Subjects -> ENGINEERING (Total: 2844 journals)
    - CHEMICAL ENGINEERING (259 journals)
    - CIVIL ENGINEERING (255 journals)
    - ELECTRICAL ENGINEERING (182 journals)
    - ENGINEERING (1420 journals)
    - ENGINEERING MECHANICS AND MATERIALS (454 journals)
    - HYDRAULIC ENGINEERING (60 journals)
    - INDUSTRIAL ENGINEERING (101 journals)
    - MECHANICAL ENGINEERING (113 journals)

ENGINEERING (1420 journals)                  1 2 3 4 5 6 7 8 | Last

Showing 1 - 200 of 1205 Journals sorted alphabetically
3 Biotech     Open Access   (Followers: 9)
3D Research     Hybrid Journal   (Followers: 22)
AAPG Bulletin     Hybrid Journal   (Followers: 11)
Abstract and Applied Analysis     Open Access   (Followers: 4)
Aceh International Journal of Science and Technology     Open Access   (Followers: 9)
ACS Nano     Hybrid Journal   (Followers: 452)
Acta Geotechnica     Hybrid Journal   (Followers: 7)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 10)
Acta Nova     Open Access   (Followers: 1)
Acta Polytechnica : Journal of Advanced Engineering     Open Access   (Followers: 4)
Acta Scientiarum. Technology     Open Access   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access   (Followers: 1)
Active and Passive Electronic Components     Open Access   (Followers: 8)
Adaptive Behavior     Hybrid Journal   (Followers: 9)
Adsorption     Hybrid Journal   (Followers: 5)
Advanced Energy and Sustainability Research     Open Access   (Followers: 8)
Advanced Engineering Forum     Full-text available via subscription   (Followers: 14)
Advanced Engineering Research     Open Access  
Advanced Journal of Graduate Research     Open Access   (Followers: 4)
Advanced Quantum Technologies     Hybrid Journal   (Followers: 1)
Advanced Science     Open Access   (Followers: 13)
Advanced Science Focus     Free   (Followers: 7)
Advanced Science Letters     Full-text available via subscription   (Followers: 13)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 11)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 20)
Advanced Theory and Simulations     Hybrid Journal   (Followers: 5)
Advances in Catalysis     Full-text available via subscription   (Followers: 8)
Advances in Complex Systems     Hybrid Journal   (Followers: 12)
Advances in Engineering Software     Hybrid Journal   (Followers: 31)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 20)
Advances in Fuzzy Systems     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 22)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 30)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 27)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 10)
Advances in Natural Sciences : Nanoscience and Nanotechnology     Open Access   (Followers: 36)
Advances in Operations Research     Open Access   (Followers: 14)
Advances in OptoElectronics     Open Access   (Followers: 6)
Advances in Physics Theories and Applications     Open Access   (Followers: 21)
Advances in Polymer Science     Hybrid Journal   (Followers: 54)
Advances in Porous Media     Full-text available via subscription   (Followers: 6)
Advances in Remote Sensing     Open Access   (Followers: 59)
Advances in Science and Research (ASR)     Open Access   (Followers: 8)
Aerobiologia     Hybrid Journal   (Followers: 4)
Aerospace Systems     Hybrid Journal   (Followers: 10)
African Journal of Science, Technology, Innovation and Development     Hybrid Journal   (Followers: 8)
AIChE Journal     Hybrid Journal   (Followers: 38)
Ain Shams Engineering Journal     Open Access   (Followers: 7)
Al-Nahrain Journal for Engineering Sciences     Open Access  
Al-Qadisiya Journal for Engineering Sciences     Open Access   (Followers: 2)
AL-Rafdain Engineering Journal     Open Access   (Followers: 3)
Alexandria Engineering Journal     Open Access   (Followers: 3)
AMB Express     Open Access   (Followers: 1)
American Journal of Applied Sciences     Open Access   (Followers: 27)
American Journal of Engineering and Applied Sciences     Open Access   (Followers: 12)
American Journal of Engineering Education     Open Access   (Followers: 20)
American Journal of Environmental Engineering     Open Access   (Followers: 16)
American Journal of Industrial and Business Management     Open Access   (Followers: 31)
Annals of Civil and Environmental Engineering     Open Access   (Followers: 3)
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Pure and Applied Logic     Open Access   (Followers: 6)
