Tootfinder

NYC's Muslim mayoral candidate gets car bomb threat, despite not owning a vehicle (Greg Wehner/Fox News)
https://www.foxnews.com/politics/nycs-muslim-mayoral-candidate-gets-car-bomb-threat-despite-not-owning-vehicle
http://www.memeorandum.com/250619/p123#a250619p123

How many RPMs? Your next car may run Red Hat Linux.
https://www.redhat.com/en/about/press-releases/red-hat-prepares-new-future-software-defined-vehicles-upcoming-general-availab…

Red Hat Prepares for a New Future of Software-Defined Vehicles with Upcoming General Availability of Red Hat In-Vehicle Operating System
Open source, continuously-certified operating system platform set for Q3 2025 launch, bringing safety-certified Linux to automotive manufacturers and suppliers

#Copper #Mining and Vehicle Electrification | IEF Report
"To meet ... trends, 115% more copper must be mined in the next 30 years than has been mined historically until now. To electrify the global vehicle fleet requires bringing into production 55% more new mines than would otherwise be needed. On…

Copper Mining and Vehicle Electrification | IEF Report
Many studies have raised concerns that copper supply cannot meet the copper demands of both the green energy transition and equitable global development. This report addresses this issue by projecting copper supply and demand from 2018 to 2050 and placing both in the historical context of copper mine output.

SurfAAV: Design and Implementation of a Novel Multimodal Surfing Aquatic-Aerial Vehicle
Kun Liu, Junhao Xiao, Hao Lin, Yue Cao, Hui Peng, Kaihong Huang, Huimin Lu
https://arxiv.org/abs/2506.15450

SurfAAV: Design and Implementation of a Novel Multimodal Surfing Aquatic-Aerial Vehicle
Despite significant advancements in the research of aquatic-aerial robots, existing configurations struggle to efficiently perform underwater, surface, and aerial movement simultaneously. In this paper, we propose a novel multimodal surfing aquatic-aerial vehicle, SurfAAV, which efficiently integrates underwater navigation, surface gliding, and aerial flying capabilities. Thanks to the design of the novel differential thrust vectoring hydrofoil, SurfAAV can achieve efficient surface gliding and…

SFMTA board is hearing Mayor Lurie’s mass displacement plan to banish working-poor, mostly Latino families living in RVs from the city.
Here’s the “refuge permit” designed as window dressing to make liberals feel ok about this. Notice to get one, you have to “agree to accept offer of… interim… housing,” ie agree to be displaced a little later anyway. 💩
#sfpol

Der weltweite #Boom bei #Elektroautos könnte in wenigen Jahren wegen eines drohenden #Lithium-Engpasses ins Stocken geraten.
Eine neue Studie zeigt, dass der Bedarf in den

Electric vehicle boom could hit major roadblock in just 5 years, study claims | BBC Science Focus Magazine
With sales skyrocketing, a shortage of this key critical material could halt progress

Building Automotive Security on Internet Standards: An Integration of DNSSEC, DANE, and DANCE to Authenticate and Authorize In-Car Services
Timo Salomon, Mehmet Mueller, Philipp Meyer, Thomas C. Schmidt
https://arxiv.org/abs/2506.13261

Building Automotive Security on Internet Standards: An Integration of DNSSEC, DANE, and DANCE to Authenticate and Authorize In-Car Services
The automotive industry is undergoing a software-as-a-service transformation that enables software-defined functions and post-sale updates via cloud and vehicle-to-everything communication. Connectivity in cars introduces significant security challenges, as remote attacks on vehicles have become increasingly prevalent. Current automotive designs call for security solutions that address the entire lifetime of a vehicle. In this paper, we propose to authenticate and authorize in-vehicle services …

Exploded SpaceX Starship rocket #4. And this is the vehicle that's supposed to send humans to the moon?
▶️ SpaceX Starship 36 Explodes During Flight 10 Testing at Starbase
https://youtube.com/watch?v=71AwkBt3_ts&si=Y5W-ysa0rXmEwoKF
✅ Read more he…

I don't want to travel on a vehicle that explodes or implodes or requires me to smell other people.

Ahh. ... Elon did it again...
Video:
#SpaceX

Spatial Optimization of Autonomous Vehicle Assignment Based on Distance-Driven Demand and Customer Patience
Niloufar Mirzavand Boroujeni, Nasim Mirzavand Boroujeni, Nima Moradi, Saeed Jamalzadeh
https://arxiv.org/abs/2506.12671

Spatial Optimization of Autonomous Vehicle Assignment Based on Distance-Driven Demand and Customer Patience
Autonomous vehicles (AVs) can improve efficiency, reduce costs, and enhance road safety. They optimize traffic flow, minimize congestion, and support sustainability through shared mobility and reduced fuel consumption. A key challenge in AV deployment is allocating vehicles to parking lots across regions to meet fluctuating demand. Proper allocation reduces delays, lowers costs, and boosts user satisfaction by ensuring timely vehicle availability. This paper explores the impact of customer wait…

https://www.cyberdaily.au/security/12253-major-truck-manufacturer-scania-confirms-insurance-site-cyber-attack
Another insurance attack.
Major truck manufacturer Scania confirms insurance site cyber attack

Major truck manufacturer Scania confirms insurance site cyber attack
Swedish heavy vehicle manufacturer Scania has confirmed that threat actors successfully breached its insurance and financial services division.

Bridging Data-Driven and Physics-Based Models: A Consensus Multi-Model Kalman Filter for Robust Vehicle State Estimation
Farid Mafi (University of Waterloo, Waterloo, Canada), Ladan Khoshnevisan (University of Waterloo, Waterloo, Canada), Mohammad Pirani (University of Ottawa, Ottawa, Canada), Amir Khajepour (University of Waterloo, Waterloo, Canada)

Bridging Data-Driven and Physics-Based Models: A Consensus Multi-Model Kalman Filter for Robust Vehicle State Estimation
Vehicle state estimation presents a fundamental challenge for autonomous driving systems, requiring both physical interpretability and the ability to capture complex nonlinear behaviors across diverse operating conditions. Traditional methodologies often rely exclusively on either physics-based or data-driven models, each with complementary strengths and limitations that become most noticeable during critical scenarios. This paper presents a novel consensus multi-model Kalman filter framework t…

Self-driving simulation software maker Applied Intuition raised $600M co-led by BlackRock and Kleiner Perkins at a $15B valuation, up from $6B in March 2024 (Katie Roof/Bloomberg)
https://www.bloomberg.com/news/articles/20

This grassy field has always been a beautiful buffer between the river and the train tracks that service the local waste management company that owns it. This time of year, wildflowers and butterflies are everywhere and it’s one of the highlights on this part of the greenway.
This week, I’ve noticed it’s suddenly begun to accumulate vintage fire and rescue vehicles. I don’t know what to make of it, but I hope it’s temporary.

