Passenger Car Research Articles

Traffic road noise and transportation energy efficiency

Future noise emission limits for passenger car are going to lower levels by 2024 -Social cost of noise for France in 2021, shows clearly that the dominant source of noise pollution is road traffic (81 Bn€ for a total of 146 Bn€) This R51 regulation is meant to lower the noise pollution from road traffic, but when looking closer to the sources and their contributions, in particular the tire/road noise interaction, the environmental efficiency of this regulation is questionable. Tire/Road interaction involves tires characteristics, that are constrained by an array of specification and it has been proven that there is a physical limit to what could be expected from the tire as far as tire/road interaction noise is concerned.Road surface however, shows very wide acoustic characteristics spread : over 15dBA from the quietest to the loudest asphalt, to be compared to 2dBA steps in the regulation and an environmental impact that will depend on the rolling stock renewal rate. This paper will present a new patented method from Renault enabling to assess road acoustic data mapping from a simple drive of a Megane E-Tech, quickly and efficiently, issuing the first ever noise pollution control maps.

Psychoacoustic assessment of automotive fan-systems

In the automotive industry, electrification trends worldwide are inducing an increase of noise sources emergences. This reinforces the acoustic assessment metrics and thresholds set by stakeholders to ensure acoustic comfort of car passengers and passersby. The main acoustic indicator, the overall Sound Pressure Level, is not relevant enough to depict pedestrian annoyance during exposure to fan-system noises. Currently, psychoacoustic assessment of these products is not systematic as the psychoacoustic metrics taken separately are not sufficient for sound quality ranking. In order to address this weakness, studies were performed by Valeo based on fan-system noise jury evaluations. It aims at providing a preference model consisting of an equation which combines several psychoacoustic metrics to assess fan-system noise annoyance; keeping in mind that Loudness -or overall SPL- high levels could mask underlying annoyances biasing its assessment. In a first step, the correlation between Overall SPL, Loudness and aeraulic power is highlighted based on standard benchmark test database. In a second step, since tonal noises affect the perceived annoyance, additional tonal metrics are analyzed versus Loudness, or acoustic classes. Tonality especially is then compared to other tonal criteria, before potential assessment of a preference model equation.

Multiple and Gyro-Free Inertial Datasets

An inertial navigation system (INS) utilizes three orthogonal accelerometers and gyroscopes to determine platform position, velocity, and orientation. There are countless applications for INS, including robotics, autonomous platforms, and the internet of things. Recent research explores the integration of data-driven methods with INS, highlighting significant innovations, improving accuracy and efficiency. Despite the growing interest in this field and the availability of INS datasets, no datasets are available for gyro-free INS (GFINS) and multiple inertial measurement unit (MIMU) architectures. To fill this gap and to stimulate further research in this field, we designed and recorded GFINS and MIMU datasets using 54 inertial sensors grouped in nine inertial measurement units. These sensors can be used to define and evaluate different types of MIMU and GFINS architectures. The inertial sensors were arranged in three different sensor configurations and mounted on a mobile robot, a passenger car and a turntable. In total, the dataset contains 45 hours of inertial data and corresponding ground truth trajectories. The data is freely accessible through our figshare repository.

Factors Affecting Single and Multivehicle Motorcycle Crashes: Insights from Day and Night Analysis Using XGBoost-SHAP Algorithm

This study aimed to identify and compare the risk factors associated with motorcycle crash severity during both daytime and nighttime, for single and multivehicle incidents in Thailand using 2021–2024 data. The research employed the XGBoost (Extreme Gradient Boosting) method for statistical analysis and extensively examined the temporal instability of risk factors. The results highlight the importance of features impacting the injury severity of roadway collisions across various conditions. For single motorcycle crashes, the key risk factors included speeding, early morning incidents, off-road events, and long holidays. In multivehicle crashes, rear-end collisions, interactions with large vehicles, and collisions involving other motorcycles or passenger cars were linked to increased injury severity. The findings indicate that the important factors associated with motorcyclist injury severity in roadway crashes vary depending on the type of crash and time of day. These insights are valuable for policymakers and relevant authorities in developing targeted interventions to enhance road safety and mitigate the incidence of severe and fatal motorcycle crashes.