Annals of Regional Science     Hybrid Journal   (Followers: 10)
Annals of Science     Hybrid Journal   (Followers: 10)
Annual Journal of Technical University of Varna     Open Access   (Followers: 1)
Antarctic Science     Hybrid Journal   (Followers: 1)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 3)
Applicable Analysis: An International Journal     Hybrid Journal   (Followers: 2)
Applications in Energy and Combustion Science     Open Access   (Followers: 4)
Applications in Engineering Science     Open Access   (Followers: 1)
Applied Catalysis A: General     Hybrid Journal   (Followers: 8)
Applied Catalysis B: Environmental     Hybrid Journal   (Followers: 22)
Applied Clay Science     Hybrid Journal   (Followers: 6)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 16)
Applied Engineering Letters     Open Access   (Followers: 5)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 4)
Applied Nanoscience     Open Access   (Followers: 11)
Applied Network Science     Open Access   (Followers: 3)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 6)
Applied Physics Research     Open Access   (Followers: 7)
Applied Sciences     Open Access   (Followers: 6)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 6)
Arab Journal of Basic and Applied Sciences     Open Access  
Arabian Journal for Science and Engineering     Hybrid Journal   (Followers: 5)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 6)
Archives of Thermodynamics     Open Access   (Followers: 13)
Arctic     Open Access   (Followers: 7)
Arid Zone Journal of Engineering, Technology and Environment     Open Access   (Followers: 2)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
ArtefaCToS : Revista de estudios sobre la ciencia y la tecnología     Open Access   (Followers: 1)
Asia-Pacific Journal of Science and Technology     Open Access  
Asian Engineering Review     Open Access  
Asian Journal of Applied Science and Engineering     Open Access   (Followers: 2)
Asian Journal of Applied Sciences     Open Access   (Followers: 2)
Asian Journal of Biotechnology     Open Access   (Followers: 9)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 7)
Assembly Automation     Hybrid Journal   (Followers: 2)
ATZagenda     Hybrid Journal  
ATZextra worldwide     Hybrid Journal  
AURUM : Mühendislik Sistemleri ve Mimarlık Dergisi = Aurum Journal of Engineering Systems and Architecture     Open Access   (Followers: 1)
Australasian Journal of Engineering Education     Hybrid Journal   (Followers: 3)
Australasian Physical & Engineering Sciences in Medicine     Hybrid Journal   (Followers: 1)
Australian Journal of Multi-Disciplinary Engineering     Hybrid Journal   (Followers: 2)
Autocracy : Jurnal Otomasi, Kendali, dan Aplikasi Industri     Open Access  
Automotive and Engine Technology     Hybrid Journal  
Automotive Experiences     Open Access  
Automotive Innovation     Hybrid Journal   (Followers: 1)
Avances en Ciencias e Ingenierías     Open Access  
Avances: Investigación en Ingeniería     Open Access   (Followers: 6)
Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 2)
Bangladesh Journal of Scientific and Industrial Research     Open Access  
Basin Research     Hybrid Journal   (Followers: 6)
Batteries     Open Access   (Followers: 11)
Batteries & Supercaps     Hybrid Journal   (Followers: 7)
Bautechnik     Hybrid Journal   (Followers: 3)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 29)
Beni-Suef University Journal of Basic and Applied Sciences     Open Access   (Followers: 3)
Beyond : Undergraduate Research Journal     Open Access  
Bhakti Persada : Jurnal Aplikasi IPTEKS     Open Access  
Bharatiya Vaigyanik evam Audyogik Anusandhan Patrika (BVAAP)     Open Access   (Followers: 1)
Bilge International Journal of Science and Technology Research     Open Access   (Followers: 1)
Biointerphases     Open Access   (Followers: 1)
Biomaterials Science     Full-text available via subscription   (Followers: 14)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 14)
Biomedical Engineering Letters     Hybrid Journal   (Followers: 6)
Biomedical Engineering: Applications, Basis and Communications     Hybrid Journal   (Followers: 6)
Biomedical Microdevices     Hybrid Journal   (Followers: 9)
Biomedical Science and Engineering     Open Access   (Followers: 8)
Biomicrofluidics     Open Access   (Followers: 7)
