Highway Test Research Articles

Introducing the rubber plate impact method: a versatile alternative to close proximity test for tire-pavement noise characterization on asphalt highways

Despite its widespread use, the close proximity (CPX) test for tire-pavement noise is limited to existing pavements, posing challenges for timely and effective corrections of noisy pavements. Additionally, the CPX test entails significant procurement and operation costs. Addressing these issues, this study introduces the rubber plate impact (RPI) method as a simple experimental technique for assessing tire-pavement noise in both laboratory and field settings. The RPI test utilizes the folding motion of the treaded rubber plate on the road surface to simulate air pumping and tread impact noise as two main contributors to tire-pavement noise. Indoor RPI tests on asphalt concrete samples of dense graded asphalt and porous asphalt mixes revealed dominant effects of air void content and associated surface texture on the level of noise. The RPI testing procedure was verified at 17 highway test sections, where both CPX and RPI tests were conducted for comparison. Multiple linear regressions between RPI and CPX data were analyzed to propose CPX prediction models at different speeds (80, 100, 120 km/h), and the performance of these prediction models was validated with independent noise datasets collected from four different highway routes. The findings suggest promising prospects for the RPI test as a cost-effective and versatile alternative to CPX for tire-pavement noise characterization on asphalt-surfaced roads, with implications for road materials design and noise mitigation strategies.

An integration scheme of simultaneous cycle slips determination combining improved geometry-free combination and TDCP model for undifferenced GNSS data

Fast and reliable cycle slip determination can ensure successive ambiguity resolution and precise positioning. Generally, it is not difficult to determine big cycle slips using the linear combination of observations, for instance, the geometry-free (GF) combination and the Hatch–Melbourne–Wübbena (HMW) combination. However, the participation of pseudorange observations may fail to identify small cycle slips. This contribution proposes an integration scheme combining the improved geometry-free (IGF) combination and time-difference carrier phase (TDCP) model to determine simultaneous cycle slips for undifferenced kinematic data. The IGF combination, which is improved from the modified geometry-free (MGF) combination and utilizes the Gauss floor function to take the decimal part of GF, can directly determine small cycle slips on a specific frequency. The TDCP model is used to estimate the differences of position and clock error between adjacent epochs by least-square adjustment using clean phase observations, and repair the remaining cycle slips by the predicted TDCP measurements obtained from the predetermined parameters. The proposed method is tested against 1 Hz kinematic dataset with simulation and highway dataset with real cycle slips. In the simulation test, all cycle slips can be correctly repaired by IGF for L1/L5, E1/E5 and E1/E5a. These combinations are unavailable for MGF. Compared to the HMW-GF method, the repair success rate of IGF improves from 96.80% to 99.16%, and the number of incorrect cases reduces from 9650 to 2535. The IGF-TDCP integration scheme can further improve the performance of IGF, whose repair success rate is more than 99.97% and incorrect cases are 38. The highway test shows that the proposed method effectively processes simultaneous cycle slips on more than half of the tracking satellites caused by the overpasses, even in the case of simultaneous 3 second data gaps on 5 satellites of 6 tracking satellites.

Research on Dueling Double Deep Q Network Algorithm Based on Single-Step Momentum Update

Vehicle behavior decision control plays a crucial role in the development of autonomous driving. However, existing autonomous driving behavior decision control algorithms based on deep reinforcement learning face several challenges, such as low efficiency in updating target network data and a lack of effective balancing between old and new experiences. To address these issues, this paper proposes a dueling double deep Q network (dueling DDQN) algorithm based on a single-step momentum update mechanism. Firstly, a single-step momentum update mechanism is designed to significantly improve the update speed of target network parameters and achieve a balanced weighting of old and new experiences during the parameter update process. Subsequently, the network structures of dueling networks and DDQNs are integrated to enhance the understanding capability of autonomous vehicles concerning their current states. Finally, tests are conducted on the OpenAI Gym simulation platform to validate the effectiveness of the proposed algorithm. The results verified that the dueling DDQN algorithm with single-step momentum updates contributes to improving the convergence speed of autonomous driving car behavior decisions. Compared with the DQN and DDQN algorithms, the proposed algorithm achieved a success rate increase of 6.0 and 8.4 percentage points in the challenging three-lane highway Test Scenario 1, and a success rate increase of 16.7 and 2.9 percentage points in Test Scenario 2, respectively. These findings demonstrate a safer and more efficient performance in autonomous driving decision-making.

