Road Surface Conditions Research Articles

GLM-Based Flexible Monitoring Methods: An Application to Real-Time Highway Safety Surveillance

Statistical modeling of historical crash data can provide essential insights to safety managers for proactive highway safety management. While numerous studies have contributed to the advancement from the statistical methodological front, minimal research efforts have been dedicated to real-time monitoring of highway safety situations. This study advocates the use of statistical monitoring methods for real-time highway safety surveillance using three years of crash data for rural highways in Saudi Arabia. First, three well-known count data models (Poisson, negative binomial, and Conway–Maxwell–Poisson) are applied to identify the best fit model for the number of crashes. Conway–Maxwell–Poisson was identified as the best fit model, which was used to find the significant explanatory variables for the number of crashes. The results revealed that the road type and road surface conditions significantly contribute to the number of crashes. From the perspective of real-time highway safety monitoring, generalized linear model (GLM)-based exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts are proposed using the randomized quantile residuals and deviance residuals of Conway–Maxwell (COM)–Poisson regression. A detailed simulation-based study is designed for predictive performance evaluation of the proposed control charts with existing counterparts (i.e., Shewhart charts) in terms of the run-length properties. The study results showed that the EWMA type control charts have better detection ability compared with the CUSUM type and Shewhart control charts under small and/or moderate shift sizes. Finally, the proposed monitoring methods are successfully implemented on actual traffic crash data to highlight the efficacy of the proposed methods. The outcome of this study could provide the analysts with insights to plan sound policy recommendations for achieving desired safety goals.

Analysis of historical road accident data supporting autonomous vehicle control strategies

It is expected that most accidents occurring due to human mistakes will be eliminated by autonomous vehicles. Their control is based on real-time data obtained from the various sensors, processed by sophisticated algorithms and the operation of actuators. However, it is worth noting that this process flow cannot handle unexpected accident situations like a child running out in front of the vehicle or an unexpectedly slippery road surface. A comprehensive analysis of historical accident data can help to forecast these situations. For example, it is possible to localize areas of the public road network, where the number of accidents related to careless pedestrians or bad road surface conditions is significantly higher than expected. This information can help the control of the autonomous vehicle to prepare for dangerous situations long before the real-time sensors provide any related information. This manuscript presents a data-mining method working on the already existing road accident database records to find the black spots of the road network. As a next step, a further statistical approach is used to find the significant risk factors of these zones, which result can be built into the controlling strategy of self-driven cars to prepare them for these situations to decrease the probability of the potential further incidents. The evaluation part of this paper shows that the robustness of the proposed method is similar to the already existing black spot searching algorithms. However, it provides additional information about the main accident patterns.

Development and verification of integrated photoelectric system for noncontact detection of pavement ponding and freezing

The ponding water and ice on the road surface can cause degradation of skid resistance that seriously affects driving safety. In order to accurately detect road surface conditions, an integrated photoelectric system was developed composed of an infrared light-emitting diode and a phototransistor. Typical asphalt pavements such as AC-13, SMA-13, and OGFC-13 were selected to simulate four road surface conditions: dry, wet, ponding water, and ice. The voltage intervals for dry and wet surface conditions were proposed by the light intensity method. The functional relationships were established between the depth of ponding and the output voltage, the thickness of ice, and the output voltage, respectively. The noncontact detection system for pavement ponding and freezing was developed by the design of the hardware of real-time controller, the software of supervisory computer, and the shell of entire system. Then the system was verified in the field conditions. According to the test results, there was a good linear relationship between the ponding depth and the output voltage, while there was a quadratic parabolic relationship between the ice thickness and the output voltage. The detecting accuracy was 91.67% for the dry and wet surface conditions. The detecting errors of ponding depth for three different types of pavement surface were 0.248, 0.168, and 0.189, respectively; the detecting errors of the ice thickness for three different types of pavement surface were 0.219, 0.261, and 0.326, respectively. The errors were within a reasonable range, and the detecting accuracy of ponding depth is higher than that of ice thickness.