Biotechnology Progress     Hybrid Journal   (Followers: 44)
Black Sea Journal of Engineering and Science     Open Access  
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Boundary Value Problems     Open Access   (Followers: 1)
Brazilian Journal of Science and Technology     Open Access   (Followers: 2)
Bulletin of Canadian Petroleum Geology     Full-text available via subscription   (Followers: 13)
Bulletin of Engineering Geology and the Environment     Hybrid Journal   (Followers: 15)
Bulletin of the Crimean Astrophysical Observatory     Hybrid Journal  
Cahiers Droit, Sciences & Technologies     Open Access   (Followers: 1)
Calphad     Hybrid Journal   (Followers: 2)
Canadian Geotechnical Journal     Hybrid Journal   (Followers: 30)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 50)
Carpathian Journal of Electronic and Computer Engineering     Open Access  
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 6)
Case Studies in Thermal Engineering     Open Access   (Followers: 8)
Catalysis Communications     Hybrid Journal   (Followers: 7)
Catalysis Letters     Hybrid Journal   (Followers: 3)
Catalysis Reviews: Science and Engineering     Hybrid Journal   (Followers: 9)
Catalysis Science and Technology     Hybrid Journal   (Followers: 13)
Catalysis Surveys from Asia     Hybrid Journal   (Followers: 4)
Catalysis Today     Hybrid Journal   (Followers: 8)
CEAS Space Journal     Hybrid Journal   (Followers: 6)
Cell Reports Physical Science     Open Access  
Cellular and Molecular Neurobiology     Hybrid Journal   (Followers: 2)
Central European Journal of Engineering     Hybrid Journal  
CFD Letters     Open Access   (Followers: 8)
Chaos : An Interdisciplinary Journal of Nonlinear Science     Hybrid Journal   (Followers: 3)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chaos, Solitons & Fractals : X     Open Access   (Followers: 1)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 3)
Chinese Journal of Engineering     Open Access   (Followers: 2)
Chinese Journal of Population, Resources and Environment     Open Access  
Chinese Science Bulletin     Open Access   (Followers: 1)
Ciencia e Ingenieria Neogranadina     Open Access  
Ciencia en su PC     Open Access   (Followers: 1)
Ciencia y Tecnología     Open Access  
Ciencias Holguin     Open Access   (Followers: 2)
CienciaUAT     Open Access   (Followers: 1)
Cientifica     Open Access  
CIRP Annals - Manufacturing Technology     Hybrid Journal   (Followers: 11)
CIRP Journal of Manufacturing Science and Technology     Hybrid Journal   (Followers: 14)
City, Culture and Society     Hybrid Journal   (Followers: 27)
Clay Minerals     Hybrid Journal   (Followers: 9)
Coal Science and Technology     Full-text available via subscription   (Followers: 4)
Coastal Engineering     Hybrid Journal   (Followers: 14)
Coastal Engineering Journal     Hybrid Journal   (Followers: 9)
Coastal Engineering Proceedings : Proceedings of the International Conference on Coastal Engineering     Open Access   (Followers: 2)
Coastal Management     Hybrid Journal   (Followers: 30)
Coatings     Open Access   (Followers: 4)
Cogent Engineering     Open Access   (Followers: 3)
Cognitive Computation     Hybrid Journal   (Followers: 3)
Color Research & Application     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 18)
Combustion, Explosion, and Shock Waves     Hybrid Journal   (Followers: 21)
Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering     Open Access  
Communications in Numerical Methods in Engineering     Hybrid Journal   (Followers: 2)
Components, Packaging and Manufacturing Technology, IEEE Transactions on     Hybrid Journal   (Followers: 28)
Composite Interfaces     Hybrid Journal   (Followers: 10)
Composite Structures     Hybrid Journal   (Followers: 335)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 279)
Composites Part B : Engineering     Hybrid Journal   (Followers: 312)
Composites Part C : Open Access     Open Access   (Followers: 3)
Composites Science and Technology     Hybrid Journal   (Followers: 247)
Comptes Rendus : Mécanique     Open Access   (Followers: 2)
Computation     Open Access   (Followers: 1)
Computational Geosciences     Hybrid Journal   (Followers: 20)
Computational Optimization and Applications     Hybrid Journal   (Followers: 11)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 6)
Computer Science and Engineering     Open Access   (Followers: 21)

