Browse Topic: Sensors and actuators

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Prognostic Techniques in Automated Driving System (ADS) Vehicle Safety2025-01-8094To be published on 04/01/2025
The recent advancements in fields such as sensors, AI, and IoT are majorly impacting the automotive industry. Automated Driving Systems (ADS) are developing rapidly, meaning that SAE level 3 and above vehicles are quickly becoming a reality. As a result, maintenance of such systems becomes essential to ensure their safe and efficient navigation. Prognostic techniques in particular are crucial to predict the future health state of the system and its components. Many methods have been developed and are being used for prognostic of conventional vehicles as well as other industries. However, ADS is a new technology, and several of these approaches are still being developed and adapted to it. In this paper, we first present a review of the most used prognostic techniques across different safety-critical domains such as aerospace, power, and manufacturing. Then, we summarize the main challenges that must be faced to successfully develop novel approaches for ADS prognostic and provide a set
Merola, Francesco, Hanif, Athar, Lami, Giuseppe, Ahmed, Qadeer, Monohon, Mark
Technical Paper
Quantifying the uncertainty in bicycle-computer speed measurements2025-01-8701To be published on 04/01/2025
The goal of this study is to quantify the uncertainty in bicycle computer measurements of speed. We acquired 100+ hours of data at 1-second intervals simultaneously from three Garmin Edge 530 computers mounted to the same handlebars during road cycling in rural and urban environments. Each computer recorded speed data using a different method: One unit was paired to a Garmin GSC 10 speed-and-cadence sensor (wheel rotation based), a second unit was paired to Garmin Speed Sensor 2 and Cadence Sensor 2 (accelerometer based), and a third unit was not paired to any remote sensors and relied on the device’s GPS position to calculate speed (GPS based). Based on these data, we generated probability distributions that quantify the uncertainty in the accelerometer based and GPS based speed measurements. This study provides foundational information regarding the appropriate methods to quantify the uncertainty in bicycle-computer speed data and to probabilistically interpret these data for
Booth, Gabrielle R., Siegmund, Gunter P.
Technical Paper
Vehicle Motion Management - A model predictive control approach to realize holistic redundancy to enable actuator fail operational autonomous driving2025-01-8812To be published on 04/01/2025
Since the series introduction of ESC (1995), the number of vehicle dynamic control functions and ADAS has increased continuously. Today, there are many functions that control the vehicle motion in cooperation, so that the vehicle motion is often implemented suboptimally. Current megatrends (electrification, AD, new SW architectures) and new key technologies (X-by-Wire) enable the development of Integrated Chassis Control (ICC), which controls all motion-relevant components to optimize vehicle motion. This function, which is currently being developed by many OEMs, not only improves the driving safety and comfort but is also furthermore essential for AD. Vehicle Motion Management (VMM), the ICC solution by IAV GmbH, uses Model Predictive Control (MPC) to predict and optimize vehicle motion in real time. The VMM architecture already developed (Observer, Supervisor, MPC, Coordination) can be adapted to the powertrain topology. This article reports on the results of a simulative potential
Wielitzka, Mark, Ahrenhold, Tim, Vocht, Moritz, Rawitzer, Jonas, Schrader, Jonas
Technical Paper
A Control Strategy for Height Adjustment in Closed-Loop Air Spring Suspension System2025-01-8798To be published on 04/01/2025
This study investigates the closed-loop air spring suspension system by developing comprehensive models for both the air spring and its associated pipeline. To address issues such as "overcharging," "over-discharging," and significant overshoot during vehicle height adjustment, a threshold control strategy was developed. This strategy manages the trigger conditions for height adjustment to mitigate overshoot and precision problems. Experiments demonstrated that while this control strategy reduced overshoot and improved accuracy, it introduced the risk of excessive control due to varying threshold settings across different modules. To resolve this issue, a fuzzy PID controller was designed, utilizing fuzzy rules to adapt PID parameters in real-time, thereby enhancing height adjustment control. Testing confirmed that the fuzzy PID controller effectively resolved the issues associated with threshold control and also improved the rate of height adjustment. Furthermore, to prevent excessive
Zheng, Guoqing, Yin, Zhihong, Chen, Shiwen, Shangguan, Wen-Bin
Technical Paper
A Review of Off-Road Datasets, Sensor Technologies and Terrain Traversability Analysis2025-01-8339To be published on 04/01/2025
Autonomous ground navigation research and application has seen development and improvement in urban and structured environments with an increase in publicly available published datasets. However, autonomous ground navigating on off-road and unstructured conditions is still challenging due to the limited datasets, difficulties caused by environmental conditions, diverse terrain types and sensor limitations which affect vehicle perception. The recently available published public offroad datasets are presented here, integrated with the sensor technologies used and terrain traversability analysis and techniques. This study identifies the gaps in the existing datasets and examines the limitations of sensing technologies used and the challenges of terrain traversability analysis. In doing so, we suggest recommendations for creating more comprehensive off-road datasets incorporating advanced sensor technologies and refined terrain traversability analysis methods. The review provides
Musau, Hannah, Ruganuza, Denis, Indah, Debbie, Mukwaya, Arthur, Gyimah, Nana, Bhosale, Mayuresh, Patil, Ashish, Gupta, Prakhar, Mwakalonge, Judith, Jia, Yunyi, Grabowsky, David, Mikulski, Dariusz, Siuhi, Saidi, Hong, Jae
Technical Paper
A Proactive System to Anticipate and Store the Damage Information on a Parked Car using Machine Learning Algorithm2025-01-8211To be published on 04/01/2025
Vehicle ADAS Systems majorly comprises of two functions: Driving and Parking. The most common form of damage to the vehicle which goes unnoticed with unidentified cause are parking damages. A vehicle once parked at a certain location may get damaged without knowledge of the user. In this work developed a solution that not only pre-warns the driver but also prepares the vehicle beforehand if it suspects a damage may occur. This eliminates the latency between damage and information capture, detects small damages such as scratches, classifies the type of damage and also informs the user beforehand. This is solution is different from our competitors as the existing solutions informs the user about the scratches/damages, but these solutions are expensive, have high response time, and the damage information is captured after the damage has occurred. The solution consists of the following check blocks: Precondition, Sensor Control and Action Module. The Precondition Module observes the
Debnath, Sarnab, PATIL, Prasad, Belur Subramanya, Sheshagiri, Govinda, Shiva Prasad
Technical Paper