My guess on the Palm Springs vehicle from pictures is either a Toyota Corolla or a VW Jetta.

Photo of the guy with his vehicle

Building Automotive Security on Internet Standards: An Integration of DNSSEC, DANE, and DANCE to Authenticate and Authorize In-Car Services
Timo Salomon, Mehmet Mueller, Philipp Meyer, Thomas C. Schmidt
https://arxiv.org/abs/2506.13261

Building Automotive Security on Internet Standards: An Integration of DNSSEC, DANE, and DANCE to Authenticate and Authorize In-Car Services
The automotive industry is undergoing a software-as-a-service transformation that enables software-defined functions and post-sale updates via cloud and vehicle-to-everything communication. Connectivity in cars introduces significant security challenges, as remote attacks on vehicles have become increasingly prevalent. Current automotive designs call for security solutions that address the entire lifetime of a vehicle. In this paper, we propose to authenticate and authorize in-vehicle services …

Yesterday and today I issued four handmade parking tickets, and left them on the windshield of each vehicle. I hope that when they return to their vehicle, they feel embarrassed. I am a below knee amputee. I am what most people would call disabled, however there are only a few areas of my life in which I actually feel disabled, and it is more accurate to describe me as having an impairment rather than a disability.

A Kinematic Constraint on Pedestrian Walking: Power-law Scaling between Critical Angular Velocity and Speed
Jinghui Wang, Wei Lv, Chao Li, Yufei Li
https://arxiv.org/abs/2506.15321

A Kinematic Constraint on Pedestrian Walking: Power-law Scaling between Critical Angular Velocity and Speed
This paper presents a statistical analysis of speed and angular velocity obtained from pedestrian experiments across nine distinct datasets. Experimental scenarios included crossing motion, unidirectional/bidirectional flows, bidirectional/four-directional crossing flows, pedestrian-vehicle interactions, unidirectional flow in a circular corridor, and circle antipode configurations. We applied filtering methods to reduce noise and analyzed the data at different sampling frequencies. The results…

MatchPlant: An Open-Source Pipeline for UAV-Based Single-Plant Detection and Data Extraction
Worasit Sangjan, Piyush Pandey, Norman B. Best, Jacob D. Washburn
https://arxiv.org/abs/2506.12295

MatchPlant: An Open-Source Pipeline for UAV-Based Single-Plant Detection and Data Extraction
Accurate identification of individual plants from unmanned aerial vehicle (UAV) images is essential for advancing high-throughput phenotyping and supporting data-driven decision-making in plant breeding. This study presents MatchPlant, a modular, graphical user interface-supported, open-source Python pipeline for UAV-based single-plant detection and geospatial trait extraction. MatchPlant enables end-to-end workflows by integrating UAV image processing, user-guided annotation, Convolutional Neu…

jennifer_lawrence_okay.gif

Law enforcement official on Hortman shooting:
"It was knocking on the door and asking the person to come out.
Absolutely impersonating a police officer ... we have the suspect's car. The suspect is on foot."
https://skywriter.blue/pages/did:plc:4

Diesel, petrol and Tesla car sales down across Europe
Nobody wants to get their hands dirty.
https://www.electrive.com/2025/05/27/electric-cars-overtake-diesel-in-new-eu-vehicle-registrations/

Electric cars overtake diesel in new EU vehicle registrations - electrive.com
According to the industry association ACEA, new registrations of electric cars in the EU rose by 26 per cent year-on-year to just under 560,000 units in the

EU electric car sales in April up 34% compared to last year, but Tesla sales *down* 53%, an even stronger fall than in the first quarter of the year.
https://www.electrive.com/2025/05/27/electric-cars-overtake-diesel-in-new-eu-veh…

Electric cars overtake diesel in new EU vehicle registrations - electrive.com
According to the industry association ACEA, new registrations of electric cars in the EU rose by 26 per cent year-on-year to just under 560,000 units in the

Low-Cost Wideband Tilted Beam Antenna for Millimeter-wave Vehicle Applications
Jiawang Li
https://arxiv.org/abs/2506.08239 https://ar…

Low-Cost Wideband Tilted Beam Antenna for Millimeter-wave Vehicle Applications
To facilitate vehicle coverage for millimeter-wave applications, this communication presents a low-cost, wideband tilted-beam antenna. A novel design is proposed in which a slot antenna is both directly excited and electromagnetically coupled to a monopole array. This slot-monopole configuration is inherently robust against substrate losses, enabling low-cost fabrication while maintaining high realized gain and compact size. Furthermore, the slot-fed structure effectively excites multiple reson…

Comparison of Innovative Strategies for the Coverage Problem: Path Planning, Search Optimization, and Applications in Underwater Robotics
Ahmed Ibrahim, Francisco F. C. Rego, \'Eric Busvelle
https://arxiv.org/abs/2506.15376

Comparison of Innovative Strategies for the Coverage Problem: Path Planning, Search Optimization, and Applications in Underwater Robotics
In many applications, including underwater robotics, the coverage problem requires an autonomous vehicle to systematically explore a defined area while minimizing redundancy and avoiding obstacles. This paper investigates coverage path planning strategies to enhance the efficiency of underwater gliders, particularly in maximizing the probability of detecting a radioactive source while ensuring safe navigation. We evaluate three path-planning approaches: the Traveling Salesman Problem (TSP), M…

(Bicycle) Speed and safety
For years I've heard people talking about how motor-assisted bicycles "are safer" because they can "match traffic speed", but I think this is mistaken.  Here's three reasons why. For me the most compelling reason comes from a 2007 paper by Laurie F. Beck, Ann M. Dellinger, and Mary E. O’Neil in the American Journal of Epidemiology, "Motor Vehicle Crash Injury Rates by Mode of Travel, United States: Using Exposure-Based Methods…

(Bicycle) Speed and safety
For years I’ve heard people talking about how motor-assisted bicycles “are safer” because they can “match traffic speed”, but I think this is mistaken.  Here’s t…

Did my first #AmateurRadio bike race support today as a family activity. My oldest and I ran separate ham SAG vehicles, and my wife ran net control some of the time.
I had borrowed a mobile U/VHF rig from my club so that we could have one rig in each vehicle, but then my coax was apparently damaged for the antenna in the other car which disabled its mobile rig, so "bring your …

Urban Discoveries 🏙️
都市发现 🏙️
📷 Pentax MX
🎞️Lucky SHD 400
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

Yiding Cao Geld mit PayPal.Me senden
Folgen Sie dem Link PayPal.Me/dingsterdingster und geben Sie den Betrag ein. Es ist bequem und sicher. Sie haben noch kein PayPal-Konto? Kein Problem.