        1 2 3 4 5 6 7 8 | Last

Similar Journals
Journal Cover
Automotive Innovation
Number of Followers: 1  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2096-4250 - ISSN (Online) 2522-8765
Published by Springer-Verlag Homepage  [2658 journals]
  • Simulator Coupled with Distributed Co-Simulation Protocol for Automated
           Driving Tests

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      Abstract: To meet the challenges in software testing for automated vehicles, such as increasing system complexity and an infinite number of operating scenarios, new simulation methods must be developed. Closed-loop simulations for automated driving (AD) require highly complex simulation models for multiple controlled vehicles with their perception systems as well as their surrounding context. For the realization of such models, different simulation domains must be coupled with co-simulation. However, widely supported model integration standards such as functional mock-up interface (FMI) lack native support for distributed platforms, which is a key feature for AD due to the computational intensity and platform exclusivity of certain models. The newer FMI companion standard distributed co-simulation protocol (DCP) introduces platform coupling but must still be used in conjunction with AD co-simulations. As part of an assessment framework for AD, this paper presents a DCP compliant implementation of an interoperable interface between a 3D environment and vehicle simulator and a co-simulation platform. A universal Python wrapper is implemented and connected to the simulator to allow its control as a DCP slave. A C-code-based interface enables the co-simulation platform to act as a DCP master and to realize cross-platform data exchange and time synchronization of the environment simulation with other integrated models. A model-in-the-loop use case is performed with the traffic simulator CARLA running on a Linux machine connected to the co-simulation master xMOD on a Windows computer via DCP. Several virtual vehicles are successfully controlled by cooperative adaptive cruise controllers executed outside of CARLA. The standard compliance of the implementation is verified by exemplary connection to prototypic DCP solutions from 3rd party vendors. This exemplary application demonstrates the benefits of DCP compliant tool coupling for AD simulation with increased tool interoperability, reuse potential, and performance.
      PubDate: 2021-10-16
       
  • Design, Modeling, and Characterization of a Tubular Linear Vibration
           Energy Harvester for Integrated Active Wheel System

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      Abstract: A major source of electric vehicle energy loss is the vibration energy dissipated by the shock absorbers under irregular road excitation, which is particularly severe when active wheel systems are employed because their greater unsprung mass leads to greater shocks and vibrations. Therefore, a tubular linear energy harvester (TLEH) with a large stroke and low electromagnetic force ripple is designed to convert this vibration energy into electricity. The proposed TLEH employs a slotted external mover with three-phase winding coils and an internal stator with PMs to increase the stroke, adopts a fractional slot-per-pole configuration to reduce its size and improve the winding factor, and realizes significantly reduced cogging force by optimizing the incremental length of the armature core. A finite element model of the TLEH is first verified against a theoretical model and then used to investigate the influences of various road excitation frequencies and amplitudes on the electromotive force (EMF) waveforms and generated power, the efficiency and damping force according to load condition, and the energy recovery and nonlinear electromagnetic force characteristics of the TLEH. A resistance controller is then designed to realize a self-damping electromagnetic suspension. The results indicate that the EMF and the generated power waveforms depend on the excitation frequency and amplitude, the efficiency increases and the damping coefficient decreases with the increasing load resistance.
      PubDate: 2021-10-12
       
  • VCANet: Vanishing-Point-Guided Context-Aware Network for Small Road Object
           Detection

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      Abstract: Advanced deep learning technology has made great progress in generic object detection of autonomous driving, yet it is still challenging to detect small road hazards in a long distance owing to lack of large-scale small-object datasets and dedicated methods. This work addresses the challenge from two aspects. Firstly, a self-collected long-distance road object dataset (TJ-LDRO) is introduced, which consists of 109,337 images and is the largest dataset so far for the small road object detection research. Secondly, a vanishing-point-guided context-aware network (VCANet) is proposed, which utilizes the vanishing point prediction block and the context-aware center detection block to obtain semantic information. The multi-scale feature fusion pipeline and the upsampling block in VCANet are introduced to enhance the region of interest (ROI) feature. The experimental results with TJ-LDRO dataset show that the proposed method achieves better performance than the representative generic object detection methods. This work fills a critical capability gap in small road hazards detection for high-speed autonomous vehicles.
      PubDate: 2021-09-13
       
  • Design of the Airbag Inflation System Applicable to Conventional and
           Autonomous Vehicles

