The official autonomous racing team of the University of Modena and Reggio Emilia
OO，Europe
We can't wait to be back at Las Vegas Motor Speedway to be a part of such an amazing event. See you in Vegas!???
Get ready for the ultimate autonomous showdown at CES 2025! The IAC returns to Las Vegas Motor Speedway on January 9 with 3+ autonomous racecars simultaneously on track going for an iconic win. ????? Read more about this high speed innovation in the Forbes article below?? https://lnkd.in/gFYVM23y #CES2025 #AutonomousRacing #IAC
Last month we took part in the last Indy Autonomous Challenge race of the year at the Racing Capital of the World, Indianapolis Motor Speedway, achieving some great results. ?? We reached an astonishing top speed of 286 kmh [ 177 mph ] and an average in a single lap of 264 kmh [ 163 mph ] in the time trial, which assured us the qualification to the passing competition. After winning a couple of head-to-head matches we made it to the final, performing an incredible duel against PoliMOVE Autonomous Racing Team which allowed both of us to push our cars to the limit and during which we reached the highest overtaking speeds in the history of autonomous driving, proving once again the outstanding level that this competition has come to. We take the chance to give a shout-out to them for the great results achieved, being grateful to share the top steps of the podium with another Italian team! Apart from these amazing results, our greatest achievement has surely been in the pre-race tests. We have been able to complete more than 1,000 laps, which means more than 3,000 km covered without an accident and with a perfectly working autonomous driving system. Many congratulations also to Cavalier Autonomous Racing for winning the time trial, as well as to all the other teams who participated in the competition. Huge thanks to Università degli Studi di Modena e Reggio Emilia and Hipert for the constant support and hard work.? Thanks also to our technical sponsor Claytex whose support was invaluable in developing our multibody simulator. Additionally, we appreciate MegaRide - applied vehicle research for their expert consultancy on tire dynamics analysis. With this event we conclude the 2024 season, enjoying the great steps forward made till now and improving from every useful lesson learned during this amazing experience, that will serve as fuel for our future challenges. As we head into the next season, our ambition to reach that top position remains stronger than ever! ??? #autonomous #autonomousdriving #autonomousvehicles #indyautonomouschallenge
Can’t wait to be there!
What can you expect in Season 2? The unexpected. Strap in, because this season we're going all out. #A2RL #AutonomousRacing #Season2
?? ?????????????????????????? ???????? ?????????????? ???? ????????-?????????? ???????????????? ??? Race control is not only essential for the safe and efficient operation of autonomous races but also has significant potential for real-world applications. The principles and technologies used in race control can be applied to traffic management for on-road autonomous vehicles. ?? ?? By utilizing centralized control systems, we can enhance road safety, manage traffic flow, and respond to emergencies more effectively. ?? This approach could revolutionize how cities handle autonomous vehicle integration, leading to smarter, safer, and more efficient transportation systems ???. ?? Continue reading to find out how this works! ??/ ???????? ???? ???????? ??????????????? ??♂? In high-speed autonomous scenarios like the competition organized by the Indy Autonomous Challenge, race control acts as the digital equivalent of traditional flag signals. These commands guide the autonomous vehicles on how to operate under various track conditions, ensuring safety and efficiency. ??/ ?????? ???? ???????? ?????????????? ??????????????????? ?? Race control is crucial for: ? ????????????: Remotely stopping vehicles, shutting down engines, and controlling speeds in hazardous situations. ?? ????????????????????: Setting maximum speed limits to ensure safe operations. ?? ?????????????????? ????????????????: Activating brakes and disabling systems in critical scenarios. ??/ ?????? ???? ???? ?????????????? ????????? ?? We utilize Marelli’s Race Control tools, featuring: ?? ?????????????????????? ?????????? ????????????: Marelli’s advanced radio technology ensures robust communication with any cellular network, enabling global connectivity. ?? ????????-???????? ??????????????????: Continuous monitoring of data such as speed, position, and system status allows race control to make informed decisions. ??? ?????????????????????? ?????????????? ??????????????????: A comprehensive interface for monitoring and managing all vehicles from a single point. ??? ???????????? ??????????????????: Multiple safety layers handle everything from minor adjustments to full emergency shutdowns, ensuring maximum safety. Stay tuned for more insights into the world of high-speed autonomy as we rev up our practice for the Indy Autonomous Challenge at the Indianapolis Motor Speedway on September 6th, 2024. ?? Learn more: https://lnkd.in/gX6wMjnP #IndyAutonomousChallenge #RaceControl #AutonomousVehicles #Innovation #Safety #Marelli #HighSpeedAutonomy