So last night, after watching the Russian Victory Day ‘24 video for contrast, I thought “what the hell” & went ahead & watched1️⃣ the PBS YT video of the “June 24 Military2️⃣ Parade” to see if it was as bad as all that
(Short Answer: Yes and No)
But this guy was the one that caught my sympathy as “you poor dude”.

Trump's economic and tariff chaos is causing businesses to back off expansion plans.
https://scdailygazette.com/2025/06/05/electric-vehicle-battery-company-halts-construction-of-sc-manufacturing-plant/

On secure UAV-aided ISCC systems
Hongjiang Lei, Congke Jiang, Ki-Hong Park, Mohamed A. Aboulhassan, Sen Zhou, Gaofeng Pan
https://arxiv.org/abs/2506.13137 …

On secure UAV-aided ISCC systems
Integrated communication and sensing, which can make full use of the limited spectrum resources to perform communication and sensing tasks simultaneously, is an up-and-coming technology in wireless communication networks. In this work, we investigate the secrecy performance of an uncrewed aerial vehicle (UAV)-assisted secure integrated communication, sensing, and computing system, where the UAV sends radar signals to locate and disrupt potential eavesdroppers while providing offload services to…

Mixed Traffic: A Perspective from Long Duration Autonomy
Filippos Tzortzoglou, Logan E. Beaver
https://arxiv.org/abs/2506.15004 https://

Mixed Traffic: A Perspective from Long Duration Autonomy
The rapid adoption of autonomous vehicle has established mixed traffic environments, comprising both autonomous and human-driven vehicles (HDVs), as essential components of next-generation mobility systems. Along these lines, connectivity between autonomous vehicles and infrastructure (V2I) is also a significant factor that can effectively support higher-level decision-making. At the same time, the integration of V2I within mixed traffic environments remains a timely and challenging problem. In…

Bedrock Ocean, which has developed an autonomous underwater vehicle to map the ocean floor using sonar and magnetic sensors, raised a $25M Series A-2 (Tim De Chant/TechCrunch)
https://techcrunch.com/2025/06/10/bedrock-ocean-dredges-u…

Exclusive: Bedrock Ocean dredges up $25M to map the seafloor with robots | TechCrunch
Bedrock Ocean wants to use autonomous underwater vehicles to make mapping the seafloor faster and cheaper.

Knowledge-Guided Attention-Inspired Learning for Task Offloading in Vehicle Edge Computing
Ke Ma, Junfei Xie
https://arxiv.org/abs/2506.04456 https://

Knowledge-Guided Attention-Inspired Learning for Task Offloading in Vehicle Edge Computing
Vehicle edge computing (VEC) brings abundant computing resources close to vehicles by deploying them at roadside units (RSUs) or base stations, thereby enabling diverse computation-intensive and delay sensitive applications. Existing task offloading strategies are often computationally expensive to execute or generate suboptimal solutions. In this paper, we propose a novel learning-based approach, Knowledge-guided Attention-inspired Task Offloading (KATO), designed to efficiently offload tasks …

Being hit by an SUV increases the likelihood of death or serious injury
https://www.lshtm.ac.uk/newsevents/news/2025/being-hit-suv-increases-likelihood-death-or-serious-injury
So, when will lawmakers catch up…

Being hit by an SUV increases the likelihood of death or serious injury | LSHTM
The likelihood of a pedestrian or cyclist being fatally injured is 44% higher if they are hit by a sports utility vehicle (SUV) or light truck vehicle (LTV) compared with smaller passenger cars, new

Nexus of Team Collaboration Stability on Mega Construction Project Success in Electric Vehicle Manufacturing Enterprises: The Moderating Role of Human-AI Integration
Jun Cui
https://arxiv.org/abs/2506.06375

Nexus of Team Collaboration Stability on Mega Construction Project Success in Electric Vehicle Manufacturing Enterprises: The Moderating Role of Human-AI Integration
This study investigates how team collaboration stability influences the success of mega construction projects in electric vehicle manufacturing enterprises, with human-AI integration as a moderating variable. Using structural equation modeling (SEM) with data from 187 project teams across China's electric vehicle sector, results indicate that team collaboration stability significantly enhances project success. The moderating effect of human-AI integration strengthens this relationship, suggesti…

Video Quality Monitoring for Remote Autonomous Vehicle Control
Dimitrios Kafetzis, Nikos Fotiou, Savvas Argyropoulos, Jad Nasreddine, Iordanis Koutsopoulos
https://arxiv.org/abs/2506.03166

Video Quality Monitoring for Remote Autonomous Vehicle Control
The delivery of high-quality, low-latency video streams is critical for remote autonomous vehicle control, where operators must intervene in real time. However, reliable video delivery over Fourth/Fifth-Generation (4G/5G) mobile networks is challenging due to signal variability, mobility-induced handovers, and transient congestion. In this paper, we present a comprehensive blueprint for an integrated video quality monitoring system, tailored to remote autonomous vehicle operation. Our proposed …

An Empirical study on LLM-based Log Retrieval for Software Engineering Metadata Management
Simin Sun, Yuchuan Jin, Miroslaw Staron
https://arxiv.org/abs/2506.11659

An Empirical study on LLM-based Log Retrieval for Software Engineering Metadata Management
Developing autonomous driving systems (ADSs) involves generating and storing extensive log data from test drives, which is essential for verification, research, and simulation. However, these high-frequency logs, recorded over varying durations, pose challenges for developers attempting to locate specific driving scenarios. This difficulty arises due to the wide range of signals representing various vehicle components and driving conditions, as well as unfamiliarity of some developers' with the…

Trilevel Memetic Algorithm for the Electric Vehicle Routing Problem
Ivan Milinovi\'c, Leon Stjepan Uroi\'c, Marko {\DJ}urasevi\'c
https://arxiv.org/abs/2506.01065

Trilevel Memetic Algorithm for the Electric Vehicle Routing Problem
The Electric Vehicle Routing Problem (EVRP) extends the capacitated vehicle routing problem by incorporating battery constraints and charging stations, posing significant optimization challenges. This paper introduces a Trilevel Memetic Algorithm (TMA) that hierarchically optimizes customer sequences, route assignments, and charging station insertions. The method combines genetic algorithms with dynamic programming, ensuring efficient and high-quality solutions. Benchmark tests on WCCI2020 inst…

Vancouver BC is having its own No Kings rally right down by the US consulate on Pender. There is little space down there, so it's a pretty terrible spot for a gathering - ideally, the street would have been closed, particularly as bumping a vehicle up a curb and into the crowd would be simple - we had a deadly instance of that just last month.
Ironically, we do have a king here.