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      Abstract: The emergency transformation of various aspects of life and business these days requires prompt evaluation of autonomous vehicles. One of the primary reassessments deals with the applicability of the vehicle passive safety system to the protection of arbitrarily positioned passengers. To mitigate possible risks caused by the simultaneous deployment of several big airbags, a new principle of their operation is required. Herein, the aspirated inflator for a driver airbag is developed that can provide 50L-airbag inflation within 30–40 ms. As a result, about 3/4 of the air is to be entrained into an airbag from the vehicle compartment. The process is initiated by a supersonic pulse jet (1/3 air volume) generated pyrotechnically. Then the Prandtl–Meyer problem formulation enables guiding linear and angular dimensions of the essential parts of the device. Accordingly, a family of experimental models of varied geometry is fabricated and tested to determine their operational effectiveness in a range of motive pressure within ~ 3–7 MPa. Experiments are performed on a specially designed facility equipped with compressed-air tanks and a high-speed valve to mimic the inflator operation with the pyrotechnic gas generator. The aspirated inflator operability is characterized using multivariate measurements of pressure fields, high-speed video-recording of the airbag inflation process, and evaluation of aspiration (entrainment) ratio. The average volume aspiration ratio measured at 300 K is found to reach 2.8 and it’s expected to almost double at 1200 K.
      PubDate: 2021-09-13
       
  • Preface for Feature Topic on Intelligent Safety for CAVs

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      PubDate: 2021-08-01
       
  • Human Performance in Critical Scenarios as a Benchmark for Highly
           Automated Vehicles

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      Abstract: Before highly automated vehicles (HAVs) become part of everyday traffic, their safety has to be proven. The use of human performance as a benchmark represents a promising approach, but appropriate methods to quantify and compare human and HAV performance are rare. By adapting the method of constant stimuli, a scenario-based approach to quantify the limit of (human) performance is developed. The method is applied to a driving simulator study, in which participants are repeatedly confronted with a cut-in manoeuvre on a highway. By systematically manipulating the criticality of the manoeuvre in terms of time to collision, humans’ collision avoidance performance is measured. The limit of human performance is then identified by means of logistic regression. The calculated regression curve and its inflection point can be used for direct comparison of human and HAV performance. Accordingly, the presented approach represents one means by which HAVs’ safety performance could be proven.
      PubDate: 2021-08-01
       
  • A Systematic Risk Assessment Framework of Automotive Cybersecurity

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      Abstract: The increasingly intelligent and connected vehicles have brought many unprecedented automotive cybersecurity threats, which may cause privacy breaches, personal injuries, and even national security issues. Before providing effective security solutions, a comprehensive risk assessment of the automotive cybersecurity must be carried out. A systematic cybersecurity risk assessment framework for automobiles is proposed in this study. It consists of an assessment process and systematic assessment methods considering the changes of threat environment, evaluation target, and available information in vehicle lifecycle. In the process of risk identification and risk analysis, the impact level and attack feasibility level are assessed based on the STRIDE model and attack tree method. An automotive cybersecurity risk matrix using a global rating algorithm is then constructed to create a quantitative risk metric. Finally, the applicability and feasibility of the proposed risk assessment framework are demonstrated through a use case, and the results prove that the proposed framework is effective. The proposed assessment framework helps to systematically derive automotive cybersecurity requirements.
      PubDate: 2021-08-01
       
  • Vehicle Travel Destination Prediction Method Based on Multi-source Data

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      Abstract: Research on vehicle travel destinations mostly only consider vehicle trajectory data and ignore the influence of other multi-source data, such as weather, time, and points of interest (POI). This study proposes a destination prediction method based on multi-source data, and a multi-input neural network model is established. In terms of the coding of vehicle trajectory data, a GeoHash to vector (Geo2vec) model is proposed to realize the characterization of the trajectory. As for the coding of temporal features, a cyclic coding model is proposed based on trigonometric functions. For the coding of POI, an origin–destination POI matrix (OD-POI) model is proposed based on the state transition probability. Experimental results show that in terms of the average distance and root-mean-square distance deviations, Geo2vec reveals reductions of 4.51% and 5.63% compared to word to vector (Word2vec), and cyclic encoding shows reductions of 6.35% and 6.67% compared to label encoding; further, the method of OD-POI state transition probability is reduced by 5.85% and 6.4%, and the model based on multi-source data is 17.29% and 17.65% lower than the model based on trajectory data only. Finally, the cyclic encoding is reduced by 48.60% in the data dimension compared to one-hot encoding. Accurate destination prediction will help improve the efficiency of automotive human–computer interaction
      PubDate: 2021-08-01
       
  • Path-Following Control of Autonomous Vehicles Considering Coupling Effects
           and Multi-source System Uncertainties