I am glad to share with you all my Ph.D. dissertation entitled "Model Predictive Planning and Control for Autonomous Racing, from HPC to Embedded Platforms". Link ??: https://lnkd.in/dpNJc9Yx In the thesis, I sum up the work I did in these three years of my Ph.D. in Mathematics and Computer Science at Università degli Studi di Modena e Reggio Emilia and Università degli Studi di Parma during my participation in the Indy Autonomous Challenge. I extended what MPC-based solutions have been capable of achieving in recent years for what concerns path tracking at the limit of handling in autonomous sportscars. In particular, I demonstrated how this approach behaves in a fully autonomous racecar under model mismatch and how it is extremely accurate with a correct model fitting and the proper integration of a more detailed model. Furthermore, I built the baseline for a mixed approach for multivehicle autonomous racing exploiting model-based planning and control keeping the computational time low thanks to the combination of a simple heuristic to find the feasible space available to be used as constraints in the optimization problem. Can't wait to extend more this work and see it running again in a fully autonomous racecar, but this time even closer to the limits! I would like to thank prof. Marko Bertogna for his trust in me and all the opportunities he provided me in these years. Thanks also to Alexander Liniger for his immense support and the knowledge (and code) he shared with me. Thanks also to Basilio Lenzo for his review. Finally, thanks to the Unimore Racing team and the Indy Autonomous Challenge crew. Thanks also to Hipert ,Claytex and MegaRide - applied vehicle research for their technical collaboration and support. #autonomous #racing #mpc
Are you interested in a low-cost and open-source simulation platform to test planning and control algorithms for #Autonomous #Racing? In "A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data", we present a simulation platform based on Assetto Corsa, with both OpenGym and ROS2 interfaces and a benchmark of different learning-based methods and a more classical solution as the Model Predictive Controller (MPC) used for the previous races of the Indy Autonomous Challenge by Unimore Racing. Hopefully, this could be the initial step of a more detailed analysis and benchmarking of the state-of-the-art autonomous racing agents and the battle between AI and human race drivers. Link to the repo: https://lnkd.in/dH2xYWJu Link to the preprint : https://lnkd.in/dWxvhWqs
In #motorsport, both humans and autonomous driving algorithms push the boundaries: achieving more performance in less training time! Technische Universit?t Graz, UC San Diego, Università degli Studi di Modena e Reggio Emilia, and Know Center have recently collaborated to push the boundaries of autonomous racing. Lots of fun collaborating with Nicklas Hansen, Ayoub Raji, Nicola Musiu, Marko Bertogna, Eduardo Veas, and Xiaolong Wang on our autonomous driving project! ???? This work aims to push the limits of #automation in motorsports, enabling the simulation of various cars and tracks with a driver model capable of handling the car like a professional driver. We released a cutting-edge racing simulation platform based on the racing simulator #AssettoCorsa KUNOS Simulazioni, featuring reinforcement learning, imitation learning, and MPC and a comprehensive dataset from human drivers to train our models and compare these approaches against human performance. ?? We look forward to seeing what the learning, control, AI, and autonomous racing communities will use our work for! ?? Find out more and access our publicly released code, environment, benchmarks, datasets: https://lnkd.in/gyxp4fiP ?? Paper: https://lnkd.in/gEXPZMXG #racing #AI #racingdriver #automotivefuture #AutonomousDriving #ReinforcementLearning #AssettoCorsa #LearningFromDemonstration #MPCControl
Check out our latest research paper! Thanks to the integration of LiDAR Odometry and a Pacejka Model we could estimate in real-time the sideslip angle of our Dallara AV-21 during the Indy Autonomous Challenge events at Autodromo Nazionale Monza and Texas Motor Speedway! Congratulations to Alessandro Toschi, the coauthors, and the whole team!