Fixed-Time Slip Control With Extended-State Observer Using Only Wheel Speed for Anti-Lock Braking Systems of Electric Vehicles

In this paper, we propose a fixed-time slip control with an extended-state observer (ESO) using only wheel speed for anti-lock brake systems (ABS) in electric vehicles. In the proposed control strategy, the longitudinal tire-road friction is defined as the disturbance. The ESO is designed to estimate the wheel speed, longitudinal tire-road friction, and longitudinal vehicle speed. Based on the estimated longitudinal tire-road friction, an optimal desired slip generator is designed, which provides optimal desired slip in real-time to maintain a nearly maximum tire-road friction coefficient (TFC), according to road surface conditions. A fixed-time controller is developed to guarantee an upper bound of convergence time determined regardless of the initial slip tracking errors. The proposed method guarantees a uniform ultimate boundedness of the wheel-slip tracking error based on an analysis of closed-loop stability. The performance of the proposed method is validated via simulations by using CarSim and MATLAB/Simulink for three scenarios on a jump TFC road surface, on a split TFC road surface, and on a suddenly cornering jump TFC road surface. The proposed method, which only employs a wheel speed sensor, achieves a shorter braking distance and stopping time in comparison with classical ABS.

Priority of provincial road maintenance in Kabupaten Aceh Besar based on analytic hierarchy process method

Road damage that has occurred on several roads has caused enormous losses, especially for road users, such as long travel times, congestion, accidents, and others. It is necessary to pay attention to this so that there is no deterioration in road quality due to road surface damage so that it can affect safety, comfort, and smoothness of traffic. Therefore, researchers damaged road surface conditions, which can affect the travel time of the vehicle. The purpose of this research is to identify the type and level of road damage and to determine road-handling priorities. The results of calculating the condition of each provincial road section in the Aceh Besar District using the PCI method are included in the very good, good and moderate categories, so that the type of handling can be determined is routine maintenance. From the results of the analysis of respondents by using Analytic Hierarchy Process (AHP), said that the priority road-handling by using several criteria, namely: the order of 1 is the type of treatment with a weight of 0.47, then the second is the condition of the road with a weight of 0.37, then the third-order is accessibility with a weight of 0.12, and the fourth place is a land use with a weight of 0.04. As for the alternative road-handling priority obtained a score’s greatest at road Keutapang Dua - Mata Ie with the acquisition of a score of 0.34, then alternate both at road Batas Kota Banda Aceh - Sp. Lam Ateuk 0.32, the third alternative on road Ir. M. Thaher 0.26, for the fourth alternative on road Sp. Lamreueng-Sp. Cot Iri 0.06, the fifth alternative on road Kota Jantho-Alue Glong 0.011, the sixth alternative on road Bts. Banda Aceh-Blang Bintang 0.010, and for the seventh alternative on road Krueng Raya - Batas Pidie with a score of 0.003. The first priority for road handling based on an assessment of road conditions using the PCI method is road Krueng Raya - Batas Pidie section.

DFMA analysis of front axle assembly of an excavator

The front axle assembly of a hydraulic excavator consists of front axle, stub axle and thrust bearing. The front axle carries the weight of the front part of the vehicle, as well as to facilitate steering and to absorb shocks due to road surface conditions. In addition, it absorbs torque applied on it due to the braking of vehicle. It is constructed with I-section in center and the ends are made either circular or elliptical. Stub axles are connected to the front axle by king pins. Front wheels are mounted on stub axle’s arrangement for steering. A nominal assembly gap in the front axle assembly has to be maintained for better performance and for easy maneuvering of the vehicle during operation. The gap depends on the model and the assembly dimensions of the front axle, stub axle and thrust bearing. A typical value ranging from 0.1 and 0.5mm is required for one particular model being manufactured by the local industry. It is reported that there are more number of assembly rejections in maintaining the said gap which lead to higher cost and downtime due to rework or interchange of parts. To reduce this, DFMA analysis was carried out using the concept of stack up tolerance to reduce the rejections and improve the performance of front axle assembly, without affecting the manufacturing.

The comparison between the method of Bina Marga and the pavement condition index (PCI) in road damage condition evaluation (case study: Prof. Ali Hasyimi Street, Banda Aceh)

Monitoring in-service road surface conditions is a part of road pavement maintenance. The most effective maintenance type will save costs and time. Road damage usually occurs on roads that have reached the design age, but some roads have been damaged before reaching the design age. To assess road damage, several methods can be used. The most widely used method in Indonesia is the Bina Marga method and the PCI (Pavement Condition Index) method. This study aims to compare both methods, in terms of accuracy and workability, in monitoring the surface condition of Prof. Ali Hasyimi street, which is located in the city of Banda Aceh. The data required for these two methods is the primary data, which are geometric, visual road damage, and traffic volume. Based on this study’s results, the Bina Marga method is easier and faster to use, while the PCI method is more detailed to utilize. In terms of accuracy, both methods relatively have the same accuracy.

