Lateral Wandering Research Articles

EVALUATION OF THE AIRPORT PAVEMENT CONDITION INDEX IN THE AIRCRAFT LATERAL WANDER AREA

EVALUATION OF THE AIRPORT PAVEMENT CONDITION INDEX IN THE AIRCRAFT LATERAL WANDER AREA

Sustainability implications of lateral wander modes for autonomous trucks

Autonomous trucks can bring changes in transport infrastructure in terms of sustainability based on the type of lateral wander mode used. In this research, two lateral wander modes, a zero wander and uniform wander mode are analyzed based on their applicability for sustainability by analyzing the CO2 emissions occurred during pavements life cycle. Both lateral wander modes have been analyzed in terms of occurrence of fatigue damage by using finite element analysis in ABAQUS. The fatigue damage predictions have then been used for planning the maintenance interventions for both lateral wander modes. Life cycle analysis has been performed for the analysis period of 30 years for the pavement section of 10 km. Results show that zero wander mode generates more emissions as a result of premature fatigue damage under channelized loading. The uniform wander mode leads to 20% less emissions when compared to zero wander mode. Moreover, the use of full depth reclamation during pavement’s life cycle improves the CO2 emissions by 15% when compared to traditional removal and reconstruction methods. Therefore, the uniform wander mode is favorable for improvement of pavement sustainability in terms of CO2 emissions.

Behavioral investigation of stochastic lateral wandering patterns in mixed traffic flow

The vehicles’ lateral movement exhibits inherent stochastic behavior, and when considered collectively, the traffic flow demonstrates certain lateral wandering pattern which serves a fundamental input for pavement design and sustainability analysis. Naturalistic driving trajectories show that the vehicles on neighboring lanes tend to interact laterally, which leads to correlated wandering on a multi-lane road. Compared with human-driven vehicles (HDV), autonomous vehicles (AVs) have a more centered wandering pattern, which accelerates the pavement fatigue. As the market penetration rate of the AVs changes, the wandering pattern of the mixed AVs flow would evolve accordingly, which further influence pavement performances. The evolutionary wandering pattern of mixed AVs flow which considers the interactions between neighboring lanes’ traffic flow is not fully studied yet. This research fills this gap with a stochastic behavioral lateral movement model that bridges the microscopic behavior and lateral wandering pattern. Firstly, a lateral movement model is developed, which assumes that lateral dynamics are influenced by lane markings, road boundaries, intra-lane interaction, and noise. The model is expressed in a stochastic differential form. The solution of the model which gives the lateral wandering is expressed by the Euler-Maruyama scheme, Fokker-Planck equation and Markov chain. Then the model is employed to investigate the wandering patterns under different scenarios. The results show that the model's outputs are consistent with current research results and empirical observations. This research provides additional insights regarding lateral wandering under mixed autonomous vehicle flow, and offers a theoretical tool for future road pavement design.

Effective lane width analysis for autonomous trucks

Lateral wander of autonomous truck can be further improved by optimizing the uniform wander. Increase in available lane width for the autonomous trucks can increase the performance efficiency of this mode. This research is based on finding the optimum, combination of lane width increment and asphalt layer thickness reduction among different scenarios. Therefore, In this research with assumed maximum lane width of 4.35 m, difference combination of lane width and asphalt layer thickness scenarios have been analyzed using finite element modelling in ABAQUS. Considering the base pavement width of 3.75 m, increment for each scenario is 15 cm and reduction in asphalt layer thickness is at 2 cm. Performance efficiency of each scenario is conducted while considering the initial construction costs and damage assessment for each scenario. Moreover, life cycle cost analysis (LCCA) is conducted for the base scenario and selected optimum scenario. Results show that increase in pavement width beyond 4.2 m, renders the scenarios uneconomical and thus, the scenario consisting of 4.2 m lane width and 16 cm asphalt layer thickness yield a maximum performance efficiency of 20% among all other alternatives. LCCA analysis shows that a difference in salvage value of 42 million Euros exists when compared with the base scenario. By selecting the optimum lane width of 4.2 m and asphalt layer thickness of 16 cm, Pavement lifetime can be further increased by 13 years with full depth reclamation used as maintenance intervention.