Very cool and very normal https://mastodon.social/@verge/114315519690612580

French drivers sue Tesla over Elon Musk's right-wing politics (Jordyn Dahl/Politico)
https://www.politico.eu/article/french-sue-tesla-elon-musks-politics-electric-vehicle-ev-europe-afd-courts/
http://www.memeorandum.com/250611/p74#a250611p74

Efficient Multi-Camera Tokenization with Triplanes for End-to-End Driving
Boris Ivanovic, Cristiano Saltori, Yurong You, Yan Wang, Wenjie Luo, Marco Pavone
https://arxiv.org/abs/2506.12251

Efficient Multi-Camera Tokenization with Triplanes for End-to-End Driving
Autoregressive Transformers are increasingly being deployed as end-to-end robot and autonomous vehicle (AV) policy architectures, owing to their scalability and potential to leverage internet-scale pretraining for generalization. Accordingly, tokenizing sensor data efficiently is paramount to ensuring the real-time feasibility of such architectures on embedded hardware. To this end, we present an efficient triplane-based multi-camera tokenization strategy that leverages recent advances in 3D ne…

Vaseline. Vaseline (or, indeed, lip balm) on the lenses works a treat. Causes no lasting damage but places the vehicle out of use for some time. https://www.theguardian.com/technology/2025/jun/10/uber-uk-trial-of-self…

"These vehicle homes sheltered dozens of working-class Latinx families, who could no longer afford the city’s soaring rents. Living in RVs was the only way many could keep their jobs in food service, janitorial work and construction while their children stayed enrolled in nearby schools.
"To city officials, it looked like homelessness. But residents didn’t see it that way. Living in RVs was a survival strategy—a way to stay housed, employed and near their communities."…

Real-World Deployment of a Lane Change Prediction Architecture Based on Knowledge Graph Embeddings and Bayesian Inference
M. Manzour, Catherine M. Elias, Omar M. Shehata, R. Izquierdo, M. A. Sotelo
https://arxiv.org/abs/2506.11925

Real-World Deployment of a Lane Change Prediction Architecture Based on Knowledge Graph Embeddings and Bayesian Inference
Research on lane change prediction has gained a lot of momentum in the last couple of years. However, most research is confined to simulation or results obtained from datasets, leaving a gap between algorithmic advances and on-road deployment. This work closes that gap by demonstrating, on real hardware, a lane-change prediction system based on Knowledge Graph Embeddings (KGEs) and Bayesian inference. Moreover, the ego-vehicle employs a longitudinal braking action to ensure the safety of both i…

Algorithmic Analysis of GTFS-RT vehicle position accuracy
Joshua Wong
https://arxiv.org/abs/2506.06479 https://arxiv.org/pdf/2506.064…

Algorithmic Analysis of GTFS-RT vehicle position accuracy
This paper presents three novel algorithms for calculating geodesic intersections on an ellipsoid. These algorithms are applied in a case study analyzing real-time transit data in California to assess vehicle position drift. The analysis reveals that while certain data anomalies can be corrected, large-scale discrepancies persist. The paper concludes by proposing a set of practical solutions that can be implemented by either data producers or consumers to significantly improve positional accura…

Spatially Consistent Air-to-Ground Channel Modeling with Probabilistic LOS/NLOS Segmentation
Evgenii Vinogradov, Abdul Saboor, Zhuangzhuang Cui, Aymen Fakhreddine
https://arxiv.org/abs/2506.12794

Spatially Consistent Air-to-Ground Channel Modeling with Probabilistic LOS/NLOS Segmentation
In this paper, we present a spatially consistent A2G channel model based on probabilistic LOS/NLOS segmentation to parameterize the deterministic path loss and stochastic shadow fading model. Motivated by the limitations of existing Unmanned Aerial Vehicle (UAV) channel models that overlook spatial correlation, our approach reproduces LOS/NLOS transitions along ground user trajectories in urban environments. This model captures environment-specific obstructions by means of azimuth and elevation…

Algorithmic Approaches to Enhance Safety in Autonomous Vehicles: Minimizing Lane Changes and Merging
Seyed Moein Abtahi, Akramul Azim
https://arxiv.org/abs/2506.15026

Algorithmic Approaches to Enhance Safety in Autonomous Vehicles: Minimizing Lane Changes and Merging
The rapid advancements in autonomous vehicle (AV) technology promise enhanced safety and operational efficiency. However, frequent lane changes and merging maneuvers continue to pose significant safety risks and disrupt traffic flow. This paper introduces the Minimizing Lane Change Algorithm (MLCA), a state-machine-based approach designed to reduce unnecessary lane changes, thereby enhancing both traffic safety and efficiency. The MLCA algorithm prioritizes maintaining lane stability unless saf…

Evaluation of "As-Intended" Vehicle Dynamics using the Active Inference Framework
Kazuharu Kidera, Takuma Miyaguchi, Hideyoshi Yanagisawa
https://arxiv.org/abs/2506.00035

Evaluation of "As-Intended" Vehicle Dynamics using the Active Inference Framework
We constructed a computational model of the driver's brain for steering tasks using the active inference framework, grounded in the free energy principle - a theory from computational neuroscience. This model enables quantitative estimation of how accurately the brain learns vehicle dynamics and performs appropriate steering, using a measure called variational free energy. Through driving simulator experiments, we observed strong correlations between variational free energy and both expert driv…

Bilevel Optimization for Improved Flexibility Aggregation Models of Electric Vehicle Fleets
Philipp H\"artel, Michael von Bonin
https://arxiv.org/abs/2506.04843

Bilevel Optimization for Improved Flexibility Aggregation Models of Electric Vehicle Fleets
Electric vehicle (EV) fleets are expected to become an increasingly important source of flexibility for power system operations. However, accurately capturing the flexibility potential of numerous and heterogeneous EVs remains a significant challenge. We propose a bilevel optimization formulation to enhance flexibility aggregations of electric vehicle fleets. The outer level minimizes scheduling deviations between the aggregated and reference EV units, while the inner level maximizes the aggreg…

Urban Discoveries 🏙️
都市发现 🏙️
📷 Pentax MX
🎞️Lucky SHD 400
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

Yiding Cao Geld mit PayPal.Me senden
Folgen Sie dem Link PayPal.Me/dingsterdingster und geben Sie den Betrag ein. Es ist bequem und sicher. Sie haben noch kein PayPal-Konto? Kein Problem.

Florida Governor Ron DeSantis has said Floridians have a right to hit protesters with their car if they need to "flee for your safety."
DeSantis was speaking on The Rubin Report on Wednesday when he said:
"We also have a policy that if you're driving on one of those streets and a mob comes and surrounds your vehicle,
and threatens you, you have a right to flee for your safety.
"And so if you drive off and you hit one of these people,
tha…

Ron DeSantis Says Floridians Have Right to Hit Protesters With Cars
"That's their fault for impinging on you," Florida's governor said.