Effect of pavement condition and geometrics at signalised intersections on casualty crashes

IntroductionThis study investigated the effects of pavement surface condition and other control factors on casualty crashes at signalized intersections. It involved conducting a before and after study for road surface condition and situational factors. It also included assessing the effects of geometric characteristics on safety performance of signalized intersections post resurfacing to control for the effect of pavement surface condition. Pavement surface condition included roughness, rutting, and skid resistance. The control factors included traffic volume, light and surface moisture condition, and speed limit. The geometric characteristics included approach width, number of lanes, intersection depth, presence of median, presence of shared lane, and presence of bus stop. MethodTo account for the repeated observations of the effect of light and surface moisture conditions in four occasions (day-dry, day-wet, night-dry and night-wet) Generalized Estimating Equation (GEE) with Negative Binomial (NB) and log link function was applied. For each signalized intersection in the sample, condition data are collected for the year before and after the year of surface treatment. Crash data, however, are collected for a minimum of three and maximum of five years before and after treatment years. ResultsThe results show that before treatment, light condition, road surface moisture condition, and skid resistance interaction with traffic volume are the significant contributors to crash occurrence. For after treatment; light condition, road surface moisture condition, their interaction product, and roughness interaction with light condition, surface moisture condition, and traffic volume are the significant contributors. The geometric variables that were found to have significant effects on crash frequency post resurfacing were approach width interactions with presence of shared lane, bus stop, or median. ConclusionsThe findings confirm that resurfacing is significant in reducing crash frequency and severity levels.Practical Applications: The study findings would help for better understanding of how geometric characteristics can be improved to reduce crash occurrence.

Fatigue performance evaluation for composite OSD using UHPC under dynamic vehicle loading

A novel composite orthotropic steel deck (OSD) using ultra-high performance concrete (UHPC) is comprised of an OSD and a thin UHPC layer that are connected through shear connectors. The innovative composite OSD system has been increasingly applied to long-span bridges in China to overcome the defect of conventional OSD that frequently suffers from fatigue cracking. However, the fatigue performance of the composite OSD system is usually evaluated with the deterministic analysis in previous studies, which may lead to inaccurate evaluation as many uncertainties, including the statistical properties of dynamic vehicle loadings and fatigue-prone details, have not been considered rationally. In this paper, the fatigue performance of the composite OSD using UHPC was investigated using the reliability-based fatigue analysis and compared with the fatigue performance of conventional OSD system. A three-dimensional vehicle-bridge coupled system was adopted to obtain the stress time histories of fatigue-prone details in the bridge decks under the action of dynamic vehicle loading. The vehicle model was determined based on the fatigue load pattern adopted in the AASHTO standard specifications and finite element models (FEMs) of both the conventional OSD and the composite OSD using UHPC were built based on a girder segment adopted from the HuMen Bridge in China. Four key influence factors, namely, the road surface condition (RSC), length of bridge deck FEM, vehicle speed, and overloading, were taken into consideration. The fatigue life of six typical fatigue-prone details in these two deck systems was evaluated and compared. The results show that the composite OSD using UHPC can effectively extend the fatigue life of OSD by at least 60% and even eliminate the risk of fatigue cracking for most fatigue-prone details. Compared to the reliability method, the fatigue life of OSD determined based on the deterministic method would be overestimated by 65–110% if the very poor RSC is considered. Besides, the composite OSD using UHPC exhibits a better fatigue performance than the conventional OSD system under the action of overloaded trucks. The results from the study can provide a reference for the design and maintenance of the composite OSD using UHPC.