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      Abstract: Path-following control is one of the key technologies of autonomous vehicles, but the complex coupling effects and system uncertainties of vehicles can degrade their control performance. Accordingly, this study proposes targeted methods to solve different types of coupling in vehicle dynamics. First, the types of coupling are figured out and different handling strategies are proposed for each type, among which the coupling caused by steering angle, unsaturated tire forces, and load transfer can be treated as uncertainties in a unified form, such that the coupling effects can be treated in a decoupling way. Then, robust control methods for both lateral and longitudinal dynamics are proposed to deal with the uncertainties in dynamic and physical parameters. In lateral control, a robust feedback–feedforward scheme is utilized in lateral control to deal with such uncertainties. In longitudinal control, a radial basis function neural network-based adaptive sliding mode controller is introduced to deal with uncertainties and disturbances. In addition, the tire saturation coupling that cannot be handled by controllers is treated by a proposed speed profile. Simulation results based on the CarSim–Simulink joint platform evaluate the effectiveness and robustness of the proposed control method. The results show that compared with a well-designed robust controller, the velocity tracking performance, lateral tracking performance, and heading tracking performance improve by 55.68%, 34.26%, and 52.41%, respectively, in the double-lane change maneuver, and increase by 87.79%, 30.18%, and 9.68%, respectively, in the ramp maneuver.
      PubDate: 2021-08-01
       
  • Cyber-Attack Detection for Autonomous Driving Using Vehicle Dynamic State
           Estimation

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      Abstract: As intelligent vehicles become increasingly computerized and networked, they gain more autonomous capabilities. However, they are also becoming more exposed to cyber-threats which are likely to be a more prominent concern. This paper proposes a cyber-attack detection method for autonomous vehicles based on secure estimation of vehicle states, with an example application under attacks in the vehicle localization system. To investigate the effects of vehicle model and estimator on the attack detection performance, different nonlinear vehicle dynamic models and estimation approaches are employed. The deviation between the measurement from the onboard sensors and the state estimation is monitored in real time. With the designed vehicle state estimator and preset threshold, the cyber-attack detection algorithm is further developed for autonomous vehicles, whose performance is tested in simulations where the vehicle localization system is assumed to be compromised during a double lane change maneuver. The test results demonstrate the feasibility and effectiveness of the proposed cyber-attack algorithm. In addition, the results illustrate the impacts of vehicle nonlinear characteristics on the cyber-attack detection performance. Beyond this, the effects of different vehicle models on the attack detection performance, as well as the selection of suitable filtering approaches for the attack detection, are also discussed.
      PubDate: 2021-08-01
       
  • End-to-End Autonomous Driving Through Dueling Double Deep Q-Network

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      Abstract: Recent years have seen the rapid development of autonomous driving systems, which are typically designed in a hierarchical architecture or an end-to-end architecture. The hierarchical architecture is always complicated and hard to design, while the end-to-end architecture is more promising due to its simple structure. This paper puts forward an end-to-end autonomous driving method through a deep reinforcement learning algorithm Dueling Double Deep Q-Network, making it possible for the vehicle to learn end-to-end driving by itself. This paper firstly proposes an architecture for the end-to-end lane-keeping task. Unlike the traditional image-only state space, the presented state space is composed of both camera images and vehicle motion information. Then corresponding dueling neural network structure is introduced, which reduces the variance and improves sampling efficiency. Thirdly, the proposed method is applied to The Open Racing Car Simulator (TORCS) to demonstrate its great performance, where it surpasses human drivers. Finally, the saliency map of the neural network is visualized, which indicates the trained network drives by observing the lane lines. A video for the presented work is available online, https://youtu.be/76ciJmIHMD8 or https://v.youku.com/v_show/id_XNDM4ODc0MTM4NA==.html.
      PubDate: 2021-08-01
       
  • Uncertainty Evaluation of Object Detection Algorithms for Autonomous
           Vehicles

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      Abstract: The safety of the intended functionality (SOTIF) has become one of the hottest topics in the field of autonomous driving. However, no testing and evaluating system for SOTIF performance has been proposed yet. Therefore, this paper proposes a framework based on the advanced You Only Look Once (YOLO) algorithm and the mean Average Precision (mAP) method to evaluate the object detection performance of the camera under SOTIF-related scenarios. First, a dataset is established, which contains road images with extreme weather and adverse lighting conditions. Second, the Monte Carlo dropout (MCD) method is used to analyze the uncertainty of the algorithm and draw the uncertainty region of the predicted bounding box. Then, the confidence of the algorithm is calibrated based on uncertainty results so that the average confidence after calibration can better reflect the real accuracy. The uncertainty results and the calibrated confidence are proposed to be used for online risk identification. Finally, the confusion matrix is extended according to the several possible mistakes that the object detection algorithm may make, and then the mAP is calculated as an index for offline evaluation and comparison. This paper offers suggestions to apply the MCD method to complex object detection algorithms and to find the relationship between the uncertainty and the confidence of the algorithm. The experimental results verified by specific SOTIF scenarios proof the feasibility and effectiveness of the proposed uncertainty acquisition approach for object detection algorithm, which provides potential practical implementation chance to address perceptual related SOTIF risk for autonomous vehicles.
      PubDate: 2021-08-01
       
  • A Computer Graphics-Based Framework for 3D Pose Estimation of Pedestrians

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      Abstract: In pedestrian-to-vehicle collision accidents, adapting safety measures ahead of time based on actual pose of pedestrians is one of the core objectives for integrated safety. It can significantly enhance the performance of passive safety system when active safety maneuvers fail to avoid accidents. This study proposes a deep learning model to estimate 3D pose of pedestrians from images. Since conventional pedestrian image datasets do not have available pose features to work with, a computer graphics-based (CG) framework is established to train the system with synthetic images. Biofidelic 3D meshes of standing males are first transformed into several walking poses, and then rendered as images from multiple view angles. Subsequently, a matrix of 50 anthropometries, 10 gaits and 12 views is built, in total of 6000 images. A two-branch convolutional neural network (CNN) was trained on the synthetic dataset. The model can simultaneously predict 16 joint landmarks and 14 joint angles of pedestrian for each image with high accuracy. Mean errors of the predictions are 0.54 pixels and − 0.06°, respectively. Any specific pose can then be completely reconstructed from the outputs. Overall, the current study has established a CG-based pipeline to generate photorealistic images with desired features for the training; it demonstrates the feasibility of leveraging CNN to estimate the pose of a walking pedestrian from synthesized images. The proposed framework provides a starting point for vehicles to infer pedestrian poses and then adapt protection measures accordingly for imminent impact to minimize pedestrian injuries.
      PubDate: 2021-08-01
       
  • A Novel Fault Detection, Identification and Prediction Approach for
           Autonomous Vehicle Controllers Using SVM

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      Abstract: Faults that develop in vehicle sensors have the potential to propagate unchecked throughout control systems if undetected. Automatic fault diagnosis and health monitoring algorithms will become necessary as automotive applications become more autonomous. The current fault diagnosis systems are not effective for complex systems such as autonomous cars where the case of simultaneous faults in different sensors is highly possible. Therefore, this paper proposes a novel fault detection, isolation and identification architecture for multi-fault in multi-sensor systems with an efficient computational burden for real-time implementation. Support Vector Machine techniques are used to detect and identify faults in sensors for autonomous vehicle control systems. In addition, to identify degrading performance in a sensor and predict the time at which a fault will occur, a novel predictive algorithm is proposed. The effectiveness and accuracy of the architecture in detecting and identifying multiple faults as well as the accuracy of the proposed predictive fault detection algorithm are verified through a MATLAB/IPG CarMaker co-simulation platform. The results present detection and identification accuracies of 94.94% and 97.01%, respectively, as well as a prediction accuracy of 75.35%.
      PubDate: 2021-08-01
       
  • Preface for Special Section on Fuel Cell Technology

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      PubDate: 2021-05-01
       
  • Experimental Investigation on Local Behaviors of PEMFC with Segmented Cell

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      Abstract: When designing a cell stack and developing an operational strategy for proton exchange membrane fuel cell, it is critical to characterize the local current, water and heat. To measure distributions of current density, relative humidity and temperature for both anode and cathode simultaneously along the straight parallel flow channels, this paper uses a segmented tool based on the multilayered printed circuit board flow field plates with embedded sensors. In this study, two kinds of experimental operations of fuel cell reactants are carried out for comparison: the co-flow operation with identical gas flow direction of hydrogen and air and the counter-flow operation with opposite gas flow directions. The detected relative humidity (RH) distributions of both anode and cathode indicate that the asymmetry of RH distribution at two sides of the membrane in counter-flow operation is better at holding water inside the fuel cell compared with the co-flow operation. The in situ measured performance distributions show that segments around the middle of the fuel cell contribute the highest current in counter-flow operation, while for co-flow operation, the current peak locates near the outlet of reactants.
      PubDate: 2021-05-01
       
