with the concept of the European Parliament and Council Directive 2014/24 / EU on Public Procurement, and Czech Government Decree 682 on the Concept of Implementation of the BIM Method in the Czech Republic of 25 September 2017 and Decree 958 of the Government of the Czech Republic of 2 November 2016 on the importance of BIM for the construction engineering and proposal of further steps to introduce it in the Czech Republic.

Determination of Technical Condition of a Bridge Structure Based on Survey Results

Nowadays, the age of most transport facilities in Russian Federation is estimated in many decades. Consequently, there is an urgent need for periodic surveys and monitoring of the state of each structure, its individual structural elements. The main purpose of these measures is to maintain the high performance indicators of the transport structure, the achievement of which is impossible without examination, analysis and evaluation of parts of the structure that are in the aquatic environment and, as a consequence, the occurrence and development of various types and degrees of defects and damages. The most important conditions for ensuring uninterrupted and safe traffic along the bridges of vehicles and pedestrians are: the normative load-carrying capacity of the structure; required clearance of the roadway and sidewalks; compliance with traffic safety requirements for bridges; observance of characteristics and maintenance of the bridge capacity for the period of ice drift and high water; timely performance of work on the care, maintenance and repair of the elements of the bridge. Technically sound structures and their reliability can be ensured if all the parameters of the road category structure and the requirements of regulatory documents are met. The work presents the survey materials of the bridge. Classification of defects by group and class of danger. The results of determining the carrying capacity on the basis of the survey are given.

Istraživanje postotka vremena provedenog u koloni na dvotračnim izvangradskim cestama

In Bosnia and Herzegovina (B&H), two-lane rural highways make up the largest percentage of road network and accommodate almost complete traffic. Because of this, platoons are often formed and vehicle speeds are reduced. To improve the quality of traffic flow, it is necessary to define the level of service (LOS) for the existing condition and for alternative possibilities of reconstructing critical elements of the road network. According to Highway Capacity Manual 2010 (HCM 2010), for two-lane highways LOS is defined by measures of efficiency: average travel speed (ATS) for road class I and percent time spent following (PTSF) for road classes I and II. HCM assumes very high ATS values for conditions on national roads that are classified as class I according to HCM classification, and the problem is also nonuniformity of highway geometry elements, which further complicates the application of ATS in B&H. Therefore, PTSF was studied in this paper as an appropriate measure for determining the efficiency of two-lane rural highways. Researches carried out in the world show significant differences in PTSF results compared to the HCM calculations. No research on this topic has been conducted in the region and HCM is used in its original form. The above reasons were the main motive to study this topic and develop a model that would be easy to apply in practice. The survey was conducted on main roads with calculation speed of 80 km/h, because they are the most important in the two-lane road network. In this dissertation, calibration and validation of the Vissim 9 simulation software was first made based on conducted field research. The reason for application of the simulation software is that it allows simulation of different traffic conditions that occur in the field but cannot all be covered by surveying, or for testing some new traffic conditions. Based on the simulations of different traffic conditions, a new model for calculation of PTSF on two-lane rural roads (for speed 80 km/h) was obtained. The obtained PTSF calculation model was validated on another section and the obtained results proved the applicability of the model.

Generation of Artificial Road Profile for Automobile Spring Durability Analysis

This paper presents the use of a generated artificial road profile in the simulation of a quarter car model for spring durability based-force extraction. In situ measurement of the road loading profile for automotive spring durability analysis, requires considerable cost and effort due to the complex experimental setup. Hence, an artificial road profile was generated for the quarter car model simulation to obtain the spring force signals. Initially, according to the ISO 8608 standard, a class “A” artificial road profile was generated using a designated waviness value, unevenness index and random phase angle. The generated road profile was used as the input to a constructed quarter car model to obtain the spring force signals. Subsequently, the generated nominal force signal was used to predict the fatigue life of the spring. Moreover, to obtain the localise fatigue behaviour of the spring, a finite element spring model together with the force signal was used for fatigue prediction. Under this class “A” road excitation, the spring possessed very high fatigue life of 1.87 × 106 blocks to failure. Further, a series of spring variant was analysed for fatigue life through this road class excitation. The relationship between spring stiffness and fatigue lives established using power regression and the coefficient of determination (R2) as high as 0.9815 was obtained. Therefore, this analysis will assist in automobile spring design regarding fatigue when road load data is not available.