Predicting Oil Production Sites for Planning Road Infrastructure: Trip Generation Using SIR Epidemic Model

Drilling activity produces a significant amount of road traffic through unpaved and paved local roads. Because oil production is an important contributor to the local economy in the state of North Dakota, the state and local transportation agencies make efforts to support local energy logistics through the expansion and good repair and maintenance of transportation infrastructure. As part of this effort, it is important to build new roads and bridges, maintain existing road pavement and non-marked road surface conditions, and improve bridge and other transportation infrastructure. Therefore, the purpose of this study is to review previous oil location prediction models and propose a novel geospatial model to predict drilling locations which have a significant impact on local roads, to verify and provide a better prediction model. Then, this study proposes a SIR (susceptible–infected–recovered) epidemic model to predict oil drilling locations which are traffic generators. The simulation has been done on the historical data from 1980 to 2015. The study found that the best fit parameters of β (contact rate) and μ (recovery rate) were estimated by using a dataset of historical oil wells. The study found that the SIR epidemic model can be applied to predict the locations of oil wells. The proposed model can be used to predict other drilling locations and can assist with traffic, road conditions, and other related issues, which is a much needed predictive model that is key in transportation planning and pavement design and maintenance.

Impact of pavement roughness and suspension systems on vehicle dynamic loads on flexible pavements

Several mechanistic-empirical software packages have been developed in the last two decades to address the impact of axle load and axle configuration on pavement responses and their performance. These software packages generally do not consider the vehicle pavement interaction. The interaction of truck suspension system with the roughness of the road surface may exert additional forces to the pavement.A process to quantify the impact of truck suspension systems and road surface condition on the damage exerted to the pavement is presented in this paper. The International Roughness Index (IRI) was used to simulate the road roughness. The truck-pavement interaction was then modeled to estimate the dynamic load applied to the pavement. The process followed to develop the algorithms is discussed, followed by a parametric study to demonstrate the interaction among the suspension properties, road roughness and vehicle speed. The impact of dynamic load on the pavement distresses and the progress of deterioration is also discussed.

Farm Vehicle Crashes on U.S. Public Roads: A Review Paper

Farm vehicles (FVs) are not primarily designed for road transportation purposes, but often need to share the roads with other motorists. The interference of these large, slow-moving vehicles with the regular traffic can lead to hazardous situations and cause severe crashes. Farm Vehicle Crashes (FVCs) are rare compared to the total number of road crashes, and hence, have been neglected by many. This has been reflected in various aspects including data collection, education, legislation, and prevention. The number of FVCs in the U.S. has been steady over the last decade. This paper conducts a literature review to put forth a better understanding of this safety issue from a transportation standpoint. The main goal of this study is to identify the characteristics of FVCs, the unique contributing factors in FVCs, and possible strategies to mitigate the issues involved. It appears that despite their lower frequency, the rate of severe injuries and fatalities in FVCs is significantly higher than the average for all crashes. The percentage of fatal crashes in FVCs can be nearly five times higher than average for all road crashes. Further, it is estimated that FVs are overrepresented in road crashes considering their low exposure on the roads. The crash contributing factors including time- dependent variables, weather and road surface conditions, location, road classification, manner of collision, and driver’s characteristics are discussed based on the result of multiple studies in different states of the U.S. Several unique characteristics of FVCs distinct them from non-farm vehicle crashes which can result from the characteristics of FVs, rural roads, and the nature of farming tasks. Improvements in lighting and marking, equipping farm vehicles with Rollover Protective Structure (ROPS) and seatbelts, educating the public and farmers, and roadway improvements are recommended as potential safety improvement strategies for mitigating the frequency and severity of FVCs.

Low speed performance based standards for the Nordic countries

Performance based standards (PBS) is an effective regulator policy which can address variation complexity in vehicle combinations. This paper investigates aspects of using computer simulation and mathematical models to assess the performance of vehicle combinations in low speed manoeuvring, and in particular roundabouts. A set of 22 vehicle combinations, including existing conventional heavy vehicles as well as prospective high capacity vehicles, is used to study the effects of turn angle and road surface conditions on the friction demand and swept path measures. Simulation results suggest that the friction demand measure is dependent on the available grip. This makes it hard to interpret and may not be suitable in the PBS framework. The swept path measure is relatively unaffected by friction levels, and can hence be calculated with simple and robust expressions not considering the road interaction. However, turn angle affects the swept path measure considerably, and should be addressed when designing the PBS scheme implementation into the legislations.