Ride Comfort Efficiency of Passenger Car’s Seat Using the Structure of Negative Stiffness with Various Dynamic Models

Ride Comfort Efficiency of Passenger Car’s Seat Using the Structure of Negative Stiffness with Various Dynamic Models

Developing high-precision battery electric forklift driving cycle with variable cargo weight

Driving cycles are essential for assessing vehicle energy demand, estimating driving range, and evaluating environmental impacts. Numerous driving cycles have been developed for passenger cars and buses. However, tailored driving cycles for logistics vehicles, especially forklifts, remains limited. Therefore, we introduce high-precision driving cycles for battery electric forklifts, which include profiles of velocity and cargo mass. The construction of driving cycles involves route selection, data acquisition, micro-trip segmentation, characteristic parameters selection, driving pattern categorization, transition probability matrix development, and driving cycle construction and evaluation. The methods proposed for constructing driving cycles are based on Markov Chain, Micro-trips combinations, and genetic algorithms. The constructed driving cycles are evaluated using relative error analysis and a simulation model. The results confirm that these cycles accurately reflect actual forklift operations and can be utilized to estimate their energy consumption.

The Environmental Impacts of Future Global Sales of Hydrogen Fuel Cell Vehicles

During the last decade, developing more sustainable transportation modes has become a primary objective for car manufacturers and governments around the world to mitigate environmental issues, such as climate change, the continuous increase in greenhouse gas (GHG) emissions, and energy depletion. The use of hydrogen fuel cell technology as a source of energy in electric vehicles is considered an emerging and promising technology that could contribute significantly to addressing these environmental issues. In this study, the effects of Hydrogen Fuel Cell Battery Electric Vehicles (HFCBEVs) on global GHG emissions compared to other technologies, such as BEVs, were determined based on different relevant factors, such as predicted sales for 2050 (the result of the developed prediction model), estimated daily traveling distance, estimated future average global electricity emission factors, future average Battery Electric Vehicle (BEV) emission factors, future global hydrogen production emission factors, and future average HFCBEV emission factors. As a result, the annual GHG emissions produced by passenger cars that are expected to be sold in 2050 were determined by considering BEV sales in the first scenario and HFCBEV replacement in the second scenario. The results indicate that the environmental benefits of HFCBEVs are expected to increase over time compared to those of BEVs, due to the eco-friendly methods that are expected to be used in hydrogen production in the future. For instance, in 2021, HFCBEVs could produce more GHG emissions than BEVs by 54.9% per km of travel, whereas in 2050, BEVs could produce more GHG emissions than HFCBEVs by 225% per km of travel.

Short-term noise annoyance towards drones and other transportation noise sources: A laboratory study.

Noise from unmanned aerial vehicles, commonly referred to as "drones," will likely shape our acoustic environment in the near future. Yet, reactions of the population to this new noise source are still little explored. The objective of this study was to investigate short-term noise annoyance reactions to drones in a controlled laboratory experiment. Annoyance to (i) two quadcopters of different sizes in relation to common contemporary transportation noise sources (jet aircraft, propeller aircraft, helicopters, single car passbys), and (ii) different drone maneuvers (takeoff; landing; high, medium, and low flybys) flown at different speeds and elevations was systematically assessed. The results revealed that, at the same sound exposure level, drones are perceived as substantially more annoying than other airborne vehicles and passenger cars. Furthermore, for drone maneuvers, landings, and takeoffs are more annoying than flybys, as are maneuvers flown at low speed. Different loudness metrics (LAE, LDE, effective perceived noise level, psychoacoustic loudness level) accounted for drone noise annoyance ratings to an equal degree. An analysis of psychoacoustic parameters highlighted the significant link between drone noise annoyance and tonality, sharpness, and loudness level. The results suggest a different perception and an increased annoyance potential of drones, which will likely require specifically tailored legislation.

Global carbon transition in the passenger transportation sector over 2000–2021

The high-emitting and hard-to-abate passenger transport sector plays a crucial role in global deep decarbonization. To lead an equitable and rapid transition in the passenger transportation, this work is the first to develop a bottom-up modeling framework integrated with the latest decomposing structural decomposition methodology to assess and compare historical emission patterns and decarbonization efforts of 28 countries over the past two decades. Results indicate: (1) Carbon emissions from the global passenger transport sector increased between 2000 and 2021, peaking in 2019, with GDP per capita and population size being key drivers of rising carbon emissions across countries. (2) The decarbonization efforts of the global passenger transport sector varied by traffic mode. The largest contributors were passenger buses [−0.46 megatons of carbon dioxide per year (Mt CO2/yr)], followed by trains (−0.4 Mt CO2/yr), and airplanes (−0.28 Mt CO2/yr), while passenger cars (1.04 Mt CO2/yr) hindered the decarbonization process. (3) Although the global passenger transport sector has cumulatively decarbonized 3005.9 Mt CO2 and achieved a decarbonization rate of 5.1 %, regional performance varied significantly, exhibiting uneven and inadequate progress. Overall, the study provides an effective data-driven assessment framework for reviewing and comparing global and national passenger transport decarbonization performance, which will facilitate the planning of decarbonization pathways by global emitters and the early achievement of zero-carbon transport.

Correlation relationships of processes in the combustion engine in the RDE test

The article presents considerations on the processes taking place in the combustion engine in the in real driving operating conditions of a vehicle performing the RDE (Real Driving Emissions) test. The tests were carried out using a passenger car with a spark-ignition engine. The processes considered in the article were related to the engine operating states, exhaust emissions and fuel consumption, and the vehicle speed, which determines the engine operating conditions. The RDE test were carried out using PEMS (Portable Emissions Measurement System) equipment, and the following variables were recorded: vehicle speed, control, rotational speed, relative torque and relative engine power, emission pollutant intensity of: carbon monoxide, hydrocarbons, nitrogen oxides and carbon dioxide, the intensity of particle number and the fuel consumption intensity. The recorded signals were digitally processed, and the statistical properties of the variables and the mutual relation between the engine operating states were examined. The properties of the measured variables were investigated in the entire RDE test and in its constituent phases: the first, corresponding to vehicle movement in cities, the second – outside cities, and the third – on highways and expressways. The pollutant specific distance emission and the particle number specific distance as well as the specific distance fuel consumption were determined in relation to the average vehicle speed, and based on these results, the exhaust emissions and fuel consumption characteristics were created. Correlational studies of the considered variables were also performed. Pearson's linear correlation coefficients for the measured variables combinations were determined.

Clearing the air: microcosting the carbon impact of drug-susceptible pulmonary TB treatment.

<sec><title>BACKGROUND</title>More than 10 million individuals develop active TB each year. The diagnosis and treatment of TB create greenhouse gas emissions, contributing to climate change. This study estimates the carbon footprint (CF) of successfully treating one person with drug-susceptible pulmonary TB (DS-PTB) in India.</sec><sec><title>METHODS</title>We defined the cascade of care for DS-PTB using national guidelines, interviews, and direct observation. We estimated the inputs for TB diagnosis and treatment in United States dollars, kilowatts per hour, and kilometres travelled; we converted them into carbon dioxide emissions equivalents (CO₂e) using an appropriate calculator.</sec><sec><title>RESULTS</title>The CF of diagnosing and treating one person with DS-PTB in India is 103.8 kg CO₂e: 31.9% attributable to diagnosis and 68.1% to treatment. Emissions came primarily from first-line drugs (21.2%), hospitalisations (17.4%), and laboratory processes.</sec><sec><title>CONCLUSION</title>We conservatively estimate that treating all persons with TB in India would produce at least 290,640 metric tonnes of CO₂e per year, approximately the same emissions as 63,182 passenger cars in the United States. It is evident that one of India's leading public health challenges also contributes meaningfully to climate change.</sec>.

KLASIFIKASI DAN VOLUME KENDARAAN BINA MARGA DARI REKAMAN VIDEO LALULINTAS DENGAN METODE ARTIFICIAL INTELLIGENCE - YOLO V8 PADA JALAN TOL JAKARTA-BOGOR DAN JAKARTA-TANGERANG

The software helps solve things faster, e.g., Epanet software, Pipe Flow Expert, WaterCAD, SAP2000 planning software, etc. Likewise, in the field of calculating traffic volume with the development of artificial intelligence technology, using video recording, volume, and speed calculations can be done easily. At this time, the classification of traffic counting is only up to 3 (three) types of vehicles classified by YOLO V8, so in this research, the classification is added to be 6 (six) types of vehicles, namely mini cars, mobile passengers, small buses, big buses, small trucks, and large trucks, according to vehicle classification established in Indonesia. The research method is done by recording the traffic on the road and then video recording with the help of the software developed with the Python program so that the volume of the vehicle according to its classification is obtained. The result obtained from this research is compared to the manual traffic counting. The comparison between vehicle counting by the software and manual counting is mini-car 97.02%, passenger car 99.49%, small bus 96.94%, large bus 97.34%, small truck 93.21%, and large truck 97.18%.

Road traffic injury among elderly people and its determinant factors: a cross-sectional study.

Injuries from Road Traffic Accidents (RTAs), particularly among vulnerable groups such as the elderly, are considered a significant public health concern. The aim of this study was to show epidemiology of RTIs among the elderly people in the Eastern Azerbaijan province of Iran. This cross-sectional study included all patients over 60 years old who admitted to the Shohada Hospital from 2006 to 2016. Data were extracted from the Hospital Information System. Injuries types were classified based on the International Classification of Diseases (ICD-10). Descriptive statistics (Mean, median and frequency) and inferential statistics (The Pearson Chi-square test) were used for data analysis through SPSS-24 software. A total of 3509 RTAs involving patients over 60 years old from 2006 to 2016. These traffic-related injuries comprised 15% of all recorded injuries (23,321 cases). The mean age of the patients was 69.91 ± 7.61 years, with a predominant male representation (2324 patients, 64.74%). The median Length of Stay (LOS) in hospital was 3 days. Injuries most commonly affected the knee and lower leg regions (27.5%). The most frequent types of accidents were those involving car passengers (40.47%) and pedestrians (36.33%). The majority of RTAs occurred during the summer season. There was a significant difference in the rate of RTAs based on variables such as sex, age, season, and LOS (p < 0.001). The study highlights traffic-related injuries among the elderly, mostly affecting the knee and lower leg regions, especially during the summer season. The efforts should include enhancing safety measures for car passengers and pedestrians, particularly during the high-risk summer months. Also, it emphasizes the need for public transportation to improve safety for older people due to lower accident rates and senior-friendly features.

인도 내수용 승용차의 차체 디자인 요인 분석

인도 내수용 승용차의 차체 디자인 요인 분석

Perspectives on Childhood Lead Exposure Prevention: Looking Back and Looking Ahead.

Lead's neurotoxic properties and potential harmful effects to humans, particularly young children, have been recognized for decades, influencing public health policies to reduce its admixture in house paint and passenger car gasoline. We signal 3 emergent trends: firearm proliferation, complex international food supply chains, and equally complex product marketing strategies, which have opened opportunities for lead exposure to children from guns and ammunition, and lead contamination in children's food and consumer goods. Readers will also be apprised of Childhood Lead Poisoning Prevention Program and education strategies cultivated and advanced by the Centers for Disease Control and Prevention and its lead prevention partners. A national governmental policy update is included, as are future considerations.

Thermal Cameras and Their Safety Implications for Pedestrian Protection: A Mixed Empirical and Simulation-Based Characterization

Multiple sensing technologies exist for advanced driver support and driving automation systems. Car manufacturers combine different solutions to increase the robustness and operational capabilities of driving automation technology perception systems. One sensing method that did not achieve high market penetration with respect to other solutions is the thermal camera. Thermal cameras can operate in low-light and high-contrast conditions as they do not need external sources of illumination. Instead, they are sensitive to the infrared radiation emitted by any surface above 0 K. Thus, thermal cameras can be a suitable candidate to compensate for the weaknesses of visible cameras. To establish the potential benefit of thermal cameras for pedestrian protection, this paper reports on an experiment using state-of-the-art thermal imaging sensors. The authors’ scientific effort includes a characterization of the infrared sensor capability to identify pedestrians when coupled with a detection algorithm and provides a simulation-based investigation of the potential safety benefits of thermal camera adoption. The analysis additionally includes a heuristic characterization of the detection capabilities of a passenger car equipped with visible cameras to provide a baseline comparison. Ultimately, the thermal sensors return noteworthy detection capability that could lead to a potentially significant improvement in road safety on rural roads provided that the sensor has sufficient resolution.

Анализ применения гидравлических гасителей колебаний в конструкциях рессорного подвешивания подвижного состава железнодорожного транспорта

Purpose: consideration of the issue of the use of hydraulic vibration dampers in spring suspension of various types of railway rolling stock. The article provides an overview of the layout of hydraulic vibration dampers in the spring suspension of rolling stock, their advantages and disadvantages are given Methods: review and analysis of spring suspension designs of various types of traction and non-traction rolling stock in operation, as well as patented designs. Analysis of the arrangement schemes of hydraulic vibration dampers in the spring suspension of rolling stock. Results: the main reason for the use of hydraulic dampers in spring suspension is the inability of cylindrical springs to minimize the influence of oscillatory movements of rolling stock that occur during its movement. The necessity of using hydraulic vibration dampers in structures of various types of rolling stock is substantiated. The arrangement schemes of hydraulic vibration dampers are considered. Examples of the use of hydraulic dampers in spring suspension of various types of rolling stock are given. Practical significance: the necessity of using hydraulic vibration dampers is shown not only in the structures of the undercarriage of passenger cars and locomotives, but also in the spring suspension of freight cars. The use of hydraulic vibration dampers makes it possible to minimize the negative impact of oscillatory movements on both the structure of the rolling stock and the health of passengers and locomotive crews, as well as to increase the comfort of their stay. The use of hydraulic dampers in the spring suspension of freight rolling stock can increase the speed of its movement by improving the running qualities of freight cars and the degree of safety of transported goods.