R-CARLA: High-Fidelity Sensor Simulations with Interchangeable Dynamics for Autonomous Racing
Maurice Brunner, Edoardo Ghignone, Nicolas Baumann, Michele Magno
https://arxiv.org/abs/2506.09629

R-CARLA: High-Fidelity Sensor Simulations with Interchangeable Dynamics for Autonomous Racing
Autonomous racing has emerged as a crucial testbed for autonomous driving algorithms, necessitating a simulation environment for both vehicle dynamics and sensor behavior. Striking the right balance between vehicle dynamics and sensor accuracy is crucial for pushing vehicles to their performance limits. However, autonomous racing developers often face a trade-off between accurate vehicle dynamics and high-fidelity sensor simulations. This paper introduces R-CARLA, an enhancement of the CARLA si…

"Two lessons here: 1) Use a marker with a wider tip than a Sharpie, so it’ll be more visible, and 2a) if civilians are able to get right onto your armored vehicle to write graffiti, maybe this wasn’t the kind of militarized raid that you needed an armored truck for in the first place, or 2b) at the very least, your security cordon sucks."
**Minneapolis Says No Fascists, DHS Won't Deport And Kill Preschooler Yet. Your ICE Times Roundup**
https://www.wonkette.com/p/minneapolis-says-no-fascists-dhs

Watch out! Got a new vehicle accessory over here

Zero-Shot Scene Understanding with Multimodal Large Language Models for Automated Vehicles
Mohammed Elhenawy, Shadi Jaradat, Taqwa I. Alhadidi, Huthaifa I. Ashqar, Ahmed Jaber, Andry Rakotonirainy, Mohammad Abu Tami
https://arxiv.org/abs/2506.12232

Zero-Shot Scene Understanding with Multimodal Large Language Models for Automated Vehicles
Scene understanding is critical for various downstream tasks in autonomous driving, including facilitating driver-agent communication and enhancing human-centered explainability of autonomous vehicle (AV) decisions. This paper evaluates the capability of four multimodal large language models (MLLMs), including relatively small models, to understand scenes in a zero-shot, in-context learning setting. Additionally, we explore whether combining these models using an ensemble approach with majority…

Collaborative Last-Mile Delivery: A Multi-Platform Vehicle Routing Problem With En-route Charging
Sumbal Malik, Majid Khonji, Khaled Elbassioni, Jorge Dias
https://arxiv.org/abs/2505.23584

Collaborative Last-Mile Delivery: A Multi-Platform Vehicle Routing Problem With En-route Charging
The rapid growth of e-commerce and the increasing demand for timely, cost-effective last-mile delivery have increased interest in collaborative logistics. This research introduces a novel collaborative synchronized multi-platform vehicle routing problem with drones and robots (VRP-DR), where a fleet of $\mathcal{M}$ trucks, $\mathcal{N}$ drones and $\mathcal{K}$ robots, cooperatively delivers parcels. Trucks serve as mobile platforms, enabling the launching, retrieving, and en-route charging of…

Diver-Robot Communication Dataset for Underwater Hand Gesture Recognition
Igor Kvasi\'c, Derek Orbaugh Antillon, {\DH}ula Na{\dj}, Christopher Walker, Iain Anderson, Nikola Mi\v{s}kovi\'c
https://arxiv.org/abs/2506.08974

Diver-Robot Communication Dataset for Underwater Hand Gesture Recognition
In this paper, we present a dataset of diving gesture images used for human-robot interaction underwater. By offering this open access dataset, the paper aims at investigating the potential of using visual detection of diving gestures from an autonomous underwater vehicle (AUV) as a form of communication with a human diver. In addition to the image recording, the same dataset was recorded using a smart gesture recognition glove. The glove uses elastomer sensors and on-board processing to determ…

Truck in Ontario CA “Rolls Coal” (blows burning oil/fuel out of an illegal modification to their exhaust system)
A saga in 48 seconds, watch to the end
#California #LosAngelesProtests

Markov Regime-Switching Intelligent Driver Model for Interpretable Car-Following Behavior
Chengyuan Zhang, Cathy Wu, Lijun Sun
https://arxiv.org/abs/2506.14762

Markov Regime-Switching Intelligent Driver Model for Interpretable Car-Following Behavior
Accurate and interpretable car-following models are essential for traffic simulation and autonomous vehicle development. However, classical models like the Intelligent Driver Model (IDM) are fundamentally limited by their parsimonious and single-regime structure. They fail to capture the multi-modal nature of human driving, where a single driving state (e.g., speed, relative speed, and gap) can elicit many different driver actions. This forces the model to average across distinct behaviors, red…

Dodajemy jeszcze jeden system budowania, brachu! Z pewnością nie pożałujesz dodania jeszcze jednego systemu budowania!
Oczywiście, że próbują wepchnąć bajzel… znaczy, #Bazel.
https://github.com/libarchive/libar…

"Despite good-faith efforts by DSI [dense street imagery] providers to protect individual privacy through blurring faces and license plates, these measures fail to address broader privacy concerns. In this work, we find that increased data density and advancements in artificial intelligence enable harmful group membership inferences from supposedly anonymized data."
via @…

Privacy of Groups in Dense Street Imagery
Spatially and temporally dense street imagery (DSI) datasets have grown unbounded. In 2024, individual companies possessed around 3 trillion unique images of public streets. DSI data streams are only set to grow as companies like Lyft and Waymo use DSI to train autonomous vehicle algorithms and analyze collisions. Academic researchers leverage DSI to explore novel approaches to urban analysis. Despite good-faith efforts by DSI providers to protect individual privacy through blurring faces and l…

I could tell as I walked up to the area that they were not the vehicles of disabled drivers, since no disabled person would be able to get in or out of them. Today there was one vehicle parked in the disabled area – a new, expensive Jaguar, with no disabled placard displayed. It seems to me that people who are wealthy, and who buy fancy, expensive vehicles feel that since their wealth allows them to purchase expensive vehicles, that they are therefore entitled to park wherever they like.