Discussion on the Status Quo of Non-Destructive Testing Technology in Highway Engineering and Strategies of Improving the Quality of Testing

Highway test and detection technology play a very important role in controlling the quality of road and bridge engineering and improving the maintenance of roads and bridges. The study of highway bridge test detection technology is both theoretically and practically useful. Road and bridge test and detection is a complicated task. With the development of science and technology highway and bridge engineering test and detection technology has also made great progress. The continuous improvement of test and detection technology has brought good social benefits to road and bridge construction. This article discusses the problems in test and detection technology of highway bridges and how to improve the quality of test and detection.

Development of rutting forecasting models for distinct asphalt pavement structures in RIOH testing track using different approaches

Rutting is one of the main exacerbation phenomena of the asphalt pavements, which seriously affects road safety and the quality of service. The predicted models are indispensable for preventing and controlling the damage caused by the exacerbation of pavement management systems. This paper is centered on developing more appropriate and exact rutting forecasting models for estimating the rutting performance of distinct asphalt pavement structures on the basis of the field data set of the Research Institute of Highway (RIOH) testing track. First of all, the critical influential factors giving rise to the rutting evolution are identified through analyzing the field data set of the RIOH testing track. After that, the framework of the rutting forecasting models based on the artificial neural networks (ANNs) coupled with genetic algorithm (GA) (GA-ANNs-based rutting forecasting models), the frameworks of the experiential and mechanics-based experiential rutting forecasting models are established according to the implicit relationship between the rutting and the key influential factors. Then, the unknown parameters of the experiential and mechanics-based experiential rutting forecasting models for different asphalt pavement structures are designed by the multivariate nonlinear optimization algorithm. Finally, the applicability of the GA-ANNs-based rutting forecasting models, the experiential and mechanics-based experiential rutting forecasting models are discussed and illustrated through analyzing their forecasting effects. The result illustrates that the proposed rutting forecasting models have better applicability for different asphalt pavement structures (i.e., the semi-rigid base pavement structure, the rigid base pavement structure, the flexible base pavement structure, and the full depth AC pavement structure).

Correlating the Asphalt-Binder MSCR Test Results to the HMA HWTT and Field Rutting Performance

Asphalt binder is one of the key constitutive components of hot-mix asphalt (HMA) that considerably affects its rutting performance. In particular, the high-temperature rheological properties measured from the multiple stress creep and recovery (MSCR) test are critical for correlating to the HMA rutting resistance. In this study, the Texas flexible pavements and overlays database was used as the data source to investigate the effect of asphalt-binder high-temperature rheological properties on the HMA rutting resistance. The study methodology was based on correlating the results of the MSCR test and the Hamburg wheel-tracking test (HWTT) to HMA field rutting performance. The data matrix for the study included asphalt binder (PG 64-22) from three different sources, three widely used Texas HMA mixes (fine gradation to coarse gradation), and five in-service highway test sections constructed using the same asphalt binders and HMA mixes. In general, the MSCR nonrecoverable creep compliance parameter, Jnrdiff, showed fairly strong correlations with the HMA rutting performance in the laboratory and field. The percent recovery parameter (R), on the other hand, exhibited the potential to ascertain and quantify the presence of modifiers in the asphalt binders. Furthermore, the test results indicated that material source/supplier has an impact on the rheological properties of the asphalt binders with the same performance grade (PG). Overall, the use of the MSCR test to quantify the asphalt-binder high-temperature rheological properties indicated the potential to compliment the laboratory HWTT test for correlating with the field HMA rutting performance in terms of the effects of asphalt binder.

Key Technologies of Physical and Virtual Test Rig for Railway Freight Car body

On the one hand, considering that the traditional fatigue method of railway freight cars is based on damage as a parameter, the influence of stress waveform cannot be considered. On the other hand, physical experiments have the characteristics of lag, long period, and high cost. The full-scale physical test and virtual test of car body are carried out. First of all, the data processing method of small deletion and the inverse problem load acquisition method based on data to data are proposed. Secondly, the dynamic stress calculation method with the bench as the boundary is proposed. Finally, taking the obtained load as the input of the physical and virtual bench, a new fatigue test method for simulating the running attitude of the car body line is completed. The acceleration RMS error of the C70E gondola body is less than 6%, the stress RMS is less than 13%, and the equivalent mileage is 3.125 million highway test results show that the car meets the life requirements of the car body. The inverse problem analysis results of virtual and physical tests are basically consistent, and the study of this method provides a basis for improving the fatigue reliability of freight car bodies.