Changes concerning commute traffic distribution on a road network following the occurrence of a natural disaster – The example of a flood in the Mazovian Voivodeship (Eastern Poland)

The purpose of this article is to determine the size and spatial structure of changes in traffic density within the regional road network following an occurrence of a flood in the Mazovian Voivodeship, Poland. The use of the application developed for the purpose of this article – offers a possibility to react accordingly when there are non-typical obstructions (here: a flood). On the basis of the conducted study, it has been stated that the greatest changes in vehicle traffic density (the analysis of commute traffic) regard the capital of Mazovian Voivodeship, which – first of all – stems from the fact that it is Warsaw that the largest number of employees commute to. Secondly, it is influenced by the location of the capital city in relation to the river system. In the case of the analysed voivodeship and in ‘normal’ circumstances (no flood), commuting to work remains approximately within the 160-min isochrone. In the second variant, this time would extend nearly eightfold, and in the remaining scenarios fivefold. As far as ‘normal’ circumstances (no flood) and commuting in the Mazovian Voivodeship are concerned, the greatest load refers in particular to the following road classes: main road of accelerated traffic, main road and cumulative road. In this case, express and motorways play a marginal role. On the other hand, in the remaining scenarios, the importance of the class of main road of accelerated traffic decreases at the expense of the classes of main road and cumulative road.

Speed independent road classification strategy based on vehicle response: Theory and experimental validation

Abstract This paper presents a speed-independent road classification strategy (SIRCS) based on sole measurement of unsprung mass acceleration. The new method provides an easy yet accurate classification methodology. To this purpose, a classification framework with two phases named off-line and online is proposed. In the off-line phase, the transfer function from unsprung mass acceleration to the road excitation is firstly formulated, and a random forest-based frequency domain classifier is then generated according to the standard road definition of ISO 8608. In the online phase, unsprung mass acceleration and vehicle velocity are firstly combined to calculate the equivalent road profile in the spatial domain, and then a two-step road classifier attributes the road excitation to a certain level based on the power spectral density (PSD) of the equivalent road profile. Simulations are carried out for different classification intervals, varying velocity, system uncertainties and measurement noises. Road experiments are finally performed in a production vehicle to validate the proposed SIRCS. Measurement of only unsprung mass acceleration to identify road classification and less rely on the training data are the major contributions of the proposed strategy.

OPTIMIZATION TO MINIMIZING DISTANCE CARS OF FIRE EXPORTER IN INDUSTRIAL REGION SIER SURABAYA

Various fire infrastructure in Surabaya has been built, but the number of fire incident is less suitable with the standard of disaster response time. This study was conducted to determine the distribution of minimization of fire engine mileage in SIER Industrial Area of ​​Surabaya. The analytical method used is qualitative descriptive by comparing existing condition, criteria, and policy review that exist in SIER Industrial Area of ​​Surabaya with data of fire service post service in Surabaya City to know unreached area of ​​fire post service and have high risk potential Will be a fire disaster in the SIER Industrial Area of ​​Surabaya. Next determine the factors and criteria for determining the location of firefighting post based on existing policy studies and conditions. Factors determining the location of firefighting in Surabaya City is a function of the building based on the type of land use, the density of the net population, the density of the building, the range of fire service, the radius of the water supply range, the incidence of fire, the time of fire disaster response, the availability of land, and the class of road. The result of this research is the implementation of building protection management on building function in industrial area, procurement of socialization and education of fire prevention for the community, coordinating with traffic police to facilitate path of location achievement

COMPARISON BETWEEN THE DOUBLE BUFFER METHOD AND THE EQUIVALENT RECTANGLE METHOD FOR THE QUANTIFICATION OF DISCREPANCIES BETWEEN LINEAR FEATURES