TUM Teleoperation: Open Source Software for Remote Driving and Assistance of Automated Vehicles
Tobias Kerbl, David Brecht, Nils Gehrke, Nijinshan Karunainayagam, Niklas Krauss, Florian Pfab, Richard Taupitz, Ines Trautmannsheimer, Xiyan Su, Maria-Magdalena Wolf, Frank Diermeyer
https://arxiv.org/abs/2506.13933

TUM Teleoperation: Open Source Software for Remote Driving and Assistance of Automated Vehicles
Teleoperation is a key enabler for future mobility, supporting Automated Vehicles in rare and complex scenarios beyond the capabilities of their automation. Despite ongoing research, no open source software currently combines Remote Driving, e.g., via steering wheel and pedals, Remote Assistance through high-level interaction with automated driving software modules, and integration with a real-world vehicle for practical testing. To address this gap, we present a modular, open source teleoperat…

This https://arxiv.org/abs/2506.02576 has been replaced.
link: https://scholar.google.com/scholar?q=a

ADFormer: Aggregation Differential Transformer for Passenger Demand Forecasting
Passenger demand forecasting helps optimize vehicle scheduling, thereby improving urban efficiency. Recently, attention-based methods have been used to adequately capture the dynamic nature of spatio-temporal data. However, existing methods that rely on heuristic masking strategies cannot fully adapt to the complex spatio-temporal correlations, hindering the model from focusing on the right context. These works also overlook the high-level correlations that exist in the real world. Effectively …

AI-Driven Vehicle Condition Monitoring with Cell-Aware Edge Service Migration
Charalampos Kalalas, Pavol Mulinka, Guillermo Candela Belmonte, Miguel Fornell, Michail Dalgitsis, Francisco Paredes Vera, Javier Santaella S\'anchez, Carmen Vicente Villares, Roshan Sedar, Eftychia Datsika, Angelos Antonopoulos, Antonio Fern\'andez Ojea, Miquel Payaro

AI-Driven Vehicle Condition Monitoring with Cell-Aware Edge Service Migration
Artificial intelligence (AI) has been increasingly applied to the condition monitoring of vehicular equipment, aiming to enhance maintenance strategies, reduce costs, and improve safety. Leveraging the edge computing paradigm, AI-based condition monitoring systems process vast streams of vehicular data to detect anomalies and optimize operational performance. In this work, we introduce a novel vehicle condition monitoring service that enables real-time diagnostics of a diverse set of anomalies …

There is no "h" in "vehicle," Jethro.

Analyzing the performance of a V2X-enhanced braking system in real-world crash situations
Jan Zimmermann, J\"org M\"onnich, Michael Scherl, Ignacio Llatser, Florian Wildsch\"utte, Frank Hofmann
https://arxiv.org/abs/2506.10535

Analyzing the performance of a V2X-enhanced braking system in real-world crash situations
By using an automated braking system, such as the Automatic Emergency Brake (AEB), crashes can be avoided in situations where the driver is unaware of an imminent collision. However, conventional AEB systems detect potential collision adversaries with onboard sensor systems, such as radars and cameras, that may fail in non-line-of-sight situations. By leveraging vehicle-to-everything (V2X) communication, information regarding an approaching vehicle can be received by the ego vehicle at an early…

Spatiotemporal Prediction of Electric Vehicle Charging Load Based on Large Language Models
Hang Fan, Mingxuan Li, Jingshi Cui, Zuhan Zhang, Wencai Run, Dunnan Liu
https://arxiv.org/abs/2506.03728

Spatiotemporal Prediction of Electric Vehicle Charging Load Based on Large Language Models
The rapid growth of EVs and the subsequent increase in charging demand pose significant challenges for load grid scheduling and the operation of EV charging stations. Effectively harnessing the spatiotemporal correlations among EV charging stations to improve forecasting accuracy is complex. To tackle these challenges, we propose EV-LLM for EV charging loads based on LLMs in this paper. EV-LLM integrates the strengths of Graph Convolutional Networks (GCNs) in spatiotemporal feature extraction w…

Autonomous Vehicle Lateral Control Using Deep Reinforcement Learning with MPC-PID Demonstration
Chengdong Wu, Sven Kirchner, Nils Purschke, Alois C. Knoll
https://arxiv.org/abs/2506.04040

Autonomous Vehicle Lateral Control Using Deep Reinforcement Learning with MPC-PID Demonstration
The controller is one of the most important modules in the autonomous driving pipeline, ensuring the vehicle reaches its desired position. In this work, a reinforcement learning based lateral control approach, despite the imperfections in the vehicle models due to measurement errors and simplifications, is presented. Our approach ensures comfortable, efficient, and robust control performance considering the interface between controlling and other modules. The controller consists of the conventi…

Optimization of Robotic Liquid Handling as a Capacitated Vehicle Routing Problem
Guangqi Wu, Runzhong Wang, Connor W. Coley
https://arxiv.org/abs/2506.02795

Optimization of Robotic Liquid Handling as a Capacitated Vehicle Routing Problem
We present an optimization strategy to reduce the execution time of liquid handling operations in the context of an automated chemical laboratory. By formulating the task as a capacitated vehicle routing problem (CVRP), we leverage heuristic solvers traditionally used in logistics and transportation planning to optimize task execution times. As exemplified using an 8-channel pipette with individually controllable tips, our approach demonstrates robust optimization performance across different l…

Efficient Learning of Vehicle Controller Parameters via Multi-Fidelity Bayesian Optimization: From Simulation to Experiment
Yongpeng Zhao, Maik Pfefferkorn, Maximilian Templer, Rolf Findeisen
https://arxiv.org/abs/2506.08719

Efficient Learning of Vehicle Controller Parameters via Multi-Fidelity Bayesian Optimization: From Simulation to Experiment
Parameter tuning for vehicle controllers remains a costly and time-intensive challenge in automotive development. Traditional approaches rely on extensive real-world testing, making the process inefficient. We propose a multi-fidelity Bayesian optimization approach that efficiently learns optimal controller parameters by leveraging both low-fidelity simulation data and a very limited number of real-world experiments. Our approach significantly reduces the need for manual tuning and expensive fi…

I am keenly aware of others who are much more seriously impaired, & actually are, or can be quite disabled. I get angry when I see people who feel entitled do things like parking in disabled parking slots. They should be ashamed of themselves. The elderly, disabled woman who arrives who is capable of getting from her vehicle to the door, and getting onto the elevator, now has to park down in the main parking area with a long walk up to the building. That is impossible for her. What is she to do?

🚗 In #Frankreich brechen die Verkäufe von #Tesla im Mai um 67 % ein.
Es gab nur 721 #Neuzulassungen, so wenige wie seit fast drei Jahren nicht mehr. Trotz neuem Model Y und gegenteiliger …

Tesla Sales Plunge 67% to an Almost Three-Year Low in France
(Bloomberg) -- Tesla Inc.’s new-vehicle registrations fell further in France, undercutting Chief Executive Officer Elon Musk’s assertion last month that the ...

Photos and partial footage of an FSD-enabled Tesla sideswiping a parked vehicle and hitting a woman in November 2023 shows FSD's limits; the NHTSA is probing it (Bloomberg)
https://www.bloomberg.com/features/2025-tesla-full-self-driving-crash/…

Natura Urbana VII 🏡
城市自然 VII 🏡
📷 Nikon FE
🎞️Ilford FP4 Plus, expired 1995
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

Yiding Cao Geld mit PayPal.Me senden
Folgen Sie dem Link PayPal.Me/dingsterdingster und geben Sie den Betrag ein. Es ist bequem und sicher. Sie haben noch kein PayPal-Konto? Kein Problem.