Problems Needing Attention in Highway Test and Detection and Countermeasures

Problems Needing Attention in Highway Test and Detection and Countermeasures

Highway Test Management Level Promotion Strategy

Highway Test Management Level Promotion Strategy

Application of Information Management in Highway Test

Application of Information Management in Highway Test

Analysis of Problems and Countermeasures in Highway Test and Inspection

Analysis of Problems and Countermeasures in Highway Test and Inspection

Application of Information Technology in Highway Test and Inspection Work

Application of Information Technology in Highway Test and Inspection Work

Discussion on Information Management and Application of Highway Test and Inspection

Discussion on Information Management and Application of Highway Test and Inspection

Researching Diesel car CO2 emissions in cold and warm-up transient test cycle

Research of CO2 emissions is not only important, but it is standard practice for homologation, technical inspections, registration of vehicles and for environmental greenhouse effect. Different agencies are taking into consideration the fact that greenhouse emissions are seriously impacting the climate change and events on the planet. Road traffic and transportation are, beside animal agriculture, the most significant polluters in dense areas, with high values of emissions. For diminishing the impact of automotive sector in the emissions field, the present work approaches the practical side of this topic. During the testing, some results will allow the definition of those conditions in which the pollutant emissions fall into control and are drastically diminished. Main objective of the paper is to research the CO2 emissions generated by a Diesel engine in a transient test cycle, both at cold operation and after warm-up phase. Second objective is to analyse the graphics from low speed and medium speed operation regimes. The CO2 emission are influenced by fuel consumption, engine speed and coolant temperature. Highway testing of CO2 emissions are to be made in further and advanced research.

Lean-Stratified Combustion System with Miller Cycle for Downsized Boosted Application - Part 2

<div class="section abstract"><div class="htmlview paragraph">Automotive manufacturers relentlessly explore engine technology combinations to achieve reduced fuel consumption under continued regulatory, societal and economic pressures. For example, technologies enabling advanced combustion modes, increased expansion to effective compression ratio and reduced parasitics continue to be developed and integrated within conventional and hybrid propulsion strategies across the industry. A high-efficiency gasoline engine capable for use in conventional or hybrid electric vehicle platforms is highly desirable. This paper is the second of two papers describing the multi-cylinder integration of a technology package combining lean-stratified combustion with Miller cycle for downsized boosted applications. The first paper describes the design, analysis and single-cylinder testing conducted to down-select the combustion system deployed to the multi-cylinder engine. This paper defines a light-duty engine package capable of achieving a 35% fuel economy improvement at US Tier 3 emission standards over a naturally aspirated stoichiometric baseline vehicle. A multi-mode combustion system was developed enabling highly efficient lean-stratified operation at light-load and stoichiometric Miller-cycle operation at mid- to high-loads. A central direct-injection four-valve layout was designed with high-tumble ports and a bowl-in-piston capable of stable operation under highly dilute mixtures when properly matched to fuel spray characteristics, injection strategy, and a high-energy ignition system. Boost system layout and base engine architecture were selected to minimize parasitics and maximize aftertreatment effectiveness. A multi-cylinder engine was developed and calibrated over a steady-state map. Results fed vehicle simulations over the EPA city and highway test cycles to predict the fuel economy improvement and tailpipe emissions potential. Fuel economy improvements over the baseline vehicle were projected at 42% and 39% for active-urea and passive-ammonia SCR aftertreatment systems respectively. Controls complexity to achieve regulatory compliance and the cost of the lean aftertreatment system were identified as the primary challenges to commercial viability.</div></div>

Advancing Platooning with ADAS Control Integration and Assessment Test Results

<div class="section abstract"><div class="htmlview paragraph">The application of cooperative adaptive cruise control (CACC) to heavy-duty trucks known as truck platooning has shown fuel economy improvements over test track ideal driving conditions. However, there are limited test data available to assess the performance of CACC under real-world driving conditions. As part of the Cummins-led U.S. Department of Energy Funding Opportunity Announcement award project, truck platooning with CACC has been tested under real-world driving conditions and the results are presented in this paper. First, real-world driving conditions are characterized with the National Renewable Energy Laboratory’s Fleet DNA database to define the test factors. The key test factors impacting long-haul truck fuel economy were identified as terrain and highway traffic with and without advanced driver-assistance systems (ADAS). Track and on-highway testing guided by SAE J1321 procedures were conducted to assess truck platooning operation under the characterized real-world driving conditions. On-highway testing is done on a route in Indiana representing operation of long-haul Class 8 trucks in the United States. The road includes low-, medium-, and high-grade segments. The highway test results of a two-truck platooning configuration indicate considerable fuel-saving reduction comparing to the test track data collected under ideal driving conditions. The test data indicate that platooning could lead to increases in fuel consumption during traffic or high-grade portions of the route, causing reduction of the overall fuel saving on the road comparing to test track results. However, integration of ADAS features on the lead truck during on-road tests leads to significant improvement of fuel saving for both trucks in CACC operation.</div></div>