Abstract Currently, in Brazil, for the assessment of the Positional Accuracy of non-point features (lines and polygons), there is no standard norm of execution. This work aims to compare the results of two methodologies that allow determining the average value of the discrepancies between linear features. The first, Equivalent Rectangle Method, aims to determine the discrepancy by considering an equivalent rectangle for the polygon obtained from the two homologous lines. The second, Double Buffer Method applies a buffer on both lines and obtains the average discrepancy value based on the relation of the areas of the generated polygons. These methods were compared in two steps. Initially, an experiment was performed with features of known measurements, where the displacement of the homologous lines was controlled in azimuth and distance. In this step, it was verified that the shape of the feature and the direction of the displacement interfere in the results of both methods when compared to the traditional procedure of measurement of discrepancies by homologous points. In the second stage, we evaluated the vector data of the OpenStreetMap (class of roads), with reference to a more accurate vector dataset produced for the Mapping of the State of Bahia. As a result, for the 1:25,000, 1:50,000, 1:100,000 and 1:250,000 scales, it was obtained, respectively, the PEC-PCD for the Equivalent Rectangle Method "C", "B", "A" and "A" and the PEC-PCD for the Double Buffer Method "R", "C", "B" and "A", where "R" means that it has not achieved the minimum PEC-PCD classification.

Risk factors for extremely serious road accidents: Results from national Road Accident Statistical Annual Report of China.

BackgroundIn the past decades, extremely serious road accidents with a death toll over ten in each have become a severe public health problem in China. This study investigates risk factors contributing to extremely serious road accidents, which will be crucial for accident prevention.MethodsCollecting data from The Road Accident Statistical Annual Report openly issued by China’s Traffic Management Bureau of the Public Security Ministry for the time period 2004–2015, we used the monthly case number of extreme serious road accidents as the dependent variable. We then selected ten risk factors as primary independent variables: professional driver, driving under influence (alcohol or drug), fatigue, vehicle type, overload, brake problem, weather, road classification, terrain, and region. The method of negative binominal regression was implemented to investigate the association between these risk factors and extremely serious road accidents.ResultsA total of 346 extremely serious road accidents were included in our analysis. On a national scale, we found that professional driver [incidence rate ratio (IRR): 1.10, 95% CI: 1.02–1.19], fatigue (IRR: 1.15, 95% CI: 1.03–1.29), large vehicle type (IRR: 1.11, 95% CI: 1.03–1.21), overload (IRR: 1.09, 95% CI: 1.03–1.16), and terrain (IRR: 1.09, 95% CI: 1.01–1.18) were significantly associated with extremely serious road accidents. Besides, separate analyses on western and non-western region indicated that both regions had shared risk factors as well as distinct factors.ConclusionsOur study identifies professional driver, fatigue, large vehicle type, overload, and terrain as significant risk factors of extremely serious road accidents in China, and targeted and preventative measures could be taken based on our findings.

Real-Time Video Processing using Contour Numbers and Angles for Non-urban Road Marker Classification

Road users make vital decisions to safely maneuver their vehicles based on the road markers, which need to be correctly classified. The road markers classification is significantly important especially for the autonomous car technology. The current problems of extensive processing time and relatively lower average accuracy when classifying up to five types of road markers are addressed in this paper. Two novel real time video processing methods are proposed by extracting two formulated features namely the contour number, , and angle, 𝜃 to classify the road markers. Initially, the camera position is calibrated to obtain the best Field of View (FOV) for identifying a customized Region of Interest (ROI). An adaptive smoothing algorithm is performed on the ROI before the contours of the road markers and the corresponding two features are determined. It is observed that the achievable accuracy of the proposed methods at several non-urban road scenarios is approximately 96% and the processing time per frame is significantly reduced when the video resolution increases as compared to that of the existing approach.

A novel nonlinear road profile classification approach for controllable suspension system: Simulation and experimental validation

Driven by the increasing requirement for road conditions in the field of the controllable suspension system, this paper presents a novel nonlinear road-excitation classification procedure for arbitrary suspension control strategy. The proposed procedure includes four steps: the definition of controller parameters, selection of insensitive frequency ranges, calculation of superior features, and generation of the classifier. To better illustrate the proposed procedure, the clipped optimal control strategy is taken as an example in the simulation part. Simulation results reveal that the proposed method can accurately estimate road excitation level for various controller parameters, vehicle speeds, and vehicle models. Three contributions have been made in this paper: (1) A road classification procedure that can be used for road adaptive suspension control with any control algorithm is developed; (2) In order to improve classification accuracy, the concept of insensitive index which is based on the time-frequency analysis is proposed; (3) Experimental validation with a quarter vehicle test rig is performed, which has verified the effectiveness of the proposed method for the adaptive controllable suspension system.