Generate Realistic Test Scenes for V2X Communication Systems
An Guo, Xinyu Gao, Chunrong Fang, Haoxiang Tian, Weisong Sun, Yanzhou Mu, Shuncheng Tang, Lei Ma, Zhenyu Chen
https://arxiv.org/abs/2506.07419

Generate Realistic Test Scenes for V2X Communication Systems
Accurately perceiving complex driving environments is essential for ensuring the safe operation of autonomous vehicles. With the tremendous progress in deep learning and communication technologies, cooperative perception with Vehicle-to-Everything (V2X) technologies has emerged as a solution to overcome the limitations of single-agent perception systems in perceiving distant objects and occlusions. Despite the considerable advancements, V2X cooperative perception systems require thorough testin…

Occlusion-Aware Ground Target Tracking by a Dubins Vehicle Using Visibility Volumes
Collin Hague, Artur Wolek
https://arxiv.org/abs/2506.03400 https://

Occlusion-Aware Ground Target Tracking by a Dubins Vehicle Using Visibility Volumes
This paper considers the problem of tracking a point of interest (POI) moving along a known trajectory on the ground with an uncrewed aerial vehicle (UAV) modeled as a Dubins vehicle using a line-of-sight (LOS) sensor through an urban environment that may occlude the POI. A visibility volume (VV) encodes a time-varying, three-dimensional representation of the sensing constraints for a particular POI position. A constant-altitude, translating, and radially time-varying circular standoff orbit is…

Measuring and Minimizing Disturbance of Marine Animals to Underwater Vehicles
Levi Cai, Youenn J\'ez\'equel, T. Aran Mooney, Yogesh Girdhar
https://arxiv.org/abs/2506.11335

Measuring and Minimizing Disturbance of Marine Animals to Underwater Vehicles
Do fish respond to the presence of underwater vehicles, potentially biasing our estimates about them? If so, are there strategies to measure and mitigate this response? This work provides a theoretical and practical framework towards bias-free estimation of animal behavior from underwater vehicle observations. We also provide preliminary results from the field in coral reef environments to address these questions.

This https://arxiv.org/abs/2505.17879 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

LLM4SP: Large Language Models for Scatterer Prediction via Synesthesia of Machines
Guided by Synesthesia of Machines (SoM), the nonlinear mapping relationship between sensory and communication information serves as a powerful tool to enhance both the accuracy and generalization of vehicle-to-vehicle (V2V) multi-modal intelligent channel modeling (MMICM) in intelligent transportation systems (ITSs). To explore the general mapping relationship between physical environment and electromagnetic space, a new intelligent sensing-communication integration dataset, named V2V-M3, is co…

Multi-Level Damage-Aware Graph Learning for Resilient UAV Swarm Networks
Huan Lin, Chenguang Zhu, Lianghui Ding, Feng Yang
https://arxiv.org/abs/2506.09703

Multi-Level Damage-Aware Graph Learning for Resilient UAV Swarm Networks
Unmanned aerial vehicle (UAV) swarm networks leverage resilient algorithms to address communication network split issues and restore connectivity. However, existing graph learning-based resilient algorithms face over-aggregation and non-convergence problems caused by uneven and sparse topology under massive damage scenarios. To alleviate these problems, we propose a novel Multi-Level Damage-Aware Graph Learning (ML-DAGL) algorithm, which generates recovery trajectories by mining information fro…

Enhanced V2X Communication Using Game-Theory Based Adaptive MAC Protocols
Dhrumil Bhatt, Nirbhay Singhal
https://arxiv.org/abs/2506.09817 https://

Enhanced V2X Communication Using Game-Theory Based Adaptive MAC Protocols
This paper presents an enhanced Vehicle-to-Everything (V2X) communication system featuring adaptive Medium Access Control (MAC) using game theory. Our approach integrates dynamic transmission power control, dynamic beacon rates, contention window adaptation, and implicit acknowledgment mechanisms within a Manhattan-like grid-based mobility scenario. Simulations are conducted in a circular coverage area, incorporating refined signal propagation models and probabilistic vehicle mobility with boun…

This https://arxiv.org/abs/2411.03328 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Foundation Models for Rapid Autonomy Validation
We are motivated by the problem of autonomous vehicle performance validation. A key challenge is that an autonomous vehicle requires testing in every kind of driving scenario it could encounter, including rare events, to provide a strong case for safety and show there is no edge-case pathological behavior. Autonomous vehicle companies rely on potentially millions of miles driven in realistic simulation to expose the driving stack to enough miles to estimate rates and severity of collisions. To …

On the Linear Programming Model for Dynamic Stochastic Matching and Its Application on Pricing
Junlin Chen, Chiwei Yan, Hai Jiang
https://arxiv.org/abs/2506.09924

On the Linear Programming Model for Dynamic Stochastic Matching and Its Application on Pricing
Important pricing problems in centralized matching markets -- such as carpooling and food delivery platforms -- often exhibit a bi-level structure. At the upper level, the platform sets prices for different types of agents (e.g., riders with various origins and destinations, or delivery orders from diverse restaurants to customer locations). The lower level then matches converted agents to minimize operational costs, such as pooling riders with similar itineraries into the same vehicle or conso…

Integer-Clustering Optimization of Hydrogen and Battery EV Fleets Considering DERs
Sijia Geng, Thomas Lee, Dharik Mallapragada, Audun Botterud
https://arxiv.org/abs/2506.09388

Integer-Clustering Optimization of Hydrogen and Battery EV Fleets Considering DERs
Electrified transportation leads to a tighter integration between transportation and energy distribution systems. In this work, we develop scalable optimization models to co-design hydrogen and battery electric vehicle (EV) fleets, distributed energy resources, and fast-charging and hydrogen-fueling infrastructure to efficiently meet transportation demands. A novel integer-clustering formulation is used for optimizing fleet-level EV operation while maintaining accurate individual vehicle dispat…

This https://arxiv.org/abs/2502.20817 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Learning-Based Leader Localization for Underwater Vehicles With Optical-Acoustic-Pressure Sensor Fusion
Underwater vehicles have emerged as a critical technology for exploring and monitoring aquatic environments. The deployment of multi-vehicle systems has gained substantial interest due to their capability to perform collaborative tasks with improved efficiency. However, achieving precise localization of a leader underwater vehicle within a multi-vehicle configuration remains a significant challenge, particularly in dynamic and complex underwater conditions. To address this issue, this paper pre…

Joint Routing and Control Optimization in VANET
Chen Huang, Dingxuan Wang, Ronghui Hou
https://arxiv.org/abs/2506.08038 https://arxiv…

Joint Routing and Control Optimization in VANET
In this paper, we introduce DynaRoute, an adaptive joint optimization framework for dynamic vehicular networks that simultaneously addresses platoon control and data transmission through trajectory-aware routing and safety-constrained vehicle coordination. DynaRoute guarantees continuous vehicle movement via platoon safety control with optimizing transmission paths through real-time trajectory prediction and ensuring reliable data. Our solution achieves three key objectives: (1) maintaining pla…