Meteorolgical Aspects of the Operational Design Domain -- Enhancing Road and Rail Safety and Efficiency through Integrated Wind, Weather, and Motion Sensing Technology2025-01-8100To be published on 04/01/2025
In recent years, integrated sensor systems have significantly advanced environmental monitoring, providing essential insights for addressing various environmental challenges. This paper introduces a novel wind, weather, and motion sensor, designed primarily for automotive environments but also applicable to rail systems. The paper explores how these sensors enhance the safety and efficiency of vehicles by detecting critical environmental parameters. Key concepts such as the Operational Design Domain (ODD) and Operational Domain (OD) are discussed, emphasizing their importance in the deployment of connected, automated, and autonomous vehicles. The distinction between ODD and OD is illustrated using real-world examples, highlighting the necessity for advanced detection and response capabilities in complex driving scenarios. Furthermore, the paper delves into the significance of road-related atmospheric conditions like temperature, humidity, pressure, and wind. Current state-of-the-art
Feichtinger, Christoph Simon
Technical Paper
Different methods-based Curvature estimation and its effect on the Lane centering performance2025-01-8055To be published on 04/01/2025
ADAS (Advanced Driver Assistance Systems) lateral feature performance heavily depends on inputs from the surroundings as well as vehicle state information/signals. One critical piece of vehicle state information is curvature, which significantly impacts performance. Vehicle curvature is often used as an input for lateral trajectory generation and is also a component of the lateral motion controller. However, obtaining vehicle curvature information is not straightforward, as there is rarely a sensor that directly measures vehicle curvature. Instead, various vehicle signals and information are used to calculate curvature, sometimes employing advanced estimation methods. In this paper, we investigate the impact on lateral feature performance when vehicle curvature is estimated from different source signals. We examine the issues and benefits associated with different techniques for obtaining ego vehicle curvature. Additionally, we present a method to address these issues and discuss how
Awathe, Arpit, Varunjikar, Tejas, Jain, Arihant
Technical Paper
Workload Estimation for a Military Ground Vehicle Crew using Supervised Machine Learning of FACS Action Unit Intensity Data2025-01-8340To be published on 04/01/2025
The proliferation of intelligent technologies in the future battlefield necessitates an exploration of crew workload balancing strategies for human-machine integrated formations. Many current techniques to measure cognitive workload, through qualitative surveys or wearable sensors, are too brittle for the harsh, austere operational environments found in military settings. Non-invasive workload estimation techniques, such as those that analyze physiological effects from video feeds of the crew, present a way forward for workload-aware Soldier-machine interfaces that could trigger events – such as task reallocation – if limits on crew or individual workload are exceeded. One such technique that is being explored is the use of facial expression analysis for workload estimation. We present the performance results of regression and classification models developed from supervised machine learning algorithms that predict pNN50, a common heart rate variability metric used as a physiological
Mikulski, Christopher, Riegner, Kayla
Technical Paper
Supervisory Control System Development for a Toyota Mirai FCEV2025-01-8586To be published on 04/01/2025
The performance of a second-generation Toyota Mirai fuel cell was characterized as part of the SwRI internal research program. This data was used to develop a supervisory controller scheme designed to balance the plant for the fuel cell system during steady-state and transient vehicle conditions. This was accomplished using a Supervisory Integrated Controller (SIC) implemented on a Real-time Power Electron- ics Control System (RPECS) with a Simulink-based control algorithm. The actuators of interest are the three hydrogen injectors at anode inlet, air compressor and three air side valves on at the cathode inlet. The FC power measurement and pressure sensor readings at the anode and cathode were utilized as real-time feedback for the controller operation. The aim of the controller was to achieve and maintain the power target set by the hybrid powertrain ECU present on the vehicle, which is responsible for balancing power on the fuel cell and battery over the high-voltage bus. These
Chundru, Venkata Rajesh, Kubesh, Matthew, Legala, Adithya
Technical Paper
Machine Learning-Based Digital Twin for Optimizing Automotive Components2025-01-8206To be published on 04/01/2025
This paper presents a Digital Twin approach based on Machine Learning (ML), aimed at creating software-based sensors to reduce the auxiliary devices of the vehicle and enabling predictive maintenance, thus reducing carbon footprint. The solution is applied to the Electric Lubrication Oil Pump (ELOP), a crucial component within a vehicle's powertrain system. The proposed ELOP Digital Twin integrates ML-based sensors to estimate critical parameters such as temperature, pressure and flow rate, reducing the reliance on physical sensors and associated hardware. This estimation approach minimizes manufacturing complexity and cost, enhancing energy efficiency during both production and operation. Furthermore, the digital twin facilitates predictive maintenance by continuously monitoring the component's performance, enabling early detection of potential failures and optimizing maintenance schedules. This leads to lower energy consumption and reduced emissions throughout the component's
Khan, Jalal, D'Alessandro, Stefano, Tramaglia, Federico, Fauda, Alessandro
Technical Paper
INTEGRATED BODY STRUCTURE TO ACCOMMODATE MANUAL AND POWER DOOR SUNSHADE VARIANTS IN A VEHICLE2025-01-8616To be published on 04/01/2025
Door Sunshade in a vehicle has proven to be very comfortable and luxurious feature to the customers. Luxury vehicles provide Power Sunshade which is electrically operated with the activation of a switch, whereas cost conscious vehicles provide manual sunshade which requires manual coiling and uncoiling. This study is to develop a Door Panel structure that can accommodate both the Manual Sunshade and Power Sunshade, thereby serving both cost conscious as well as luxury seeking customers. Manual Sunshade consists only of cassette, Pull Bar, Spindle Mechanism and Hooks whereas the power sunshade consists of Cassette, Pull Bar, Spindle Mechanism, Flap mechanism, Bowden Cable Mechanism, Actuator and Motor. Due to this difference in Package, it becomes difficult to accommodate both Variants of Sunshade into the same body system. However, this study helps in developing a common body structure by ways of effective Packaging, Modifying the cable and Actuator Mechanism and critical packaging of
S M, Rahul, d, ANANTHA, Kakani, Phani Kumar
Technical Paper
Identifying Negative Driver States that Share Commonalities for Interventions2025-01-8676To be published on 04/01/2025
Advancements in sensor technologies have led to increased interest in detecting and diagnosing "driver states"-collections of internal driver factors generally associated with negative driving performance, such as alcohol intoxication, cognitive load, stress, and fatigue. This is accomplished using imperfect behavioral and physiological indicators that are associated with those states. An example is the use of elevated heart rate variability, detected by a steering wheel sensor, as an indicator of frustration. Advances in sensor technologies, coupled with improvements in machine learning, have led to an increase in this research. However, a limitation is that it often excludes naturalistic driving environments, which may have conditions that affect detection. For example, reductions in visual scanning are often associated with cognitive load (e.g., Angell et al., 2015); however, these reductions can also be related to novice driver inexperience (e.g., Stahl et al., 2019) and alcohol
Seaman, Sean, Zhong, Peihan, Angell, Linda, Domeyer, Joshua, Lenneman, John
Technical Paper
Concept of an electromechanical brake-by-wire system for battery-electric vehicles2025-01-8804To be published on 04/01/2025
Brake-by-wire systems have received more and more attention in the recent years, but a closer look on the available systems shows, that they have not reached full by-wire level yet. Most systems are still using hydraulic connections between main cylinder and the brake calipers on at least one axle to ensure functional safety. Mostly, this is the front axle, since the front brakes have to convert more kinetic energy during braking manoeuvers due to the dynamic wheel load shift. Electromechanical actuators are currently used for rear brake systems in hybrid brake-by-wire applications solely, since a loss of the front brake calipers can lead to severe conditions and control loss of the vehicle during braking. Further, the higher mass of battery-electric vehicles (BEVs) leads to much higher braking forces on both axles, so the electromechanical calipers on the market are no longer suitable. This article presents a concept for a brake-by-wire system for a battery electric vehicle, which
Heydrich, Marius, Lenz, Matthias, Ivanov, Valentin, Stoev, Julian, Lecoutere, Johan
Technical Paper
Decentralized perception system with multiple viewpoints2025-01-8097To be published on 04/01/2025
Vehicle-to-Infrastructure (V2I) cooperation has emerged as a fundamental technology to overcome the limitations of the individual ego-vehicle perception. Onboard perception is limited by the lack of information for understanding the environment, the lack of anticipation, the drop of performance due to occlusions and the physical limitations of embedded sensors. V2I perception in a cooperative manner improves the ego-vehicle perception range by receiving information from the infrastructure that has another point of view, mounted with sensors, such as camera and LiDAR. This technical paper presents a perception pipeline developed for the infrastructure, based on images with multiple viewpoints. It is designed to be scalable and has five main components: the image acquisition for the modification of camera settings and to get the pixel data, the object detection for fast and accurate detection of four wheels, two wheels and pedestrians, the data fusion module for robust fusion of the 2D
Picard, Quentin, Fadili, Maryem, Morice, Malo, Pechberti PhD, Steve
Technical Paper
FIT File Processing for Accident Reconstruction2025-01-8696To be published on 04/01/2025
It is becoming increasingly common for bicyclists to record their rides using cycling computers and watches, the majority of which save the data they collect using the Flexible and Interoperable Data Transfer (.FIT) Protocol. As the contents of .FIT files are not readily accessible to users, the purpose of this paper is to demonstrate the differences induced by several common methods of analyzing .FIT files. We used a Garmin Edge 840 bicycle computer with a wireless wheel speed sensor to record ride data at both 1 Hz frequency and using the computer’s Smart Recording setting. The.FIT files were downloaded directly from the computer, uploaded to the test platforms, and then exported to .GPX, and/or .CSV formats: the platforms tested were Strava, RideWithGPS, Garmin Connect, and GoldenCheetah. Those same .FIT files were also converted directly to .CSV using the Garmin FIT Software Developer Kit (SDK) FitCSVTool utility, written to .KML files using a custom MATLAB script, and compared to
Sweet, David, Bretting, Gerald
Technical Paper
Testing Complex Circuits with Radio-frequency Reflectometry2025-01-8251To be published on 04/01/2025
Driving automation systems rely heavily on sophisticated electronics to function effectively, and economic pressure poses new challenges in manufacturing. Tightly integrated sensors, processors, and communication modules monitor and control the vehicle's operation at any time. Size, weight, power, and cost constraints put pressure on manufactures to reduce stack electronics, miniaturize boards, and innovate over the traditional sequential assemble/test cycle. Consequently, designers and manufacturers reduce access to boards, remove test points, co-locate RF with other components, and break the sequential SMT line. Radiofrequency (RF) reflectometry is a mature and reliable technology essential for characterizing materials, components, and analog circuits. It provides precise insights into electromagnetic properties like impedance and permittivity, crucial for optimizing RF and microwave designs. Widely used in fields from material science to quantum computing, RF reflectometry is key to
Fischmeister, Sebastian, Moreno, Carlos
Technical Paper
Trajectory Tracking Fault-tolerant Control for Distributed Drive Electric Vehicles Considering Steering Actuator Faults2025-01-8299To be published on 04/01/2025
Trajectory tracking control is a key component of vehicle autonomous driving technology. Compared with traditional vehicles, Distributed Driven Electric Vehicle (DDEV) is an ideal vehicle for trajectory tracking control because of its high space utilization, redundant control freedom and fast system response. However, the chassis execution system of DDEV has a relatively large number of sensors, which significantly increases its probability of failure. In this paper, we propose a trajectory tracking fault-tolerant control method for DDEV considering steering actuator faults. Firstly, we establish the dynamic model of the steering actuator and the trajectory tracking model of DDEV. The model is linearized and discretized by using Taylor series expansion and forward Euler method. Next, considering multi-objective constraints such as motion comfort, actuator saturation and road adhesion boundary, the trajectory tracking control strategy of DDEV is designed by using model predictive
Chen, Zhicheng, Teng, Yuhan
Technical Paper
Parameter Virtual Calibration Method for Vehicle Path Tracking Controller Based on the Deep Reinforcement Learning2025-01-8311To be published on 04/01/2025
Path tracking control, which is one of the most important foundations of autonomous driving, could help the vehicle to precisely and smoothly follow the preset path by actively adjusting the front wheel steering angle. Although there are a number of advanced control methods with simple structure and reliable robustness that could assist vehicles achieving path tracking, these controllers have many parameters to be calibrated, and there is a lack of guidance documents to help non-professional test site engineers quickly master calibration methods. Therefore, this paper proposes a parameter virtual calibration method based on the deep reinforcement learning, which provides an effective solution for parameter calibration of vehicle path tracking controller. Firstly, the vehicle trajectory tracking model is established through the kinematic relationship between the vehicle and the target path, combined with the Taylor series expansion linearization method. Next, a vehicle path tracking
Zhao, Jian, Guo, Chenghao, Zhao, HuiChao, Zhao, Yongqiang, Yu, Zhen, Zhu, Bing, Chen, Zhicheng
Technical Paper
Discrepancies Between Metadata and Actual Camera Field of View: A Photogrammetric Approach2025-01-8686To be published on 04/01/2025
Camera matching photogrammetry is widely used in the field of accident reconstruction for mapping accident scenes, modeling vehicle damage from post collision photographs, analyzing sight lines, and video tracking. A critical aspect of camera-matching photogrammetry is determining the Field of View (FOV) of the photograph being analyzed. FOV is a function of the focal length of the camera and the size of the camera sensor and is recorded in the metadata of the photograph. The intent of this research is to analyze the accuracy of the metadata reported Field of View (FOV) and Focal Length. The FOV from photographs captured by over 20 different cameras of various makes, models, and focal lengths will be determined using a controlled and repeatable measurement methodology. The difference in measured FOV versus reported FOV will be presented and analyzed. This research will provide analysts with a quantifiable and acceptable range of FOVs when camera matching and utilizing the metadata from
Smith, Connor A., Erickson, Michael, Hashemian, Alireza
Technical Paper
A Novel Nonlinear Model Predictive Control Strategy for a Class of Nonlinear Systems with Multiple Actuators’ Response Time-Delays2025-01-8028To be published on 04/01/2025
This paper investigates the problem of nonlinear model predictive control (NMPC) strategy for a class of nonlinear systems with multiple actuators’ response time-delays. Considering the response time-delays of the actuators when constructing NMPC problem will usually greatly increase the scale of the optimization problem. To address these problems, a novel NMPC strategy is designed. At the first stage, the NMPC strategy is designed for the nonlinear system without actuator’s response time-delay, which will not increase the scale of the optimization problem. The optimal control sequence solved by NMPC is polynomial fitted into a time-continuous polynomial function, which is used as the reference signal of the actuators’ response time-delay models. At the second stage, combining inverse model and inverse Laplace transform techniques, a novel inverse model compensation control (IMCC) strategy is designed for actuators’ response time-delays, which can track the reference signal without
Wang, Bin
Technical Paper
Exploring the Automated Mobility Partnership (AMP) Portal's Capabilities for Enhancing Automated Driving Systems Safety Assurance Processes2025-01-8674To be published on 04/01/2025
The Automated Mobility Partnership (AMP) is a consortium of industry and academic stakeholders dedicated to advancing automated driving systems through a comprehensive suite of tools, datasets, and methodologies. The AMP portal contains ten years of U.S. police-reported crash data and over 35 million miles of curated naturalistic driving data, including thousands of annotated crashes and near-crashes. This resource enables data discovery, visualization, processing, and analysis through a secure web portal. This paper briefly describes the AMP portal and examines its utility in developing and evaluating the safety of automated systems using standardized processes. We analyze a hypothetical SAE Level 2 automation scenario with hands-off capabilities, guided by the Safety of the Intended Functionality (ISO 21448:2022) framework. The results show that AMP is instrumental in identifying triggering conditions, hazards, and functional insufficiencies. The portal uses the naturalistic driving
Antona-Makoshi, Jacobo, Williams, Vicki, Ali, Gibran, Sullivan, Kaye, Terranova, Paolo, Kefauver, Kevin, Hatchett, Alex
Technical Paper
Liquid Viscosity Decoupling Measurement Based on U-Shaped Tungsten Wire Sensor2025-01-8460To be published on 04/01/2025
In this paper, based on the cylindrical flow theory of incompressible viscous fluids and the equivalent circuit model of resonant sensing elements, a theoretical model for the measurement of liquid viscosity with a U-Shaped tungsten wire resonance sensor was established. This model can measure the liquid viscosity independently without liquid density or coupled detection of liquid density. The experimental results show that the decoupling of liquid viscosity and its density can be achieved at Re<1. The liquid viscosity is strongly linear with the resonant conductance. The viscosity measurement error is less than 7.24% in the viscosity range of 7.235cP to 85.2cP
Shan, Baoquan, Shen, Yitao, Yang, Jianguo, Wu, Dehong
Technical Paper
Simulation-Based Study on the Influence of Multiple Ferromagnetic Particles on the Voltage Signal of an Inductive Sensor2025-01-8398To be published on 04/01/2025
To address the issue of signal aliasing when multiple particles pass through a metallic particle sensor, which can lead to misidentification of particle count, we employ numerical simulation methods for an in-depth investigation. We developed a mathematical model of a three-coil inductive metal particle sensor to explore the signal variations induced by the passage of a single particle. We utilized micro-element simulation analysis to dissect the signal generated by a single particle, elucidating the underlying change process. Focusing on dual ferromagnetic particles as the subject of study, we conducted simulations and demodulation of the induced voltage under various combinations of sizes and spacings to investigate the influence patterns of two adjacent ferromagnetic particles on the sensor's induced signal. Further research into the peak signals of different diameter particles at a constant spacing revealed that, for a given spacing, the ratio of peak signals between particles of
Chen, Sen, Shen, Yitao, Wang, Zheyu, zheng, zheng, Qiang, Guiyan, HAO, YIN, Hu, Ting
Technical Paper
Coordinated Motor Speed Control Design for Seating Systems2025-01-8069To be published on 04/01/2025
Automotive seating systems have become much more sophisticated in terms of providing more flexible configurations and comfort functionalities to the consumer. Regular power seating with a few motors to move and adjust the seat position has turned to be more technical advanced reconfigurable systems with more sensors and actuators, such as Easy Entry, Zero Gravity, Stadium Swivel IP Nesting, Power Long Rails etc. The overall control of the seating becomes more and more like the robotics control with many coordinated movements. In this paper, a novel control strategy is proposed for the coordinated speed controls of multiple motors. Unlike traditional seating controls, other than the open loop controls, a feed-back approach is proposed together with a Kalman-filter based speed estimation via raw signal of Hall Effect sensor. The control of multiple motors at the same time will also be coordinated and synchronized properly, so that the seat will move in coordination, will not only not to
Yang, Hanlong, li, Miranda
Technical Paper
ROADSIDE TRAFFIC SURVEILLANCE FOR OPTIMAL TRAFFIC CONTROL USING A REAL-TIME EDGE COMPUTING PLATFORM2025-01-8099To be published on 04/01/2025
In recent years, traffic surveillance has become a crucial component of Intelligent Transportation Systems (ITS), playing a significant role in enhancing transportation safety, improving transit efficiency, refining traffic management and control, and fostering sustainability in urban and rural environments. The recent advancements in machine learning and sensor fusion technologies are expected to further increase the importance of traffic surveillance within ITS. Although traffic surveillance can be conducted through either centralized or distributed network architectures, the latter, enabled by edge computing, is becoming increasingly popular. Consequently, this research concentrates on leveraging deep learning and sensor fusion technologies for traffic surveillance on an edge computing platform. The technical objective is to develop a comprehensive system capable of detecting, classifying, localizing, and tracking vehicles using roadside sensors and AI computing hardware. For
Li, Shenglin, Leech, David, Yoon, Hwan-Sik
Technical Paper
Empirical Analysis on Machine Vision Recognition of Green Bike Lanes for Vulnerable Road Users Safety2025-01-8017To be published on 04/01/2025
Deliberate modifications to infrastructure can significantly enhance machine vision recognition of road sections designed for Vulnerable Road Users, such as green bike lanes. This study evaluates how green bike lanes, compared to unpainted lanes, enhance machine vision recognition and vulnerable road users safety by keeping vehicles at a safe distance and preventing encroachment into designated bike lanes. Conducted at the American Center for Mobility, this study utilizes a vehicle equipped with a front-facing camera to assess green bike lane recognition capabilities across various environmental conditions including dry daytime, dry nighttime, rain, fog, and snow. Data collection involved gathering a comprehensive dataset under diverse conditions and generating masks for lane markings to perform comparative analysis for training Advanced Driver Assistance Systems. Quality measurement and statistical analysis are used to evaluate the effectiveness of machine vision recognition using
Ponnuru, Venkata Naga Rithika, Das, Sushanta, Grant, Joseph, Naber, Jeffrey, Bahramgiri, Mojtaba
Technical Paper
Synchronizing Real-Time Control in Centralized Automotive E/E Architectures2025-01-8072To be published on 04/01/2025
Abstract: Automotive technologies have been rapidly evolving with the introduction of electric powertrains, Advanced Driver-Assistance System (ADAS) and Over-The-Air (OTA) upgradability. Existing decentralized architectures are not an optimal choice for these applications, due to significant increases in cost and complexity. The transition to centralized architectures enables heavy computation to be delegated to a limited number of powerful Electronic Control Units (ECUs) called domain or zone controllers. The remaining ECUs, known as smart actuators, will perform well defined and specific tasks, receiving new parameters from the dedicated domain/zone controller over a network. Net- work bandwidth and time synchronization are the two major challenges in this transition. New automotive standards have been developed to address these challenges. Automotive Ethernet and Time Sensitive Networking (TSN) are two standards that are well-suited for centralized architectures. This paper presents
Ayesh, Mostafa, Bandur, Victor, Pantelic, Vera, Wassyng, Alan, Wasacz, Bryon, Lawford, Mark
Technical Paper
RGB2BEV-Net: A PyTorch-based End-to-End Pipeline for RGB to BEV Segmentation Using an Extended Dataset for Autonomous Driving2025-01-8023To be published on 04/01/2025
In this work, we introduce RGB2BEV-Net, an end-to-end pipeline that extends traditional BEV segmentation models by utilizing raw RGB images with Bird’s Eye View (BEV) generation. While previous work primarily focused on pre-segmented images to generate corresponding BEV maps, our approach expands this by collecting RGB images alongside their affiliated segmentation masks and BEV representations. This enables direct input of RGB camera sensors into the pipeline, reflecting real-world autonomous driving scenarios where RGB cameras are commonly used as sensors, rather than relying on pre-segmented images. Our model processes four RGB images through a segmentation layer before converting them into a segmented BEV, implemented in the PyTorch framework after being adapted from an original implementation that utilized a different framework. This adaptation was necessary to improve compatibility, optimize performance and ensure better integration of the entire system within autonomous vehicle
Hossain, Sabir, Lin, Xianke
Technical Paper
Improved Distance Estimation in Dynamic Environments through Multi-sensor Fusion with Extended Kalman Filter2025-01-8034To be published on 04/01/2025
The application of multi-sensor fusion for enhanced distance estimation accuracy in dynamic environments is crucial for advanced driver assistance systems (ADAS) and autonomous vehicles. Limitations of single sensors such as camera or radar in adverse conditions motivate the use of combined camera and radar data to improve reliability, adaptability, and object recognition. A multi-sensor fusion approach using an Extended Kalman Filter (EKF) is proposed to combine sensor measurements with a dynamic system model, achieving robust and accurate distance estimation. The research utilizes the Mississippi State University Autonomous Vehicular Simulator (MAVS) to create a controlled environment for data collection. Data analysis is performed using MATLAB. Qualitative (visualization of fused data vs ground truth) and quantitative metrics (RMSE, MAE) are employed for performance assessment. Initial results with simulated data demonstrate accurate distance estimation compared to individual
Ebu, Iffat Ara, Islam, Fahmida, Rafi, Mohammad AbdusShahid, Iqbal, Umar, Rahman, Mahfuzur, Ball, John
Technical Paper
Synthesis and characterisation of poly (aniline –co-chloroaniline) polymers and applications in automotive industries as paint coatings2025-28-0037To be published on 02/07/2025
Polyaniline (PANI)-polymer based paints have emerged as a promising solution for enhancing the durability and performance of automobile surface coatings. These paint coatings offer superior corrosion resistance, conductivity, and environmental stability, making it an ideal. Here novel copolymers of dodecylbenzenesulfonic acid aided poly (aniline-co-m-chloroaniline) nanocomposites of various compositions were prepared by oxidative method in micellar solution. The nanocomposites were analyzed by using UV-Vis and FT-IR spectroscopic methods. The crystalline nature of the polymer was evidenced through XRD patterns. SEM revealed the presence of particles with spherical morphology 100 nm in diameter. The electrical activity of the doped polymer was found to be content increasing from 3:1 to 3:3 x 10-2 S/cm to 5.64 x 10-7 S/cm with chloroaniline. These copolymers are added as additives in manufacturing of paint. These novel paints offer multiple protective mechanisms, including barrier
Pachanoor, Vijayanand, Moorthi, Bharathiraja
Technical Paper
Fabrication And Analysis of Pneumatically Actuated Soft Robotic Gripper With Negative Pressure2025-28-0145To be published on 02/07/2025
Soft-bending actuators are gaining considerable attention in robotics for handling delicate objects and adapting to complex shapes, making them ideal for biomimetic robots. Soft pneumatic actuators (SPAs) are favoured in soft robotics due to their compliance and safety features. Using negative pressure for actuation, it enhances stability by reducing the risk of sudden or unintended movements, crucial for delicate handling and consistent performance. Negative pressure actuation is more energy-efficient, safe and are less prone to leakage, increasing reliability and durability. This paper involves development of a new soft pneumatic actuator design by comparing various designs and to determine its performance parameters. This paper depicts on designing, and fabricating flexible soft pneumatic actuators working under negative pressure for soft robotic applications. Uniaxial tensile tests were conducted to characterise the properties of materials used to fabricate the soft actuator, and
Warriar J S, Sreejith, Sadique, Anwar, George, Boby
Technical Paper
Autonomous Drone Solution for Human-Wildlife Conflict Management2025-28-0198To be published on 02/07/2025
Human-wildlife conflicts pose significant challenges to both conservation efforts and community well-being. As these conflicts escalate globally, innovative technologies become imperative for effective and humane management strategies. This paper presents an integrated autonomous drone solution designed to mitigate human-wildlife conflicts by leveraging technologies in drone surveillance and artificial intelligence. The proposed system consists of stationary IR cameras that are setup within the conflict prone areas, which utilizes machine learning to identify the presence of wild animals and to send the corresponding location to a drone docking station. An autonomous drone equipped with high resolution IR cameras and sensors is deployed from the docking station to the provided location. The drone camera utilizes object detection technology to scan the specified zone to detect the animal and emit animal repelling ultrasonic sound from a device integrated to the drone to achieve non
Sadanandan, Vaishnav, Sadique, Anwar, George, Angeo Pradeep, Vinod, Vishal, Raveendran, Darshan Unni
Technical Paper
Actuators, Linear Mechanical, General Specification GuideARP5812 (Current)01/09/2025
This SAE Aerospace Recommended Practice (ARP) establishes design, manufacturing performance and test requirements for linear mechanical actuators intended to be used for linear motion applications in response to manual or automatic power control system inputs. It is applicable, but not confined to, ball screws, sliding contact screws, roller screws, helical splines, rack and pinion assemblies, and skewed roller actuators. It is a reference for preparing detail specifications for mechanical actuators compatible and applicable to military or commercial aircraft systems
A-6B3 Electro-Mechanical Actuation Committee
Recommended Practice
Self-Learning Method for Shift Hub Position in a Double-Input Shaft Hybrid Gearbox Using Linear Active Disturbance Rejection Control and Nutcracker Optimization Algorithm02-18-01-000401/07/2025
Due to manufacturing, assembly, and actuator wear, slight deviations between the actual and logical positions of various gears in a transmission system may accumulate, affecting shift quality, reducing shift accuracy, and causing operational anomalies. To address this issue, a self-learning method based on the top dead center (TDC) and lower dead center (LDC) was proposed, specifically for the hybrid gearbox of an electric torque converter (eTC) module and a double-input shaft gearbox (DIG). The linear active disturbance rejection control (LADRC) method was employed to estimate and manage the nonlinear resistance during the motion of the shifting motor. To simplify the controller parameter problem, the nutcracker optimization algorithm (NOA) was utilized to tune the LADRC parameters, thereby optimizing the position self-learning process. The control strategy was modeled using MATLAB/SIMULINK, and its reasonableness was verified through hardware-in-the-loop (HIL) tests. Based on these
Hong, Hanchi, Quan, Kangning, d’Apolito, Luigi, Xu, Li
Journal Article
Low-Level Data Fusion between Camera and Automotive RADAR for Vehicle and Pedestrian Detection Using nuScenes Database2024-36-006412/20/2024
Autonomous driving technology has indeed become a focal point of research globally, with significant efforts directed towards enhancing its key components: environment perception, vehicle localization, path planning, and motion control. These components work together to enable autonomous vehicles to navigate complex environments safely and efficiently. Among these components, environment perception stands out as critical, as it involves the robust, real-time detection of targets on the road. This process relies heavily on the integration of various sensors, making data fusion an indispensable tool in the early stages of automation. Sensor fusion between the camera and RADAR (Radio Detection and Ranging) has advantages because they are complementary sensors, where fusion combines the high lateral resolution from the vision system with the robustness in the face of adverse weather conditions and light invulnerability of RADAR, as well as having a lower production cost compared to the
Cury, Hachid Habib, Teixeira, Evandro Leonardo Silva, Silva, Rafael Rodrigues
Technical Paper
Engine Speed Control for the Urban Hybrid-Flex Vehicle2024-36-011812/20/2024
Hybrid Electric Vehicles (HEVs) combine combustion and electric propulsion means to achieve key objectives, such as: reducing fuel consumption, minimizing pollutant emissions, and enhancing the overall energy efficiency of the Powertrain System. The series hybrid electric vehicles, in special, have a topology compound by four Subsystems, which are: Traction, Storage, Energy Generation, and Energy Management. The Energy Generation Subsystem is responsible for the power supply of the electric traction motors and batteries, depending on the control strategy promoted by the Energy Management Subsystem. The Energy Generation Subsystem is essentially made by an Internal Combustion Engine (ICE) and a Generator. Effective control of the power output from the Energy Generation Subsystem necessitates precise regulation of the engine speed. Thus, it is necessary to control the engine speed because this is directly related to the power demand of the consumers of other subsystem components. This
Júnior, João Marcos Hilário Barcelos, de Sousa Oliveira, Alessandro Borges, Teixeira, Evandro Leonardo Silva, Pereira, Bruno Luiz, Pinheiro, Leandro Soares, dos Santos Ribeiro, Eduardo, dos Santos de Oliveira, Jordano
Technical Paper
Zonal Architecture: A Way of Using of the CAN Protocol2024-36-012712/20/2024
In the automotive industry, the zonal architecture is a design approach that organizes a vehicle’s electronic and communication systems into specific zones. These zones group components based on their function and physical location, enabling more efficient integration and simplified communication between the vehicle’s various systems. An important aspect of this architecture is the implementation of the Controller Area Network (CAN) protocol. CAN is a serial communication protocol developed specifically for automotive applications, allowing various electronic devices within a vehicle, such as sensors, actuators, and Electronic Control Units (ECUs), to communicate with each other quickly and reliably, sharing information essential for the vehicle’s operation. However, due to its limitations, there is a need for more efficient protocols like Automotive Ethernet and Controller Area Network Flexible (CAN FD), which allow for higher transmission rates and larger data packets. To centralize
Santos, Felipe Carvalho, Silva, Antônio Lucas, Paterlini, Bruno, Pedroso, Henrique Gomes, Alves, Joyce Martins, Milani, Pedro Henrique Pires, Klepa, Rogério Bonette
Technical Paper
Automation of a Quarter-Car Suspension Test Bench2024-36-011512/20/2024
This paper aims to describe a quarter-car suspension test bench automation process to be utilized in an academic environment. The project is made up of pneumatic system modeling and control system design. An analysis of the bench’s pneumatic system is carried out. This pneumatic system is composed of a pneumatic actuator and a proportional directional control valve, which are responsible for generating the road profile. It is proposed a model to compensate the non-linearities present in the pneumatic system measurement process and the disturbances caused by the under test suspension system, as well as a control strategy for small displacements of the load through linear control approaches, which provide the necessary flexibility to directly influence the parameters affecting the dynamics of the excitation system platform’s displacement, thereby reducing the complexity of the controller design to be adopted. Furthermore, analyses are conducted on the effectiveness of the control in
Siqueira, Matheus Amaral, Gomes, Pedro Carvalho, Teixeira, Evandro Leonardo Silva, Fortaleza, Eugênio Libório Feitosa, Morais, Marcus Vinicius Girão
Technical Paper
Low-Cost Improvements of an Old Flow Bench and a Discussion of Replacing Orifice Plate by MAF in its Flow Measurement2024-36-007012/20/2024
Recognizing the significant challenges inherent in the analysis of periodic gas flow through reciprocating engines, one can easily appreciate the value of studying the steady flow through cylinder heads, manifolds, and exhaust systems. In these studies, flow benches are the cornerstone of the experimental apparatus needed to validate theoretical results or to perform purely experimental analysis. The Metal-Mechanics Department of IFSC owns a SuperFlow model SF-110 flow bench that has suffered some in house maintenance and received electronic sensors to allow computerized data acquisition. As the essential original sensors in this flow bench were liquid column manometer (for pressure difference across the test subject) and micromanometer (for pressure difference across the orifice plate used to measure the flow), the essential new sensors are electronic differential pressure sensors (installed in parallel with the original ones). In recent decades, however, the use of a mass air flow
Vandresen, Marcelo, dos Santos, Luciano Amaury
Technical Paper
Application of Servo-Assisted Technology in Commercial Vehicle Steering Systems for Autonomous Mobility in Off-Road Trucks. Case Study: Application on 8x2/8x4 Sugarcane Trucks2024-36-003312/20/2024
The exponential growth of the agribusiness market in Brazil combined with the high receptivity among farmers of new technological solutions has driven the study and implementation of high technology in the field. This work aimed to apply servo-assisted driving technology to enable autonomous mobility in an off-road sugarcane truck responsible for harvesting sugarcane. The technology consists of a conventional hydraulic steering with a motor, ECU and torque and angle sensors responsible for reading input data converted from GPS signals and previously recorded tracking lines. The motor responsible for replacing 100% of the physical force generated by the driver acts in accordance with the required torque demand, and the sensors combined with the ECU correct the course to meet the follow-up line through external communication ports. The accuracy of the system depends exclusively on the accuracy of the GPS signal, in this case reaching 2,5 cm, which is considered extremely high accuracy
Oliveira Santos Neto, Antídio, Lara, Vanderlei, Silva, Everton, Destro, Daniel, Moura, Márcio, Borges, Felipe, Haegele, Timo
Technical Paper
Flight Control Actuators - Dynamic Seals, Collection of Duty Cycle DataARP4895B (Current)12/18/2024
This SAE Aerospace Recommended Practice (ARP) provides an algorithm aimed to analyze flight control surface actuator movements with the objective to generate duty cycle data applicable to hydraulic actuator dynamic seals
A-6A3 Flight Control and Vehicle Management Systems Cmt
Recommended Practice
Unified Multi-Modal Multi-Agent Cooperative Perception Framework for Intelligent Transportation Systems2024-01-702812/13/2024
Cooperative perception has attracted wide attention given its capability to leverage shared information across connected automated vehicles (CAVs) and smart infrastructure to address the occlusion and sensing range limitation issues. To date, existing research is mainly focused on prototyping cooperative perception using only one type of sensor such as LiDAR and camera. In such cases, the performance of cooperative perception is constrained by individual sensor limitations. To exploit the multi-modality of sensors to further improve distant object detection accuracy, in this paper, we propose a unified multi-modal multi-agent cooperative perception framework that integrates camera and LiDAR data to enhance perception performance in intelligent transportation systems. By leveraging the complementary strengths of LiDAR and camera sensors, our framework utilizes the geometry information from LiDAR and the semantic information from cameras to achieve an accurate cooperative perception
Meng, Zonglin, Xia, Xin, Zheng, Zhaoliang, Gao, Letian, Liu, Wei, Zhu, Jiaqi, Ma, Jiaqi
Technical Paper
Research on a Detection Algorithm of Contaminant on Automotive Cameras Optical Surface Based on SEFaster-YOLOv82024-01-703212/13/2024
Cameras are crucial sensors in intelligent driving systems. Due to the optical windows of these cameras generally being exposed, they are highly susceptible to contaminant from external dust, mud, and other contaminants. These contaminants can degrade the vehicle’s perception capabilities, posing safety risks. Therefore, research on the identification and automatic cleaning of optical window surface contamination for automotive cameras is essential. This paper constructs a dataset of contaminated images of automotive cameras using a method based on shooting and image fusion. By introducing the SE attention mechanism and replacing the YOLOv8 backbone network with FasterNet, this paper proposed the SEFaster-YOLOv8 model. Experimental results show that the SEFaster-YOLOv8 model reduces the parameter count by 37.6% compared to the original YOLOv8 model. The mAP@0.5 and mAP@0.5:0.95 reach 95.7% and 66.9%, respectively, representing improvements of 1.8% and 1.1% over the original YOLOv8
Ran, Lujia, Hu, Zongjie, Lu, Xiangxiang, Wu, Zhijun
Technical Paper
Cracking Activity and Characterization of Magnesium Titanium Dioxide - Silicon Dioxide Catalysts2024-01-524112/10/2024
Purified nickel and a large number of MgTi2 / NiO2 catalysts with various MgTi2 loadings were produced using the traditional incipient wetness method. X-ray crystallography and Fourier-transform infrared spectroscopy were used to examine the catalysts. To understand the material's microstructure better, the researchers investigated oxygen adsorption at 90K. The amine titration method was used to investigate the acidic characteristics of these catalysts. In a study on cumene cracking, these catalysts were employed. The catalyst was found to be amorphous up to a loading of 12 weight percent MgTi2, but at higher loadings, crystalline MgTi2 phase formed on an amorphous silica substrate. When NiO2 is doped with more MgTi2, there are significant differences in the structure, surface acidity, and catalytic activity of the catalysts. Catalysts with a higher MgTi2 loading are noticeably more acidic than those with a lower MgTi2 loading. A correlation between the amount of cracking activity and
Ashok Kumar, B., Dhiyaneswaran, J., Selvaraj, Malathi, Pradeepkumar, M., Shajeeth, S.