An objective method of street classification for noise studies

An average daily traffic (ADT)-based street classification method to assess urban noise has been experimentally analysed. Different statistical tests were applied to the noise levels and traffic flows measured in a medium-sized city (Mérida, Spain). The ADT-based classification method was compared to a previously proposed categorization method. The results obtained showed that not all of the statistical tests provided similar results, and that the ADT-based classification method provided good results with less overlapping categories/levels. It also showed a better classification of sampling points than the one obtained when applying the categorization method. Advantages and drawbacks of each classification procedure are discussed.

The Use of Tree Barks to Monitor Traffic Related Air Pollution: A Case Study in São Paulo–Brazil

The analysis of chemical elements in the barks of trees is an alternative procedure to access spatial heterogeneity of traffic related air pollution. However, the role of tree species in the characterization of the variability of airborne pollution is poorly known. We present an observational study conducted in Sao Paulo, Brazil, based on the analysis of 498 trees from three common species: Tipuana tipu, Poincianella pluviosa and Ligustrum sp.. We considered ANCOVA models to compare the concentrations of Al, Fe, Zn, Cu, Mn, Ba and S in the bark of trees located close to streets with different levels of traffic intensity controlling for the extension of nearby green areas. The expected trend of increasing elemental concentration in the bark of trees located near streets with greater traffic intensity or close to smaller green areas was only fully evidenced by T. tipu. For instance, the concentrations of Zn, Fe, Al and Ba increase by 200%, 350%, 230% and 280% respectively, for trees of this species located near arterial streets when compared to those observed near local streets. On the other hand, the concentrations of Zn, Fe, Al and Ba are reduced by 41%, 45% 50%, 30%, respectively, for trees located near green areas. For P. pluviosa, the capacity to suggest an association between the tree bark concentration of chemical elements with increasing levels of air pollution and presence of green areas was only fully observed for Zn and Cu. For Ligustrum sp., weaker and sometimes non-expected associations between bark concentrations of the chemical elements and either street classification or green area extension were observed. Our results indicate that the choice of species is a key element in the use of tree barks as a biomonitoring tool in urban landscapes. Species like T. tipu, with rough and highly porous bark, are the most appropriate for such purpose.

Road Damage Detection and Classification Using Deep Neural Networks with Smartphone Images

AbstractResearch on damage detection of road surfaces using image processing techniques has been actively conducted. This study makes three contributions to address road damage detection issues. First, to the best of our knowledge, for the first time, a large‐scale road damage data set is prepared, comprising 9,053 road damage images captured using a smartphone installed on a car, with 15,435 instances of road surface damage included in these road images. Next, we used state‐of‐the‐art object detection methods using convolutional neural networks to train the damage detection model with our data set, and compared the accuracy and runtime speed on both, using a GPU server and a smartphone. Finally, we demonstrate that the type of damage can be classified into eight types with high accuracy by applying the proposed object detection method. The road damage data set, our experimental results, and the developed smartphone application used in this study are publicly available (https://github.com/sekilab/RoadDamageDetector/).

Analysis of the results of general traffic measurements on the national roads carried out in the years 2000-2015 in the Silesian Voivodeship

Paper presents the analysis of the results of General Traffic Measurements on the national roads carried out in the years 2000-2015 in the Silesian Voivodeship. Traffic measurements are the basic tool that is used to obtain information about traffic conditions. They allow identification of road infrastructure that requires modernization or complete reconstruction. The information obtained is needed to properly manage, maintain and plan the development of the road network. Data obtained from General Traffic Measurements are used to make decisions related to the classification of roads and to determine their priorities on the road network at the national and international scale. Information from the GTM allows to evaluate traffic conditions and the possibility of introducing changes to the organization of traffic.