Improving Multi-Vehicle Perception Fusion with Millimeter-Wave Radar Assistance
Zhiqing Luo, Yi Wang, Yingying He, Wei Wang
https://arxiv.org/abs/2506.00837

Improving Multi-Vehicle Perception Fusion with Millimeter-Wave Radar Assistance
Cooperative perception enables vehicles to share sensor readings and has become a new paradigm to improve driving safety, where the key enabling technology for realizing this vision is to real-time and accurately align and fuse the perceptions. Recent advances to align the views rely on high-density LiDAR data or fine-grained image feature representations, which however fail to meet the requirements of accuracy, real-time, and adaptability for autonomous driving. To this end, we present MMatch,…

Invariant Extended Kalman Filter for Autonomous Surface Vessels with Partial Orientation Measurements
Derek Benham, Easton Potokar, Joshua G. Mangelson
https://arxiv.org/abs/2506.10850

Invariant Extended Kalman Filter for Autonomous Surface Vessels with Partial Orientation Measurements
Autonomous surface vessels (ASVs) are increasingly vital for marine science, offering robust platforms for underwater mapping and inspection. Accurate state estimation, particularly of vehicle pose, is paramount for precise seafloor mapping, as even small surface deviations can have significant consequences when sensing the seafloor below. To address this challenge, we propose an Invariant Extended Kalman Filter (InEKF) framework designed to integrate partial orientation measurements. While con…

This https://arxiv.org/abs/2410.05740 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Learning to Drift in Extreme Turning with Active Exploration and Gaussian Process Based MPC
Extreme cornering in racing often leads to large sideslip angles, presenting a significant challenge for vehicle control. Conventional vehicle controllers struggle to manage this scenario, necessitating the use of a drifting controller. However, the large sideslip angle in drift conditions introduces model mismatch, which in turn affects control precision. To address this issue, we propose a model correction drift controller that integrates Model Predictive Control (MPC) with Gaussian Process R…

Robust and Safe Multi-Agent Reinforcement Learning Framework with Communication for Autonomous Vehicles
Keshawn Smith, Zhili Zhang, H M Sabbir Ahmad, Ehsan Sabouni, Maniak Mondal, Song Han, Wenchao Li, Fei Miao
https://arxiv.org/abs/2506.00982

Robust and Safe Multi-Agent Reinforcement Learning Framework with Communication for Autonomous Vehicles
Deep multi-agent reinforcement learning (MARL) has been demonstrated effectively in simulations for many multi-robot problems. For autonomous vehicles, the development of vehicle-to-vehicle (V2V) communication technologies provide opportunities to further enhance safety of the system. However, zero-shot transfer of simulator-trained MARL policies to hardware dynamic systems remains challenging, and how to leverage communication and shared information for MARL has limited demonstrations on hardw…

Nonlinear Oscillatory Response of Automated Vehicle Car-following: Theoretical Analysis with Traffic State and Control Input Limits
Sixu Li, Yang Zhou
https://arxiv.org/abs/2505.24029

Nonlinear Oscillatory Response of Automated Vehicle Car-following: Theoretical Analysis with Traffic State and Control Input Limits
This paper presents a framework grounded in the theory of describing function (DF) and incremental-input DF to theoretically analyze the nonlinear oscillatory response of automated vehicles (AVs) car-following (CF) amidst traffic oscillations, considering the limits of traffic state and control input. While prevailing approaches largely ignore these limits (i.e., saturation of acceleration/deceleration and speed) and focus on linear string stability analysis, this framework establishes a basis …

MOMAV: A highly symmetrical fully-actuated multirotor drone using optimizing control allocation
Marco Ruggia
https://arxiv.org/abs/2506.08868 https://

MOMAV: A highly symmetrical fully-actuated multirotor drone using optimizing control allocation
MOMAV (Marco's Omnidirectional Micro Aerial Vehicle) is a multirotor drone that is fully actuated, meaning it can control its orientation independently of its position. MOMAV is also highly symmetrical, making its flight efficiency largely unaffected by its current orientation. These characteristics are achieved by a novel drone design where six rotor arms align with the vertices of an octahedron, and where each arm can actively rotate along its long axis. Various standout features of MOMAV are…

A Survey on the Role of Artificial Intelligence and Machine Learning in 6G-V2X Applications
Donglin Wang, Anjie Qiu, Qiuheng Zhou, Hans D. Schotten
https://arxiv.org/abs/2506.09512

A Survey on the Role of Artificial Intelligence and Machine Learning in 6G-V2X Applications
The rapid advancement of Vehicle-to-Everything (V2X) communication is transforming Intelligent Transportation Systems (ITS), with 6G networks expected to provide ultra-reliable, low-latency, and high-capacity connectivity for Connected and Autonomous Vehicles (CAVs). Artificial Intelligence (AI) and Machine Learning (ML) have emerged as key enablers in optimizing V2X communication by enhancing network management, predictive analytics, security, and cooperative driving due to their outstanding p…

Diffusion Models for Safety Validation of Autonomous Driving Systems
Juanran Wang, Marc R. Schlichting, Harrison Delecki, Mykel J. Kochenderfer
https://arxiv.org/abs/2506.08459

Diffusion Models for Safety Validation of Autonomous Driving Systems
Safety validation of autonomous driving systems is extremely challenging due to the high risks and costs of real-world testing as well as the rarity and diversity of potential failures. To address these challenges, we train a denoising diffusion model to generate potential failure cases of an autonomous vehicle given any initial traffic state. Experiments on a four-way intersection problem show that in a variety of scenarios, the diffusion model can generate realistic failure samples while capt…

This https://arxiv.org/abs/2409.12949 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

A Learning-based Quadcopter Controller with Extreme Adaptation
This paper introduces a learning-based low-level controller for quadcopters, which adaptively controls quadcopters with significant variations in mass, size, and actuator capabilities. Our approach leverages a combination of imitation learning and reinforcement learning, creating a fast-adapting and general control framework for quadcopters that eliminates the need for precise model estimation or manual tuning. The controller estimates a latent representation of the vehicle's system parameters …

Self driving algorithm for an active four wheel drive racecar
Gergely Bari, Laszlo Palkovics
https://arxiv.org/abs/2506.06077 https://

Self driving algorithm for an active four wheel drive racecar
Controlling autonomous vehicles at their handling limits is a significant challenge, particularly for electric vehicles with active four wheel drive (A4WD) systems offering independent wheel torque control. While traditional Vehicle Dynamics Control (VDC) methods use complex physics-based models, this study explores Deep Reinforcement Learning (DRL) to develop a unified, high-performance controller. We employ the Proximal Policy Optimization (PPO) algorithm to train an agent for optimal lap tim…