Wander Effect on Pavement Performance for Application in Connected and Autonomous Vehicles

Connected and Autonomous Vehicles (CAV) will change how road engineers design road pavements because they can position themselves within a traffic lane, keeping their position in the lane more precisely than human-driven vehicles. These vehicles will have lower lateral wandering, which can induce more damage to pavements, such as cracking and permanent deformation, than the conventional vehicles, with consequences for the infrastructures due to the increased cracking and reduced safety due to the rutting. Thus, it is essential to assess the wander effect on pavement performance to define policies for its implementation on CAV. This paper studies the impact of the lateral wander of the traffic on pavement performance, considering its fatigue and permanent deformation resistance. This impact can be used to define limits for the wander to minimize distresses on the pavement. The results of this study allow us to conclude that for a pavement with a 10 cm asphalt layer, the wander effect is more significant for fatigue life. A pavement life increase of 20% was observed for a wander of 0.2 m, while for 0.6 m, the fatigue life can increase up to 48%. For the permanent deformation, a pavement life increase of 2% for a wander of 0.2 m was observed, but for 0.6 m, the pavement life can be increased up to 34%.

A machine learning-based approach to assess impacts of autonomous vehicles on pavement roughness.

Studies have been initiated to investigate the potential impact of connected and automated vehicles (CAVs) on transportation infrastructure. However, most existing research only focuses on the wandering patterns of CAVs. To bridge this gap, an apple-to-apple comparison is first performed to systematically reveal the behavioural differences between the human-driven vehicle (HDV) and CAV trajectory patterns for the first time, with the data collected fromthe camera-based next generation simulation dataset and autonomous driving co-simulation platform, CARLA and SUMO, respectively. A gradient boosting-based ensemble learning model for pavement performance (i.e. international roughness index) prediction is then developed with the input features including three driving pattern features, namely, lateral wandering deviation, longitudinal car-following distance and driving speed, plus 20 othercontext variables. A total of 1707 observations is extracted from the long-term pavement performance database for model training purposes. The result indicates that the trained model can accurately predict pavement deterioration and that CAV deteriorates pavement faster than HDV by 8.1% on average. According to the sensitivity analysis, CAV deployment will create a greater impact on the younger pavements, and the rate of pavement deterioration is found to be stable under light traffic, whereas it will increase under congested traffic. This article is part of the theme issue 'Artificial intelligence in failure analysis of transportation infrastructure and materials'.

Influence of class A40 autonomous truck on rutting and fatigue cracking

AbstractEffects of autonomous trucks' different lateral wander modes have been analyzed in this research using a dload subroutine. Two lateral wander modes, a zero-wander mode in which a truck is programmed to follow a predetermined wheel path without any lateral movement and a uniform wander mode, where the truck uniformly distributes itself along the lateral width of the lane, are used. European class A40 truck has been modeled in ABAQUS code. Results show that fatigue life of pavement increases by 1.45 times if a uniform wander mode is used, which corresponds to a decrease in fatigue life of 14 months if a zero-wander mode is used. In case of rutting progression, 40% acceleration of rutting happens under a zero-wander mode. In case of uniform wander mode, rut depth decreases by 1.25 times against the zero-wander mode.

Truck platoon analysis for autonomous trucks

Selection of optimum platoon pattern based on types of trucks inside the platoon, the number of trucks in the platoon, headway distance, interplatoon distance as well as the use of different lateral wander modes for autonomous trucks has been analyzed. The objective of this research is to study the impacts of axle configurations, truck grouping, headway distance and lateral wander options on the performance of truck platoons. Four different headway distances from 2 to 5 m are compared. The first platoon PT-1 only consists of semi trailers, the second platoon PT-2 only consists of rigid body trucks and the third platoon PT-3 consists of equally distributed random traffic mix. Analysis has been conducted using the dload subroutine for projecting zero wander and uniform wander movements for each truck in the platoon on a three layered pavement crossection at vehicle speeds of 90 km/h for a total of 15 years of pavement lifetime consisting of 1.4 million equivalent single axle loads in finite element software ABAQUS. Results show that PT-3 platoon yields the minimum accumulation of damaging strains when compared against other platoon types. A headway distance of 5 m is suggested when using a zero wander mode and 3 m when using a uniform wander mode. In case of zero wander mode, fatigue life of the pavement decreases by 1.2 years and the use of uniform wander mode delays the rutting by 1.6 years, thereby increasing lifetime of the pavement.

Evaluation of Airport Pavement Base Layer Stiffness Characteristics via Embedded Field Sensors

Real-time stiffness monitoring of unbound aggregate layers using embedded field sensors is crucial for advanced airport pavement design and management. This paper describes research findings on monitoring base layer stiffness characteristics for airport pavements using an embedded bender element (BE) field sensor, inductive coil sensors, and pressure cells. A full-scale pavement test section was constructed at the Federal Aviation Administration (FAA)’s National Airport Pavement Test Facility (NAPTF). A BE field sensor, inductive coil sensor pairs, and pressure cells were installed in the unbound aggregate base to evaluate the layer stiffness, applied load stress, and deformation characteristics. A triple dual tandem gear loading module applied 58,000 lb per wheel to the tested section with a wander pattern consisting of 66 passes arranged in nine lateral wander positions. Dynamic responses of coil sensors and pressure cells were collected during the traffic test, whereas BE signals were collected after completing each wander pattern. Laboratory repeated load triaxial tests with BE instrumentation were also conducted to establish a correlation for converting BE field sensor readings to layer modulus properties. The in situ modulus characteristics of the aggregate base layer were evaluated during full-scale testing using two methods: shear wave velocities from a BE field sensor, and strain and stress measurements from coil sensors and pressure cells. The moduli estimated using both approaches fell into typical ranges of crushed aggregate bases and were highly comparable. The moduli from the dynamic sensor measurements clearly showed the effect of vehicle wander on aggregate base layer measured responses.

Influences of bus traffic loading on asphalt concrete rutting

ABSTRACT Permanent deformation is the primary failure mode for the asphalt concrete (AC) pavement in urban environment. It is mainly caused by a combination of heavy traffic load, low vehicle speed and channelised traffic. A rut prediction model would therefore be a valuable tool for planning maintenance scheduling and selecting an appropriate asphalt material. This study uses the PEDRO (Permanent deformation in asphalt concrete layers for roads) model to evaluate the rutting performance of flexible pavements in dedicated bus lanes and intersections in urban areas. For this purpose, three road sections along a bus lane in Malmö, Sweden, were selected. To achieve this, AC cores from the road sections were tested using a Shear Box Tester to characterise the asphalt mixtures. Traffic data such as axle load, tyre configuration, speed, and lateral wander distribution of vehicles, and climate data were measured for the selected sections. Field measurements were carried out to assess the structural conditions of the pavements and to measure transverse profiles. This study introduced a procedure for the evaluation and local calibration of the PEDRO rutting model. The results revealed that the prediction of the transverse profiles are generally in good agreement with the rut measurements.

Traffic channelisation and pavement deterioration: an investigation of the role of lateral wander on asphalt pavement rutting

ABSTRACT Accurate estimation of traffic load plays a crucial role in the economical design of pavements. The cross sectional distribution of the vehicle positions means that the traffic load is spread across the surface of the pavement. Several factors influence the distribution of vehicle positions and hence load. When wheel paths are perfectly aligned with each other, this is termed channelised traffic (or channelisation). This study investigated the impact of channelisation on asphalt pavement rutting. Data was collected on 100 sections of pavement in the city of Portsmouth, United Kingdom including vehicle/wheel positions and rut depths. Regression analysis was conducted to understand how the degree of channelisation influenced the rut depths that the traffic loading had created. The analyses revealed that the degree of channelisation of traffic has a statistically significant contribution to the progress of rutting. In this study, the difference between the maximum and minimum degrees of channelisation observed, related to a seven-fold difference in the rut depth. These findings give further guidance to pavement engineers when designing new pavements and considering the maintenance schedules for existing pavements, as it allows them to better predict the future condition and lifespan of a pavement.

Fatigue damage analysis of pavements under autonomous truck tire passes

Abstract Two different tire configurations consisting of a dual tire and a super single wide tire having different range and distribution of contact pressures have been analyzed. Along with the effect of speed on development of pavement damage at speeds of 5, 50 and 80 km h−1 under zero and uniform wander modes. Results show that at super slow speeds of 5 km h−1, at dual wheel moving at zero wander mode, decrease in fatigue life of the pavement is 3.5 years, which is 1.45 times more than the dual wheel moving at uniform wander and 3.4 times more than wide tire moving at uniform wander mode. The difference between fatigue damage at different lateral wander modes is prominent at speeds greater than 50 km h−1. A wide tire performs better than the dual wheel under zero wander configurations.

