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Sensors and Perception for Autonomous Vehicle Development

2024-10-21
This 4-week virtual-only experience, conducted by leading experts in the autonomous vehicle industry and academia, provides an in-depth look at the most common sensor types used in autonomous vehicle applications. By reviewing the theory, working through examples, viewing sensor data, and programming movement of a turtlebot, you will develop a solid, hands-on understanding of the common sensors and data provided by each. This course consists of asynchronous videos you will work through at your own pace throughout each week, followed by a live-online synchronous experience each Friday. The videos are led by Dr.
Technical Paper

Comparative Analysis of GenAI Models for EV Battery Characterization Data Expansion and Validation

2024-10-17
2024-28-0032
Rapid advancement of electric vehicle (EV) technology has propelled the need for reliable and efficient methods for battery data expansion and validation. This has vital importance – to ensure safety aspects and efficient design of EV system. Traditional data collection methods for battery characterization are a large subject for the design of experiments and are often expert’s skill intensive, time-consuming, and lack scalability. This study proposes a Generative Artificial Intelligence (GenAI) based approach for two activities – First to assist the DOE of cell/battery characterization at different C rates and temperatures accounting for varied degradation rates. Secondly, manipulations of characterization data accounting for measurement and data recording errors. The study compares GenAI models like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer-based (Time-GPT) models in generating and validating EV battery characterization data.
Technical Paper

Enhancing Autonomous Vehicle Safety: A Statistical Approach to Real-Time Anomaly Detection in Autonomous Vehicles

2024-10-17
2024-28-0033
Enhancing Autonomous Vehicle Safety: A Statistical Approach to Real-Time Anomaly Detection in Autonomous Vehicles In 2022, Automakers reported approximately 400 crashes of vehicles with partially automated driver-assist systems to the NHTSA. Out of the 98 self-driving crashes with injuries, 11 resulted in serious injuries. Five incidents involving Tesla’s were fatal. According to Policy Advice, 43% of Americans are uncomfortable inside a driverless car, citing safety as their biggest concern. A survey by Advocates for Highway and Auto Safety indicated 75% of people would rather drive themselves than ride in an AV. The current limitations of training data for autonomous vehicles (AVs) can lead to performance deficiencies when encountering unexpected scenarios beyond their training scope. This can compromise passenger safety and hinder public trust in AV technology.
Technical Paper

Automotive security solution using Hardware Security Module (HSM)

2024-10-17
2024-28-0037
In today's world, Vehicles are no longer mechanically dominated, with increased complexity, features and autonomous driving capabilities, vehicles are getting connected to internal and external environment e.g., V2I(Vehicle-to-Infrastructure), V2V(Vehicle-to-Vehicle), V2C(Vehicle-to-Cloud) and V2X(Vehicle-to-Everything). This has pushed classical automotive system in background and vehicle components are now increasingly dominated by software’s. Now more focus is made on to increase self-decision-making capabilities of automobile and providing more advance, safe and secure solutions e.g., Autonomous driving, E-mobility, and software driven vehicles, due to which vehicle digitization and lots of sensors inside and outside the vehicle are being used, and automobile are becoming intelligent. i.e., intelligent vehicles with advance safe and secure features but all these advancements come with significant threat of cybersecurity risk.
Technical Paper

Contextual Study of Security and Privacy in Key As A Service (KAAS) for Architecture & Networking products

2024-10-17
2024-28-0039
One of the mega trends in the automotive industry, to integrate the car with the smartphone, has opened the adoption of Key-as-a-Service (KaaS). Traditionally, car keys or key fobs have been physical devices that provide entry and ignition capabilities. However, KaaS offers a digital alternative to traditional keys, which allow users to access and operate their vehicles using their smartphones or other digital devices. This innovative approach brings numerous benefits, including user personalization, enhanced security, remote access, and integration along with other digital services and ecosystems. KaaS also opens new possibilities for vehicle sharing and temporary access arrangements. Users can grant access to family members, friends, or service providers for a specific time-period without the need for physical key handovers. While KaaS offers convenience and flexibility, it also introduces potential security risks that must be carefully considered and addressed.
Technical Paper