Vehicular Communication Management Framework: A Flexible Hybrid Connectivity Platform for CCAM Services

In the upcoming decade and beyond, the Cooperative, Connected and Automated Mobility (CCAM) initiative will play a huge role in increasing road safety, traffic efficiency and comfort of driving in Europe. While several individual vehicular wireless communication technologies exist, there is still a lack of real flexible and modular platforms that can support the need for hybrid communication. In this paper, we propose a novel vehicular communication management framework (CAMINO), which incorporates flexible support for both short-range direct and long-range cellular technologies and offers built-in Cooperative Intelligent Transport Systems’ (C-ITS) services for experimental validation in real-life settings. Moreover, integration with vehicle and infrastructure sensors/actuators and external services is enabled using a Distributed Uniform Streaming (DUST) framework. The framework is implemented and evaluated in the Smart Highway test site for two targeted use cases, proofing the functional operation in realistic environments. The flexibility and the modular architecture of the hybrid CAMINO framework offers valuable research potential in the field of vehicular communications and CCAM services and can enable cross-technology vehicular connectivity.

Feasibility Validation of a 5G-Enabled mmWave Vehicular Communication System on a Highway

In this paper, we present an mmWave-based vehicle-to-infrastructure (V2I) communication system operating at a 22 - 23GHz frequency band, and evaluate its feasibility and effectiveness on an actual highway through a field trial. Based on a network layout that is well suited for the mmWave-based high mobility vehicular applications, we provide physical and higher layer design details, which are based on the 3GPP 5G New Radio (NR) standard. We then investigate key technologies to overcome the performance degradation of the mmWave-based system due to high mobility: a user equipment (UE)-oriented beam switching-based beamforming scheme, a fast and robust handover procedure with a two-step timing advance (TA) update, and mobile relaying for providing better quality-of-service (QoS) to in-vehicle UEs. The proposed system design and related key technologies are validated through a real-world testbed in an actual highway test site. Regarding this, we describe the specifics of testbed implementation and provide the experimental results obtained from the trial. The validation results show that the 5G NR-based mmWave system is feasible and effective for realizing high data rate vehicular communication on a highway.

МНОГОСЕНСОРНАЯ БЕСПРОВОДНАЯ СЕТЕВАЯ СИСТЕМА ДЛЯ МОНИТОРИНГА УРАГАНОВ

A wireless sensor system is described. Pressure sensor measurements are compared with National Weather Service data and wind tunnel test data. It then describes a minivan highway test that was used to evaluate the effect of sensor housing shape on pressure measurements. Computational Fluid Dynamics (CFD) analysis was also performed to complement the wind tunnel and road van tests, as well as to determine optimal mesh shapes and sizes, boundary conditions, and the best turbulence model that would reproduce the measured pressures. (UV) The following describes the Hurricane Simulator tests that were used to evaluate the effect of wind gusts on pressure and automatic/cross-correlations of pressure and velocity between different sensors. A CFD simulation of the UF Hurricane Simulator test was also performed to evaluate the sensitivity of turbulence models in capturing true pressure and velocity changes on the test site due to gusts. Vibration testing using a shaker table to analyze the effect of structural vibration on sensor pressure measurements is described.

Correlating the asphalt-binder high-temperature properties (DSR) to HMA permanent deformation (RLPD) and field rutting: A laboratory-field study

Asphalt-binders are part of the key material constituents affecting the performance of hot-mix asphalt (HMA), and ultimately, the field performance of flexible pavement structures. Quite often, it is desired/useful to predict the HMA permanent deformation (viscoelastic) properties and field rutting from the asphalt-binder properties. Using the Texas flexible pavements and overlays database, namely the Texas Data Storage System (DSS), as the data source, this laboratory-field study was conducted to correlate the asphalt-binder properties to HMA permanent deformation (viscoelastic) properties and field HMA-layer rutting performance of in-service highway sections. Data extracted from the Texas DSS included asphalt-binder high-temperature rheological properties measured using the dynamic shear Rheometer (DSR) test, HMA permanent deformation (PD) and viscoelastic properties from the repeated load permanent deformation (RLPD) test, and field rut depth (RD) data for the HMA layers of in-service highway test sections. Two Texas asphalt-binder types, four HMA mixes, and four in-service field highway sections were used in the study. For some parametric comparisons, the corresponding results indicated good statistical correlations among the asphalt-binders, HMA mixes, and field rutting performance, with a coefficient of determination (R2) over 60%. Overall, the study findings indicated that the HMA PD properties and field HMA-layer rutting can be predicted from the asphalt-binder high-temperature rheological properties, with a linear or logarithmic model, to an accuracy exceeding 60%.