Technical Paper
Automatic Hose Cutting Machine for Small Scale Industries2024-01-521712/10/2024
The goal of this work is to increase the accuracy and efficiency of hose cutting operations in small scale industries is by designing and building an automatic hose-cutting equipment. The device uses a computer-controlled system to autonomously cut pipes of various sizes and lengths. By means of a stepper motor-driven, rapidly spinning blade, the cutting process is accomplished. Additionally, the machine has sensors that measure the hose's length and modify the cutting position as necessary. Premium components and materials are used in the machine's construction; these are chosen for their performance and longevity. The device is able to boost cut precision and raise industry production all around from 100% to 190% efficient system thereby decreasing labor and time needed for hose cutting operations
Feroz Ali, L., Manikandan, R., Madhankumar, S., Sri Hari, P., Suriya Prakash, T., Vishnu Doss, G.
Technical Paper
Design and Implementation of Advanced Safety Features in Two-Wheeled Vehicles for Accident Prevention and Anti-Theft System2024-01-522912/10/2024
Embarking on exploring the cutting-edge domain of smart bike innovations, this study focuses primarily on enhancing safety and security measures. Through meticulous development and implementation, it introduces seven pioneering features to curb accidents and thwart theft incidents. These transformative functionalities encompass a spectrum of aspects, including cautionary systems for side stand and helmet usage, advanced alcohol detection mechanisms, and robust anti-theft measures employing ID card and password protocols. Moreover, integrating speed control mechanisms and automated brake activation on encountering speed breakers further elevates the safety quotient of the smart bike. By harnessing a diverse array of sensors such as RF, REED, ultrasonic, and gas sensors, these features collectively pave the way for a paradigm shift in road safety standards. The report meticulously details the intricacies of design, execution, and cost estimation, underscoring the transformative impact of
Mallieswaran, K., Agaramudhalvan, S., Nithya, R., Shuruti, R., Radhika, S.
Technical Paper
Autonomous Mobile Robot for Gas Leak Localization2024-01-522612/10/2024
LIDAR-based autonomous mobile robots (AMRs) are gradually being used for gas detection in industries. They detect tiny changes in the composition of the environment in indoor areas that is too risky for humans, making it ideal for the detection of gases. This current work focusses on the basic aspect of gas detection and avoiding unwanted accidents in industrial sectors by using an AMR with LIDAR sensor capable of autonomous navigation and MQ2 a gas detection sensor for identifying the leakages including toxic and explosive gases, and can alert the necessary personnel in real-time by using simultaneous localization and mapping (SLAM) algorithm and gas distribution mapping (GDM). GDM in accordance with SLAM algorithm directs the robot towards the leakage point immediately thereby avoiding accidents. Raspberry Pi 4 is used for efficient data processing and hardware part accomplished with PGM45775 DC motor for movements with 2D LIDAR allowing 360° mapping. The adoption of LIDAR-based AMRs
Feroz Ali, L., Madhankumar, S., Hariush, V.C., Jahath Pranav, R., Jayadeep, J., Jeffrey, S.
Technical Paper
Design and Implementation of a Detailed Digital Fuel Indicator System for Accurate Fuel Monitoring2024-01-520012/10/2024
This research introduces a Detailed Digital Fuel Indicator (DDFI) system to enhance fuel monitoring accuracy in automobiles using advanced infrared (IR) sensor technology for precise fuel level detection. The innovative system includes a secondary tank, meticulously calibrated to the volumetric ratio of the primary tank, to ensure consistent and accurate readings. The DDFI system provides real-time data on fuel levels with an impressive accuracy of ±5%, a notable improvement over the traditional methods. Key components of the system include an IR sensor, a programmable integrated circuit (IC), and a secondary tank fabricated from galvanized iron (GI) sheet metal, ensuring durability and reliability in various environmental conditions. The system is designed to be user-friendly, offering an intuitive interface for drivers to monitor fuel levels effortlessly. Additionally, the DDFI system integrates seamlessly with existing vehicle systems, allowing for easy installation and minimal
Mallieswaran, K., Nithya, R., Rajendran, Shuruti, Arulaalan, M.
Technical Paper
AI-Based Smart Vehicle Parking System2024-01-524212/10/2024
This project presents the development of an advanced Autonomous Mobile Robot (AMR) designed to autonomously lift and maneuver four-wheel drive vehicles into parking spaces without human intervention. By leveraging cutting-edge camera and sensor technologies, the AMR integrates LIDAR for precise distance measurements and obstacle detection, high-resolution cameras for capturing detailed images of the parking environment, and object recognition algorithms for accurately identifying and selecting available parking spaces. These integrated technologies enable the AMR to navigate complex parking lots, optimize space utilization, and provide seamless automated parking. The AMR autonomously detects free parking spaces, lifts the vehicle, and parks it with high precision, making the entire parking process autonomous and highly efficient. This project pushes the boundaries of autonomous vehicle technology, aiming to contribute significantly to smarter and more efficient urban mobility systems
Atheef, M. Syed, Sundar, K. Sham, Kumar, P. P. Prem, Karthika, J.
Technical Paper
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