Prediction of water film thickness due to condensation over instrument cluster based on Eulerian Wall Film approach of computational fluid dynamics

2024-10-17
2024-28-0009
This paper investigates the condensation within a two wheeler instrument cluster in different weather conditions. Instrument cluster have high heating components within its assembly particularly over Printed Circuit Board (PCB) which leads to formation of condensation. Air breathers are important component that can be utilized to reduce the condensation in the cluster. Location and orientation of air breather and air vents plays the vital role in the air flow through the instrument cluster. In this study, number of breather and their location and orientation is optimized to reduce the condensation or film thickness on the crystal (transparent body) of cluster. Transient Computational Fluid Dynamics (CFD) based Eulerian Wall Film approach is utilized to investigate the physics administering the condensation phenomenon in the instrument cluster. Experimental tests are conducted to investigate condensation phenomenon actually occurring in the model.
Technical Paper

Towards automation of reference data generation for ADAS/AD functions development – ALiVA framework

2024-10-17
2024-28-0022
The advancements towards autonomous driving have propelled the need for reference/ground truth data for development & validation of various functionalities. Traditional data labelling methodologies are time consuming, skills intensive & have many drawbacks. These challenges are addressed through ALiVA (automatic lidar, image & video annotator), a semi-automated framework assisting for event detection & reference data generation through annotation/labelling of video & point-cloud data. ALiVA is capable of processing large volumes of camera & lidar sensor data. Main pillars of framework are object detection-classification models, object tracking algorithms, cognitive algorithms & annotation results review functionality. Automatic object detection functionality generates precise bounding box around the area of interest & assigns class labels to annotated objects.
Technical Paper

Design, Modeling and Analysis of Roll Cage for SAE BAJA Vehicle

2024-10-17
2024-28-0012
This paper studies design parameters, selection of materials and structural analysis for an All-Terrain Vehicle (ATV) BAJA roll cage at the event site in any possible situation. SolidWorks 2022 was used for creating the prototype of the roll cage and then both static structural as well as dynamic crash analysis for the roll cage was done using Altair HyperWorks 2023 for various collisions like front, rear, side, rollover, torsional, front bump, rear bump, front roll over, side roll over and rear roll over. In addition to their corresponding deformation, Von Mises stresses were observed and a safety factor was calculated for these load cases which was found to be in the range of 1.5 to 3. Without reducing the roll cage’s strength, the roll cage designed for a four-wheel drive configuration is developed with driver comfort and safety in mind. Finding the optimal safety factor is the core objective of the analysis, as it ensures in any situation, the ATV’s roll cage will stay secure.
Technical Paper

Enhancing Gear Performance: Discrete Response Optimization through OptiSLang

2024-10-17
2024-28-0040
Original equipment manufacturers have already begun to transition their vehicles from traditional internal combustion engines (ICs) to electric drives (EVs). As the industry continues to move towards electrification, the entire industry, and especially Valeo, is focusing on lean product development (LPD) with the help of numerical simulation. Optimization techniques help industry achieve the most accurate product at the lowest cost without sacrificing performance. Generally gears are mainly used for power transmission in the advanced technologies of electric vehicles. There are many factors that must be taken into account when designing a gear transmission system. Finding the most appropriate design parameters for a gear transmission system can be a challenge, and optimization parameters will help to find the best compromise between them.
Technical Paper

Enhancing the safety and handling of virtual vehicles in simulated traffic: A co-simulation approach with Multibody dynamics & Carla

2024-10-17
2024-28-0026
In recent years, there has been an increased emphasis on autonomous driving technologies to improve vehicle road safety amidst rising traffic congestion and the complexities of intersection, jaywalking and diverse road conditions. Therefore, improving the vehicle's handling ability is crucial for safe and efficient traffic navigation, particularly emphasizing collision prevention and safety in unforeseen circumstances. Evaluating safety perspectives in such situations, the lane change event serves as an important measure for addressing the matter and forms the focus of this paper. However, for such new age technology conducting proving ground tests replicating urban conditions is a costly endeavour. Hence, simulation is a better approach which can mimic real traffic conditions, develop control systems, and simulate vehicle handling behaviour, all working together within a closed-loop system.
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