Analysis and Optimization of Low‐Speed Road Noise in Electric Vehicles

When a certain electric vehicle is driving at a constant speed of 40 km/h on the rough asphalt road, the rear passenger can obviously feel the ear pressure, which seriously affects the comfort. Through the analysis of objective data, it was found that the problem was caused by the road excitation, which leads to the coupling between the mode of the backup door and the mode of the acoustic cavity, and causes the resonance of the car cavity, thus causing the ear pressure sensation. To solve this problem, this paper optimizes the backup door by means of experiment and simulation, increases the dynamic vibration absorber, makes its modal frequency avoid the acoustic cavity modal frequency, and achieves the purpose of reducing the interior noise. After optimization, the vehicle noise is reduced by 8 dBA at 42 Hz under 40 km/h working condition of rough road surface, and the ear pressure sensation is reduced at the same time, thus improving the NVH (noise, vibration, and harshness) performance of the vehicle.

Analysis of the Accident Rate of the Constituent Entities of the Russian Federation

Every year, tens of thousands of road traffic accidents occur on the territory of Russia, characterized by different accident rates. Some of the most common are road traffic accidents, in the place of which violations of the mandatory requirements for the operational state of highways and railway crossings have been recorded under the conditions of ensuring road safety. The condition of the asphalt concrete road surface affects the grip performance of the vehicle with the road. It is necessary to study the statistics of road traffic accidents in the constituent entities of the Russian Federation located in different road and climatic zones in order to determine the dependence and the degree of influence of the state of the road surface on the number of accidents occurring.

Effect of operating conditions on a heavy truck ride comfort with hydro-pneumatic suspension system

The purpose of this paper is to analyze the performance of the hydro-pneumatic suspension system (HPSs) of a mining dump truck on ride comfort under operating conditions. To achieve goals, a 3-D full-vehicle vibration model of a mining dump truck with 10 degrees of freedom is set up to analyze the effects. A nonlinear mathematical model is set up based on the nonlinear characteristics of the HPSs to determine their vertical force which is connected with a 3-D full-vehicle vibration model. The effects of operating conditions on a heavy truck ride comfort are respectively analyzed through the values of the root mean square of acceleration responses of the vertical cab, pitch and roll angles of cab (awc, awphi and awteta). The analysis results indicate that the survey conditions have a great influence on vehicle ride comfort. Especially, the values of awc, awphi and awteta with the poor road surface condition respectively reduce by 43.1%, 45.9% and 61.8% compared to the very poor road surface condition at vehicle speed of 30 km/h and full load.

Wheel slip ratio regulation for investigating the vehicle's dynamic behavior during braking and steering input

In this study, the vehicle's dynamic behavior during braking and steering input is investigated by considering the quarter-car model. The case study for this research is a Sport-Utility Vehicle (SUV) with the anti-lock braking system (ABS) and nonlinear dynamic equations are considered for it along with Pacejka tire model. Regulating the wheel slip ratio in the optimal value for different conditions of the road surface (dry, wet and icy) during braking is considered as the ABS control strategy. In order to regulating the wheel slip ratio in the optimal value, an intelligent adaptive fuzzy controller that can perform online parameter estimation is considered. In this regard, the proposed controller tracks the optimal wheel slip ratio with changing the condition of the road surface from dry to wet and icy. The adaptive fuzzy controller consists of linguistic base, inference engine and defuzzifier section. The wheel slip ratio and vehicle longitudinal acceleration are selected as inputs of the controller, controller adapter and detector of the road surface condition. During braking and steering input, effective parameters of the wheel that are affected on the vehicle's dynamic behavior and its stability are investigated.

Motion Control of Peristaltic Mobile Robot with Adapting to Road Surface Conditions

Motion Control of Peristaltic Mobile Robot with Adapting to Road Surface Conditions

A Study on the Estimation of Winter Road Surface Conditions Using Measured Traffic Data

A Study on the Estimation of Winter Road Surface Conditions Using Measured Traffic Data

The State-of-the-Art Review on Applications of Intrusive Sensing, Image Processing Techniques, and Machine Learning Methods in Pavement Monitoring and Analysis

In modern transportation, pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians. Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users. Therefore, monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance, which in turn ensures public transportation safety. Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions. Advanced technologies can be employed for the collection and analysis of such data, including various intrusive sensing techniques, image processing techniques, and machine learning methods. This review summarizes the state-of-the-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches.