Standard Vehicle Research Articles

Crop leaf disease detection and classification using machine learning and deep learning algorithms by visual symptoms: a review

<span lang="EN-US">A Quick and precise crop leaf disease detection is important to increasing agricultural yield in a sustainable manner. We present a comprehensive overview of recent research in the field of crop leaf disease prediction using image processing (IP), machine learning (ML) and deep learning (DL) techniques in this paper. Using these techniques, crop leaf disease prediction made it possible to get notable accuracies. This article presents a survey of research papers that presented the various methodologies, analyzes them in terms of the dataset, number of images, number of classes, algorithms used, convolutional neural networks (CNN) models employed, and overall performance achieved. Then, suggestions are prepared on the most appropriate algorithms to deploy in standard, mobile/embedded systems, Drones, Robots and unmanned aerial vehicles (UAV). We discussed the performance measures used and listed some of the limitations and future works that requires to be focus on, to extend real time automated crop leaf disease detection system.</span>

Adaptive Center-of-Mass Relocation for Aerial Manipulator Fault Tolerance

This work proposes a fault tolerant aerial manipulator based on a standard hexarotor vehicle, which is able to maintain independent control of torque and vertical thrust in case of motor failure by adequately changing the manipulator configuration and therefore modifying the position of the system’s center of mass. By analyzing the disturbance torque that the manipulator exerts on the vehicle, conditions to achieve stable flight and operation limits are established. To provide an experimental proof of concept, several flights are performed, both in indoor and outdoor environments, for different size and weight of manipulators.

Charging operations in battery electric bus systems considering fleet size variability along the service

This paper analyzes the new operations induced by the energy range limitation in battery electric bus (BEB) systems to ensure the service provision along the whole day. An operating model has been developed to estimate the number of resources to be deployed (extra vehicles and charging facilities) for two charging schemes: charging at bus garage facility and opportunity charging at on-street chargers. Firstly, the model calculates the entrance and exit time of buses in service assuming an unlimited battery capacity, caused by demand and headway variations in different time periods along day. Then, based on the previous results, the model estimates the moment when vehicles will run out of energy and proposes a charging schedule as well as new vehicle movements between chargers, bus garage and routes to maintain the targeted headway. Consequently, the model is able to calculate the number of resources needed and the total cost for a given route and battery size, allowing cost and performance comparison to diesel and hybrid powertrains. The estimated results in two bus routes in Barcelona indicate that the purchasing cost of BEB vehicles (670,000 euros/veh for articulated, 500,000Euros/veh for standard vehicles, both depreciated over a lifetime of 15 years), battery packs (231 Euro/kWh purchased, depreciated over a lifetime of 10 years), as well as the investment in chargers, are still high to clearly justify their cost-competitiveness against diesel or hybrid counterparts. Nevertheless, if the acquisition cost of both vehicles and battery pack are only reduced by 9%, the BEB technology may present cost savings for transit agencies. It only happens if the fleet size is as large as the corresponding to diesel and hybrid technologies. Opportunity charging is resulted to be more cost- efficient than charging at bus garage for small battery packs, routes with acceptable time headway adherence and, specially, when fast chargers are located very close to terminal stops. Nevertheless, when the real bus route design and operation do not fulfill these standards, charging scheme at bus garage is preferable.

Anti-Rollover Control of a Counterbalance Forklift Based on Roll Energy Classification

This study proposes an energy stability index suitable for a counterbalance forklift, aiming to solve the problem that the traditional vehicle stability index load transfer rate is difficult to accurately judge the stability state of such a forklift. The analysis of the structure of the counterbalance forklift and contact relationship between the body and rear axle are used as bases to establish a two-stage dynamic model and derive real-time instability energy of a forklift truck in the rollover process under different conditions. Additionally, this research proposes an anti-rollover control strategy of the counterbalance forklift based on roll energy classification. The corresponding calculation formula of the forklift energy stability index is selected according to different stability conditions to perform roll energy classification. An anti-rollover oil cylinder and active rear wheel steering are used as an anti-rollover control actuator, and an anti-rollover control is implemented based on model predictive control. Last, a simulation based on European standard operating conditions and real vehicle test verification is conducted. Results show that the anti-rollover control strategy based on roll energy classification can effectively reduce the risk of forklift rollover and improve the stability and active safety of a counterbalance forklift.

Study on 3D printed auxetic structure-based non-pneumatic tyres (NPT’S)

ABSTRACT The customized 3D printer will enable us to make cost-effective and usable rapid prototypes of TPU (Thermoplastic Polyurethane) based NPT. The current article’s objective is to investigate 3D printing technique based on FDM using a DIY 3D printer and TPU based auxetic structures based on NPT (Non-Pneumatic Tyre). Auxetic structures were used in the current research, instead of air, to retain energy and have a cushioning effect, thereby providing passengers with a relaxing journey. A comparative analysis was carried out between three distinct cell geometries to develop simple NPT models. Three different structures considered for FEA-based software testing static loading conditions of a standard passenger vehicle. CAD models were generated and performed a static analysis on ANSYS software. Through FEA simulation, reentrant hexagonal type auxetic structure is the most suitable one for a city utilitarian vehicle.

Historiographical Reflections on the Beethoven Year 250

For a certain subset of eminent Beethoven scholars, the celebration of Beethoven's 250th birthday in 2020 represented a challenge. In taking up the opportunity to communicate with a wider population of educated music lovers, the standard vehicle, a Beethoven biography, was off the table for them – because they had already written one. In the three books reviewed here, each author responds to this dilemma by focusing on themes in reception history. I will attempt to clarify their main points, comment on similarities and differences in their approaches, and evaluate how successful each one might be in in making recent Beethoven scholarship more accessible for the general reader. I will argue that all three of these books successfully target the more musically literate segment of lay readers, and that any weak points arise at the intersection between their academic content and the address to these members of their presumed readership.

An Improved Model for Design Fatigue Load of Highway Bridges Considering Damage Equivalence

Reasonable fatigue load should be determined before bridge fatigue analysis. However, the design frequency calculation method of the standard vehicle does not always make sense when the standard vehicle load model that is provided by existing standards is adopted, as the weights (equivalent coefficients) variation of different vehicle types are not considered from the perspective of damage equivalence. The method through direct damage calculation is workable but the process is usually laborious and time-consuming. To solve this problem, the traffic data of 35 highway sites involving 15 provinces in China were collected and the fatigue load spectrum were derived. The equivalent coefficients of each vehicle type at all of the 35 locations were calculated directly and the relationship with the corresponding gross vehicle weight was obtained formulaically through statistical analysis. Therefore, the design frequency of the standard vehicle can be calculated by the product of the actual frequency for a certain type of vehicle and the corresponding equivalent coefficient. The effectiveness of the proposed method was verified from the perspective of damage equivalence compared with the existing-standard method, and its flexibility and applicability for complex traffic conditions such as China were also demonstrated. In addition, three grades for the design frequency were put forward as references in relevant project design.

An Automotive Ferrofluidic Electromagnetic System for Energy Harvesting and Adaptive Damping.

Vibration energy harvesting is receiving significant interest due to the possibility of using extra power in various machines and constructions. This paper presents an energy-harvesting system that has a structure similar to that of a linear generator but uses permanent magnets and magnetorheological fluid insets. The application of a standard vehicle example with low frequencies and amplitudes of the excitations was used for the optimization and experimental runs. The optimization for low excitation amplitudes shows that the best magnetic field change along the slider is obtained using differentially orientated radial magnets of 5 mm in width. This configuration was used for the experimental research, resulting in 1.2–3.28 W of power generated in the coils. The power conditioning system in the experimental research was replaced by loading resistors. Nevertheless, the initial idea of energy harvesting and a damping effect was confirmed by the circuit voltage output.

Morphometric study of humpback whale mother-calf pairs in the Sainte Marie channel, Madagascar, using a simple drone-based photogrammetric method

Morphometric studies of humpback whales (Megaptera novaeangliae) occurring in the Indian Ocean area have been limited by the technology currently available. In the Sainte Marie channel, Madagascar, straightforward aerial single-camera photogrammetry was tested on mother-calf pairs that combines standard Unoccupied Aerial Vehicle (UAV) with free, easy-to-access, and user-friendly software. The goals of the study were to estimate mother and calf body measurements and to investigate the effect of maternal parity (primiparous versus multiparous, based on length) on calf size. A mean length of 12.4±1.2 m for mothers (N = 16) and 5±0.9 m for calves (N = 16) was estimated. The size of calves did not depend significantly on maternal parity. The photogrammetry method used was simple and cost-effective, yet produced convincing morphometric measurements with acceptable precision and accuracy. The coefficients of variation (CVs) of repeated estimates and the level of error were relatively low (CV = 2.31 % for a known-sized object and average CV = 2.52 % for individual whales; average error = 1.8 % for a known-sized object). These results will encourage more teams to study the morphometry of large marine mammals despite limitations in terms of resources.

Penerapan Norma Hukum Klausul Baku Dalam Klausul Penarikan Kendaraan Bermotor Pada Perjanjian Pembiayaan Konsumen

This article aims to consumer financing agreements, standard clauses that have made previously by finance companies are stipulated as fixed requirements and cannot negotiate anymore. In the consumer financing agreement, there is a fiduciary guarantee so that a vehicle withdrawal clause include as a consequence of the breach of contract carried out by the consumer. This vehicle withdrawal clause often creates problems ahead between finance companies and consumers as in the District Court's Decision No. 105/Pdt.G/BPSK/2012/PN.Ska and No. 24/Pdt.G/BPSK/2013/PN.Skw. The problem in this research is about how the legal force of the standard clause in the consumer financing agreement according to the regulations in force in Indonesia, how the legal protection of consumers the application of the vehicle withdrawal clause in the consumer financing agreement and how the legal reasoning of judges in assessing the validity of the vehicle withdrawal clause in a consumer financing agreement (Study of District Court Decisions No. 105/Pdt.G/BPSK/2012/PN.Ska and No. 24/Pdt.G/BPSK/2013/PN.Skw). The research employed normative laws and analytically descriptive. This research also using the statute approach and conceptual approach. Analysis of the data used in legal materials in this research will carry out in a qualitative analysis of primary data and secondary data that describe and analyze the standard clauses and vehicle withdrawal clauses in consumer financing agreements, as well as concluding by deductive method. This study concludes that the legal force of a standard clause in a valid and binding consumer financing agreement applies as a law to the parties as long as it meets formal and material conditions based on Law No.8/1999 concerning Consumer Protection, OJK Regulation No. 1/POJK/07/2013 concerning Consumer Protection in the Financial Services Sector, OJK Circular Letter No.13/SE.OJK.07/2014 concerning Standard Agreement and OJK Regulation No. 35 /POJK.05/2018 concerning Business of a Financing Company. Legal protection for consumers in the application of a vehicle withdrawal clause because of a breach of contract by the consumer is preventive legal protection and repressive legal protection. Legal reasoning for judges in making decisions does not consider the validity of the agreement process in the consumer financing agreement because the vehicle withdrawal clauses listed can categorize as defects in the agreement abuse of circumstances.

A Dynamic Evolution Method for Autonomous Vehicle Groups in a Highway Scene

Vehicle groups that are composed of autonomous vehicles can increase the perception range of vehicles, and their dynamic evolution can provide guidance for the operation of autonomous vehicles. Most existing studies on vehicle group formation neither propose a standard vehicle group model, nor consider vehicle mobility and dynamic topology of vehicle groups. Instead, they focus on detecting dynamic evolution without predicting it. This work proposes a dynamic evolution method for autonomous vehicle groups. It first defines five vehicle states and their transitions. Then, it proposes an autonomous vehicle group formation method based on vehicle states and formulates an autonomous vehicle group model. Next, it uses meta vehicle group sequences to manage vehicle groups at different times. Finally, it gives detection and prediction methods of vehicle group dynamic evolution. Extensive simulation results show that the proposed method can be used to establish interconnection among autonomous vehicle nodes, detect dynamic evolution characteristics inside a vehicle group precisely, and predict dynamic evolution trends of vehicle groups effectively.

Analysis of the rider’s body movement during the intervention of the Autonomous Emergency Braking system for Motorcycles (MAEB)

Among the rider assistance systems for powered-two-wheelers (PTWs) that are currently in the developing stage, autonomous emergency braking (identified by the acronym MAEB - Motorcycle Autonomous Emergency Braking) was shown to be promising to significantly improve the safety of such vehicles. This system, which is already available on passenger cars and trucks (known as AEB), reduces the vehicle speed in the event of a forthcoming collision. The lack of implementation of AEB on standard motorcycles is due to the characteristic capsize instability of PTWs and their complex dynamics, which is, strongly influenced by the motion of the rider. In a recent field-test campaign within the EU funded project “PIONEERS”, tests were conducted with common riders as participants to evaluate the intervention of MAEB in urban riding scenarios. A combined analysis of the data recorded from the vehicle, data related to the movement of the rider’s body measured through an inertial measurement unit and videos recorded during the test, allowed characterizing the different behaviours of the rider’s body in response to the activation of the automatic braking system in straight riding conditions. The results showed that body movement can be used as an indicator of the riders’ ability to control the vehicle under automatic braking conditions. In addition, in tests conducted with 0.5 g automatic decelerations, riders showed to be able to recover to natural riding position within the timeframe of the automatic braking activation event. This study defined an innovative method for evaluating the response of motorcyclists to the braking intervention and provides insights into the applicability of MAEB on standard vehicles.

Analysis on the difference of DC energy consumption of electric vehicles under repeat cycles

In order to avoid the problem of too many AC energy consumption cycles and time-consuming for the standard electric vehicle driving range test, the DC energy consumption test can be used to obtain the energy consumption of the test cycle at any time period and estimate the driving range. However, the rationality of intercepting part of the circulating DC energy consumption to estimate the whole process still lacks sufficient experimental support. Therefore, in this paper, two different electric vehicle prototypes were selected, and a complete energy consumption test experiment was carried out according to the standard test process. Through the test of DC energy consumption, the difference characteristics of electric vehicle driving braking energy and energy consumption under repeated cycles were analyzed. The fluctuation range provides data support for the use of DC power to evaluate the energy consumption of electric vehicles

A Novel Capacity Estimation Method for the Lithium Batteries Using the Enhanced Coulomb Counting Method With Kalman Filtering

As the use of energy storage systems (ESSs) and electric vehicles (EVs) increases, the importance of lithium-ion (Li-ion) batteries is also growing. The accurate capacity estimation of a battery is useful for detecting the degradation and end-of-life of the battery for scheduled maintenance and replacement, thereby improving the reliability of battery-powered systems. However, many of the capacity estimation methods developed thus far are offline methods and are not suitable for online monitoring. In this study, a novel capacity estimation method for Li-ion batteries is proposed, based on the enhanced coulomb counting (ECC) method. Typically, the battery capacity calculated by ECC has a large error owing to the error in the state of charge estimation. Therefore, additional means are required to obtain an accurate value for the battery capacity. The Kalman filter is an optimal estimator of the hidden state with Gaussian noise and is applied to the capacity values calculated by the ECC method. The performance of the proposed method in estimating capacity is verified through experiments with a Li-ion battery operated using a standard vehicle driving schedule. The results show that the online capacity estimation using the proposed method is performed successfully within 10 h with a 1.7% error.

Kerbside NOx and CO concentrations and emission factors of vehicles on a busy road

Vehicular emissions contribute to roadside pollutants in cities, yet on-road emission estimates remain relatively uncommon. Nevertheless, they make an important contribution to exposure along Hong Kong's congested roads and street canyons. This study used kerbside microsensor-based monitors on Hennessy Road, one of the busiest roads in the north part of Hong Kong Island, to determine both concentrations and emission factors (EFs) of NOx and CO. Kerbside NOx and CO concentrations are skewed, with high concentrations representing plume segments from larger vehicles. The average EFs for each minute of traffic was determined from the pollutant concentration ratio with ΔCO2. These related to bus frequency for NOx, and EURO 4 or lower-emission standard vehicles for CO. The 1-min mean EFNOx 7.55 g kg−1 and EFCO 12.6 g kg−1 are typical for flows for the fleet dominated by buses, but highly skewed (Weibull shape parameter ∼0.44). Individual vehicle EFs were determined from peaks in NOx, CO and CO2, and number plates. Leading and trailing parts of the plume segments gave similar EFs (R2 > 0.95), suggesting this method was reasonably robust across the vehicle passage. Nevertheless, these EFs were also skewed, but the shape parameter was again ∼0.44. EFNOX for vehicle classes was: buses > goods vehicles > private cars > vans > taxis and diesel > petrol > LPG, with larger engine sizes also dominant. Differences were more difficult to assess with CO, but LPG vehicles had the highest EFs. Our EF estimates lay in the range found in previous studies but differ from fleet emissions calculated for regulatory purposes in Hong Kong (EMFAC). However, some high EMFAC emitters were also high in our estimates for individual vehicles. Vehicles may not perform on-road as inventory calculations suggest. The high EF variability found in our study implies that a large sample is required to assess the likely emissions from a vehicle fleet.

Unmanned Aerial Multi-Object Dynamic Frame Detection and Skipping Using Deep Learning on the Internet of Drones

The Internet of Drones (IoD) has a revolutionary impact on monitoring and preserving the environment. Traffic regulations face enormous challenges due to rapid growth in the number of vehicles. In IoD, multiple-aerial-drone video sensing infrastructure can increase detected objects. However, the main difficulty lies in picture quality due to lighting conditions, the angle of view, and the physical structure of vehicles. This research mainly focuses on the development and deployment of a deep-learning-based system to analyze traffic congestion. The model uses multiple drone video feeds and vehicle information to detect, classify, and count a transport vehicle in a live traffic feed. The model is trained with a deep learning approach to first align the video frame and then detect the object in a top-down aerial drone video. The dynamic skipping method helps process a long video feed and accurately compares the video frame to the viewer, and then, using the standard vehicle query (i.e., make, model and year of manufacture), detect traffic scenarios in real time. The proposed model has many applications requiring a particular area to monitor real-time data analysis and drone routine tasks.

Multi-speed gearbox design and shifting control optimization to minimize fuel consumption, exhaust emissions and drivetrain mechanical losses

Internal combustion engine vehicles (ICEVs) still represent a major fraction of the global vehicle market and enhancements of conventional vehicle powertrain design have been considered a viable large-scale alternative to reach short-term sustainable goals focused on the reduction of air pollutant emissions and fuel consumption. Thus, the purpose of this paper is to employ a multi-objective optimization for the ICEV drivetrain design and gear shifting control aiming at the minimization of fuel consumption, exhaust emissions and gearbox power losses. The optimization problem is solved by the Interactive Adaptive-Weight Genetic Algorithm (i-AWGA) and comprises different design variables of the multi-speed transmission and differential system, considering constructive constraints. The i-AWGA procedure also optimizes the fuzzy logic shifting controller by defining its input and output membership functions, fuzzy rules and respective weights. The vehicle model is evaluated under a combined driving cycle, therefore robust powertrain configurations can be obtained by the optimization process. The best trade-off solution results in the reduction of gas emissions in 2.32% HC, 3.44% CO and 23.78% NOx, along with the 15.6% fuel savings, facing the standard vehicle.