Study of Overtaking Maneuvers on Wide One-Way Roads in Weak Lane-Disciplined Traffic Using Naturalistic Driving Data

Drivers make assumptions and predictions on the expected paths of nearby vehicles. In traffic with weak lane discipline, prediction of the paths of other vehicles becomes more uncertain than in lane-based traffic because of frequent lateral wander. The situation becomes even more challenging on one-way roads where the scope for lateral wander is greater than on two-way roads. Study of overtaking maneuvers on wide one-way roads in the absence of lane discipline therefore becomes imperative. This paper investigates driver behavior while overtaking on wide one-way roads in disorderly traffic using naturalistic driving data collected by an instrumented vehicle. This study proposes definitions of the start and end of the maneuver that lead to behaviorally identifiable time points. The behavior of the overtaking vehicle driver is studied in both longitudinal and lateral directions. Data from 181 overtaking maneuvers on one-way roads of two different road widths are used to study the behavior. The primary observation of the present study is that, although the initial motivation for overtaking is a driver’s sense of urgency because the faster driver of the overtaking vehicle wants to avoid the slow-moving vehicle ahead, once the maneuver starts, the actions of the driver are guided by their concern for safety. One of the major implications of the present study is that the results can be used to develop microsimulation models to analyze driver behavior while overtaking in disorderly traffic streams.

Fatigue Life Predictions for a European Pavement Test Section Subjected to Individual and Platoon Truck Configurations

Truck platooning for the transportation of loads is a strategy recently proposed by the automotive sector to cope with traffic congestion, fuel consumption, and operational costs. This new way of configuring trucks changes the typical pressures pavements structures experience. For this reason, the research efforts of the pavement sector should be aligned with the automotive sector to propose road-friendly platoon configurations. This is one of the objectives of the European project ENSEMBLE. ENSEMBLE, as indicated by its acronym, works on ENabling SafE Multi-Brand pLatooning for Europe. In this context, the present study presents a real scale test done in the Applus IDIADA facilities to evaluate the fatigue behavior of a pavement structure subjected to individual and platoon truck configurations. The effects of parameters such as traffic distribution through the year and by time of day, percentage of platoons, truck loads, number of trucks in platoon configuration, lateral wandering, and inter-truck distances were evaluated. The study’s findings revealed that the reduced rest times between trucks in the platoon configuration reduce the recovery time of the asphalt layers, increasing the fatigue damage to the pavement at high temperature conditions. This underlines the need for further research to allow the proper implementation of truck platoons. For example, research is needed to define strategies to make truck platoon configurations more pavement-friendly and analyze the costs associated with the changes in the required road maintenance/rehabilitation treatments, among others.

A novel design of partially magnetized pavement for wireless power transfer to electric vehicles with improved efficiency and cost saving

As electric vehicles (EVs) tend to replace conventional gasoline vehicles, efficiently charging EVs with limit energy loss is critical. One promising solution is to utilize wireless charging module embedded in the pavement for dynamic charging. The existence of pavement layer between coils was regarded as a negative impact factor for wireless power transfer (WPT) by most previous studies. However, this study proposes an innovative design of partially magnetized pavement to improve the WPT efficiency via creating a magnetized pathway through the pavement layer. The specific magnetized area and location will be varied by the particular coil design. The basic WPT system with coils in air was first simulated and the results were validated by analytical solutions and experimental results. Finite element models (FEMs) of WPT-roadway systems were then built to analyze magnetic field and WPT efficiency of new design considering different coil embedment depth, vehicle wandering, magnetic properties of pavement layer. The results revealed the advantage of the partially magnetized pavement over conventional pavement for wireless power transfer, which did provide 1.5%–13.3% improvement of charging efficiency. Such advantage from partially magnetized pavement was more significant if that surface layer above transmitting coil was thicker or the magnetized part had higher magnetic permeability. Moreover, the efficiency improvement remained effective until the vehicle lateral wander reached 0.5 m. The economic analysis showed that a high electricity cost saving was brought with limited amount of magnetic materials needed.

Evaluation of Network-Level Data Collection Variability and its Influence on Pavement Evaluation Utilizing Random Forest Method

The use of pavement condition data to support maintenance and resurfacing strategies and justify budget needs becomes more crucial as more data-driven approaches are being used by the state highway agencies (SHAs). Therefore, it is important to understand and thus evaluate the influence of data variability on pavement management activities. However, owing to a huge amount of data collected annually, it is a challenge for SHAs to evaluate the influence of data collection variability on network-level pavement evaluation. In this paper, network-level parallel tests were employed to evaluate data collection variability. Based on the data sets from the parallel tests, classification models were constructed to identify the segments that were subject to inconsistent rating resulting from data collection variability. These models were then used to evaluate the influence of data variability on pavement evaluation. The results indicated that the variability of longitudinal cracks was influenced by longitudinal lane joints, lateral wandering, and lane measurement zones. The influence of data variability on condition evaluation for state routes was more significant than that for interstates. However, high variability of individual metrics may not necessarily lead to high variability of combined metrics.