  • Critical Speeds of Electric Vehicles for Regenerative Braking

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      Abstract: Efficient regenerative braking of electric vehicles (EVs) can enhance the efficiency of an energy storage system (ESS) and reduce the system cost. To ensure swift braking energy recovery, it is paramount to know the upper limit of the regenerative energy during braking. Therefore, this paper, based on 14 typical urban driving cycles, proposes the concept and principle of confidence interval of “probability event” and “likelihood energy” proportion of braking. The critical speeds of EVs for braking energy recovery are defined and studied through case studies. First, high-probability critical braking speed and high-energy critical braking speed are obtained, compared, and analyzed, according to statistical analysis and calculations of the braking randomness and likelihood energy in the urban driving cycles of EVs. Subsequently, a new optimized ESS concept is proposed under the frame of a battery/ultra-capacitor (UC) hybrid energy storage system (HESS) combined with two critical speeds. The battery/UC HESS with 9 UCs can achieve better regenerative braking performances and discharging performances, which indicates that a minimal amount of UCs can be used as auxiliary power source to optimize the ESS. After that, the efficiency regenerative braking model, including the longitudinal dynamics, motor, drivetrain, tire, and wheel slip models, is established. Finally, parameters optimization and performance verification of the optimized HESS are implemented and analyzed using a specific EV. Research results emphasize the significance of the critical speeds of EVs for regenerative braking.
      PubDate: 2021-05-01
       
  • Experimental Investigation of the Rail Pressure Fluctuations Correlated
           with Fuel Properties and Injection Settings

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      Abstract: Injection-induced rail pressure fluctuations are proven to cause nonuniform spray development. These fluctuations are also responsible for generating lower injection pressures, to the detriment of jet penetration length and break-up timing. Despite the vast literature dealing with such issues, several aspects of rail pressure fluctuations remain unclear. Additionally, the need for compliance with the emission legislation has shed light on the potential of alternative fuels, which represent a pathway for sustainable mobility. This scenario has motivated the present study dealing with the assessment of the time history of rail pressure correlated with fuel properties. Tests have been performed using a last-generation common rail injection equipment under various injection settings, employing diesel and 2-methylfuran-diesel blend. This paper describes the research activity and aims to provide new insights into the correlation of rail pressure fluctuations with fuel properties.
      PubDate: 2021-05-01
       
  • Cathode Design for Proton Exchange Membrane Fuel Cells in Automotive
           Applications

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      Abstract: An advanced cathode design can improve the power performance and durability of proton exchange membrane fuel cells (PEMFCs), thus reducing the stack cost of fuel cell vehicles (FCVs). Recent studies on highly active Pt alloy catalysts, short-side-chain polyfluorinated sulfonic acid (PFSA) ionomer and 3D-ordered electrodes have imparted PEMFCs with boosted power density. To achieve the compacted stack target of 6 kW/L or above for the wide commercialization of FCVs, developing available cathodes for high-power-density operation is critical for the PEMFC. However, current developments still remain extremely challenging with respect to highly active and stable catalysts in practical operation, controlled distribution of ionomer on the catalyst surface for reducing catalyst poisoning and oxygen penetration losses and 3D (three-dimensional)-ordered catalyst layers with low Knudsen diffusion losses of oxygen molecular. This review paper focuses on impacts of the cathode development on automotive fuel cell systems and concludes design directions to provide the greatest benefit.
      PubDate: 2021-05-01
       
  • Proton Exchange Membrane (PEM) Fuel Cells with Platinum Group Metal
           (PGM)-Free Cathode

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      Abstract: Proton exchange membrane (PEM) fuel cells have gained increasing interest from academia and industry, due to its remarkable advantages including high efficiency, high energy density, high power density, and fast refueling, also because of the urgent demand for clean and renewable energy. One of the biggest challenges for PEM fuel cell technology is the high cost, attributed to the use of precious platinum group metals (PGM), e.g., Pt, particularly at cathodes where sluggish oxygen reduction reaction takes place. Two primary ways have been paved to address this cost challenge: one named low-loading PGM-based catalysts and another one is non-precious metal-based or PGM-free catalysts. Particularly for the PGM-free catalysts, tremendous efforts have been made to improve the performance and durability—milestones have been achieved in the corresponding PEM fuel cells. Even though the current status is still far from meeting the expectations. More efforts are thus required to further research and develop the desired PGM-free catalysts for cathodes in PEM fuel cells. Herein, this paper discusses the most recent progress of PGM-free catalysts and their applications in the practical membrane electrolyte assembly and PEM fuel cells. The most promising directions for future research and development are pointed out in terms of enhancing the intrinsic activity, reducing the degradation, as well as the study at the level of fuel cell stacks.
      PubDate: 2021-05-01
       
 
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