Non-repeatability of the WLTP vehicle test results

The paper presents results of considerations on the repeatability of the passenger car test results obtained in the WLTP procedure on a chassis dynamometer. The research concerned the aspects of exhaust emissions and fuel consumption. Measurements were carried out in the WLTC test with a cold engine start and then in four WLTC (Worldwide harmonized Light vehicles Test Cycle) tests with a hot engine start. The following values were measured: average specific distance emissions of hydrocarbons, non-methane hydrocarbons, carbon monoxide, nitrogen oxides, particulate matter and carbon dioxide, specific distance particulate number, and operational fuel consumption. Thus, it was possible to assess the impact of the engine's thermal state at start-up on the test results and the nature of test results repeatability with the start-up of a hot engine. The repeatability of the test results was assessed based on the coefficient of variation obtained in the individual tests and the relationship of the maximum difference between measurement results values in the individual tests for a hot engine start. The obtained test results turned out to be very diverse for the considered parameters and indicated low repeatability. Values of carbon dioxide emissions and operational fuel consumption were definitely the least varied in individual hot engine start tests. The exhaust emission of particulate matter varied the most in individual test iterations. However, the specific distance particulate number was relatively similar between individual tests, less so than the exhaust emission of other pollutants. In the case of different engine thermal state at start-up, the emitted particulate number varied the most in the test results, while the emission of carbon dioxide and operational fuel consumption varied the least. The repeatability of executing the velocity process in WLTC tests at hot engine and cold engine start-up was also examined as processes determining exhaust emissions and fuel consumption. These tests were much more repeatable than the exhaust emission and fuel consumption.

Choice-based macroscopic lane-change prediction model for weaving areas

This paper introduces two macroscopic lane change models, separately for small vehicles (passenger cars and vans) as well as heavy vehicles. The model is structured using a Nested Logit discrete choice framework. The model was estimated and validated using unique trajectory data collected from a busy weaving section in Antwerp, Belgium. The models exhibit an average and maximum rate of inaccurate prediction results, amounting to 11% and 16%, respectively. Additionally, the model underestimates the total number of lane change maneuvers, with a margin of no more than 4.1–7.7%. This study aims to fill the gap in macroscopic lane change models, which mainly depend on theoretical underpinnings, by including empirical data from the analysis of more than 31,000 observed maneuvers. Furthermore, it differentiates among three maneuver intents, a unique alternative-specific discrete choice framework. This differentiation allows for the consideration of drivers’ systematic taste variations. In contrast to other models that utilize empirical datasets and are heavily dependent on expensive video-based data, including the entire traffic flow, this study introduces a novel approach for estimating the position and frequency of maneuvers by using just a small fraction (1–2%) of vehicle trajectories, supplemented by loop detector data, therefore eliminating the need for information from surrounding vehicles. Additionally, the work’s uniqueness is its validation methods extending beyond just numerical evaluations. The practical usability and usefulness of the model are shown in real-world traffic circumstances. Finally, the model is integrated in the context of a macroscopic simulation that represents a highly consistent lane balance based on the Scalable Quality Value statistics.

Классификация отказов и неисправностей легковых автомобилей с целью создания системы оценки технического состояния

The article provides an overview and classification of motor vehicle faults (class: passenger cars). The cause-and-effect relationships «Fault-RTA» are studied. Failure of steering and suspension elements entails loss of vehicle control, which leads to traffic accidents. It is determined that safety is significantly affected and cannot be self-diagnosed by articulated joints of ball joints and stabilizer struts. The ball joint is the support of the hub. Failure of the ball joint leads to loss of control of the vehicle’s trajectory due to the fact that the wheel occupies an arbitrary and uncontrolled position in the wheel arch. Wear of the ball joint consists in the occurrence of play in the joint, which is now diagnosed by human senses. The technical condition is assessed using a primitive method: the vehicle is suspended and, using a lever, the mechanic applies various loads to the ball joint. The article predicts the possibility of creating a self-diagnostic system for joints with articulated joints. Along with this, a statistical analysis of emerging failures and malfunctions in cars by brand and class is carried out, which allows us to assert the constancy of the problem under study. An analysis of the relationship between failures and malfunctions with road accidents is carried out, which reflects the most frequent causes of accidents due to vehicle malfunctions.