Simple Method for Incorporating Lateral Wheel Wander in the Computation of Fatigue Damage in New Flexible Pavement Structures

The lateral position of trucks wheels when they pass over the pavement is not the same for all trucks. This variation in the lateral position of truck wheels is called wheel wander, and it is generally assumed to follow a normal distribution. For pavement design purposes, it is assumed that the standard deviation of this normal distribution is 250 mm. The lateral wheel wander reduces the accumulation of damage in a given point inside the pavement structure and therefore prolongs the fatigue life of pavements. The lack of lateral wander causes stress concentrations and therefore increased damage and distresses to pavements. This paper describes a method for incorporating any distribution for lateral wheel wander in the estimation of damage in flexible pavement structures using matrix construction and multiplication. This method was applied for two different pavement structures and several standard deviations of wheel wander. The results show that the lateral wheel wander phenomenon decreases the induced fatigue damages in the pavement structures when compared to that caused by channelized traffic (no wander). The results also show that the effect of wheel wander on the induced fatigue damage is less in thicker pavement. The equivalent axle load factor between distributed and channelized lateral wheel wander were calculated to demonstrate the effect of different standard deviations of wheel wander on the induced fatigue damage.

Vehicle Lateral Wander Measures Using Ultrasonic Sensors

This paper evaluates the measurement of vehicle lateral wander using ultrasonic sensors. Measurements were made on different sections of the Costa Rican National Road Network. The recorded data allowed to determine the cumulative frequency distribution, lateral wander data and a confidence interval for the measurements. In some routes, where the sample size is greater than 70 vehicles, the distribution of the lateral wander data adjusted to a normal distribution. However, in several cases the data does not resemble a normal distribution curve, or other distributions reported in the literature. Finally, an Android app was developed to automate the data collection process using the ultrasonic sensor setup, simplifying the measurement process. From the cumulative frequency results, obtained with the ultrasonic sensors, it was determined that most vehicles travel between 50 and 150 cm from the edge of the road. In order to validate the data, the results obtained with the ultrasonic sensor setup were compared with the results obtained by image analysis of video recordings. These image analysis is possible due to pavement markings every five centimeters on the pavement from the lane edge. The results from video recordings and ultrasonic sensors show a high coefficient of correlation.

Relationship between channelisation and geometric characteristics of road pavements

ABSTRACT Traffic loading is the primary factor considered when designing a pavement. It is suggested in some design guides that the spread of the traffic load across the pavement surface should be considered alongside the standard axle loading the pavement will need to carry over its lifespan. However, there is little guidance on how to predict the spread of traffic loads when designing a new pavement, and empirical studies supporting any such guidance is also limited. This study helps to address this gap through analyses of data collected on the vehicle positions on 100 sections of pavement in Portsmouth, United Kingdom. The analyses, found a positive linear association between the degree of lateral wander and both the lane width and road width. These results suggest that the use of a binary measure of vehicle position used in the UK design guidance may not be suitable. The results also highlight the importance of both lane and road width, contrary to the existing body of research that indicates only one or the other to be a determinant of vehicle position. These findings have significant potential benefits to pavement engineers when estimating the lifespan of new pavements.

Optimization of Lateral Wandering of Automated Vehicles to Reduce Hydroplaning Potential and to Improve Pavement Life

The deployment of automated vehicles (AVs) has many potential benefits, such as reductions in congestion and emissions, and safety improvements. However, two notable aspects of AVs are their impact on roadway hydroplaning and pavement life. Since most AVs are programmed to follow a set path and maintain a lateral position in the center of the lane, over time, significant rutting will occur in asphalt surfaced pavements. This study measured AV lateral wandering patterns and compared them with human driven vehicles. Both wandering patterns could be modeled with a normal distribution but have significantly different standard deviations. AVs have a standard deviation for the lateral traffic wander pattern at least three times smaller than human driven vehicles. The influences of AVs with smaller lateral wandering on pavement rutting and fatigue life were analyzed with the Texas Mechanistic-Empirical Flexible Pavement Design system. The research discovered that AVs would shorten pavement fatigue life by 20%. Additionally, pavement rut depths (RD) increased by 13% and reached critical values of the RD 30% earlier. Deeper ruts formed more quickly leading to thicker water films on wet roads, and consequently, a much higher risk of hydroplaning. The research also calculated maximum tolerable RDs at different hydroplaning speeds. AVs have a much smaller tolerable RD human driven vehicles because of a greater water film in the rutted wheel path. This research thus proposed an optimal AV lateral wandering pattern: a uniform distribution. A uniformly distributed lateral wandering pattern for AVs prolongs pavement fatigue life, reduces pavement RD, and decreases hydroplaning potential.