Histopathological Profiles of Rats (Rattus norvegicus) Induced with Streptozotocin and Treated with Aqueous Root Extracts of Ruellia tuberosa L.

Diabetes mellitus (DM) is a serious worldwide health threat since the number of people with DM is forecasted to grow annually. Thus, effective and affordable treatment is urgently needed. Our previous studies used n-hexane and hydroethanolic root extracts of Ruellia tuberosa L. which significantly affected diabetic rats. In this study, aqueous R. tuberosa L. root extracts were used as treatments for the diabetic rat model and their effects were evaluated. Diabetes was generated by the administration of streptozotocin (STZ) at 20 mg/kg within 5 sequential days. Male Wistar rats were orally treated with the extracts and standard drug (metformin 200 mg/kg) and vehicle every day for 4 weeks. Hypoglycemic effects were assessed for normal, diabetic control, standard, and extract-treated groups. Histopathology was also carried out for the pancreatic, hepatic, and kidney tissues. The progression of diabetes was considerably diminished after extract treatment. In treated rats, the highest dose of extract induced a decline in blood glucose and serum malondialdehyde (MDA) levels at 25% and 35%, respectively. Furthermore, aqueous extract of R. tuberosa L. treatment decreased MDA levels in the pancreas by 12%. Histologic examination of the organ tissues of diabetic rats showed deteriorating alterations. After treatment, histopathological damages to the tissues and cells were reversed. The results of the experiments recommend that aqueous extract of R. tuberosa L. has antidiabetic effects on STZ-induced diabetic rats; nevertheless, a higher dose of the aqueous extracts is needed to achieve more significant results.

An Overview on Automated Vehicles

A self-driving car is a machine that can really hear and function without the need for human intervention. A human rider is never needed to maintain control of the vehicle or to be in the vehicle at the same time. A self-employed vehicle should be able to do all of the duties that a competent human driver can. A standard vehicle should be capable of traveling to any place. Thousands of hours have been recorded on US highways by self-driving vehicles, such as Google's robotic vehicle prototype, but they are not yet commercially accessible. Self-sufficient vehicles use a range of technologies. It may be developed to assist navigation using GPS sensor data. Sensors and other equipment should be used to avoid accidents. And also use a variety of technologies, such as extended truth, in which a vehicle delivers data to drivers in novel and innovative ways. Many people think that substantial autonomous vehicle development will aggravate current man-made car insurance and traffic regulations. Extensive research on autonomous cars is taking place not just in the United States, but also in Europe and other areas of the world. According to industry analysts, it will only be a matter of time until individuals are able to use a device on a regular basis as a result of such advances. The construction and device design of an autonomous vehicle, as well as the control system module that enables the vehicle to travel independently, are covered in this article. The CaRINA I model was used to test and validate the team's autonomous navigation and driver assistance technologies. Our technology covers modifications to mechanical vehicles as well as the creation and implementation of an integrated computer architecture.

Electric vehicle additive sounds: Detection results from an outdoor test for sixteen participants

Electric vehicles are significantly quieter than standard internal combustion engine vehicles. Although this is a benefit to the acoustic soundscape, it presents a safety concern, particularly to the vision impaired. Because of this, governments around the world have mandated that artificial sounds be added to electric vehicles in order to improve pedestrian safety. In the United States, these regulations are embodied in a National Highway Transportation Safety Administration document, FMVSS-141. This document provides guidance on the 1/3 octave-band frequency content, overall SPL, and measurement procedures that must be followed for a vehicle to be certified. This talk will present the results of a listener test with 16 participants who pressed a button upon detection of an approaching vehicle equipped with a FMVSS-141 compliant additive sound. Results are presented at probability of detection versus distance. This provides a unique view of the effectiveness of these sounds and additional aspects of this problem such as additive sound contribution to noise pollution and listener false alarm rates. Lastly, the talk will cover difficulties with this type of outdoor testing and recommendations for conducting them in a virtual environment.