Our paper, "Guess the Drift with LOP-UKF: LiDAR Odometry and Pacejka Model for Real-Time Racecar Sideslip Estimation," has been accepted at the 35th IEEE Intelligent Vehicles Symposium (IEEE IV 2024)! This is a significant step in Unimore Racing's research into enhancing safety and performance for autonomous racing through innovative techniques. ?? With great excitement, I announce that I'll present our findings in the poster session on Monday, June 3, 2024, from 10:50 AM to 12:40 PM in the Yeongsil + Eorimok Rooms. If you are at the symposium, come by to discuss our study and gain insights into our new approach! ?? Our study introduces the LOP-UKF method, which integrates LiDAR Odometry with the Pacejka tire model predictions, employing an Unscented Kalman Filter for robust estimation of the sideslip angle. Our tests with the Dallara AV-21 during the Indy Autonomous Challenge have shown promising results in real-world racing scenarios, in different grip conditions of both road courses and oval speedways. ?? Preprint is now available for those interested in the technical details and potential applications. Read the full paper here: https://lnkd.in/dwEdwDx4 A huge thank you to all the co-authors for their contribution Nicola Musiu Francesco Gatti Ayoub Raji Francesco Amerotti Micaela Verucchi Marko Bertogna. #IEEEIV2024 #IndyAutonomousChallenge #research #innovation #racing #motorsport #selfdrvingcars #autonomousdriving #autonomousvehicles
Excited to be back in a few months to where it all began 3 years ago - Racing in ovals once again but with more experience at Temple of Speed - Indy Autonomous Challenge at Indianapolis Motor Speedway! #autonomous #racing #driverlesscars #IAC
?? ?? The Indy Autonomous Challenge is making a return to the Indianapolis Motor Speedway on September 6, 2024! ???? This historic event will feature a head-to-head race of the world's fastest autonomous racecars, driven by AI software developed by 10 teams from 18 top universities across the globe. ?? In October 2021, IAC organized the world's first head-to-head autonomous racing competition at IMS. Since then, the IAC and its university teams have set multiple records for high-speed ground-based autonomy, including 9000 miles of autonomous racing! ?? The upcoming race, held in partnership with the Indiana Economic Development Corporation, will feature the best minds in autonomous vehicle technology. It's not just a race, but a showcase of how AI drivers can safely navigate high speeds, revolutionizing future mobility and supply chain logistics. ?? The race day will include interactive events, including an Innovation Paddock, a Future Mobility Summit, and a STEM Zone to inspire the next generation of leaders and innovators. ?? Learn more: https://lnkd.in/gX6wMjnP ?? Get tickets: https://lnkd.in/gEEum66E
Oops.. we did it again: lost the glory in the last lap! Last week, our team Unimore Racing participated to the AbuDhabi Autonomous Racing League, an incredible showdown of technology culminated in Saturday's 2.25M$ autonomous race. The car was simply amazing. Kudos to ASPIRE that managed assembling it in record times. It was delivered to the teams just a few weeks before the racing event. Since then, our car always got the fastest lap, until the trials, where we got the 2nd starting position in the Grand Finale, between our friends of Milan and Munich. I wouldn't recommend being in a sandwich between PoliMOVE Autonomous Racing Team and FTM Institute of Automotive Technology TUM, incredible teams that are never afraid of hitting the full throttle. We had to attack Milan, while defending from Munich. Try to do it without sending any command to your car, having to pre-program everything beforehand. Easy, ain't it? Well, it turns out PoliMOVE spins, and our car manages to safely overtake them. Detection and emergency maneuvering around the spinning car ran amazingly. We are leading over our german friends with a one minute gap. I start wondering how can we lose it this time. We ask permission to lap Constructor University stopped in the main straight. Permission denied by race control. Cars sent back to boxes, neutralizing all time gaps. We start smelling bad luck. Race restarts with us in leading over TUM, that has additional hp thanks to the push-to-pass option allowed to followers. We manage keeping the lead, setting the best time in the first sector. Car is stable, ready to give some good show to the public with TUM, when suddenly our car decelerates and stops. TUM keeps its racing line and gets the victory in the same lap. History repeating like in the first historic Indy Autonomous Challenge race in Indianapolis, when we also stopped in the last lap after setting the best time in the final. Back then, it was a stupid 1M$ bug in the number of laps. This time, a HW problem beyond our control: we suddenly lost all odometry sources (IMU, GPS, GPU, wheels, Kistler). As we did not yet find a solution to drive a blind car, we decelerate until a safe stop. Victory fading away. I am incredibly proud of the team. Fastest lap, sectors and highest speed in the final. You guys are amazing, and it was heartbreaking seeing your sadness after the race. Victory may or may not come, but what you achieved with limited resources will stay with you forever, witnessing your value and your passion. And I am honestly really happy for our friends at TUM. Kudos to Markus Lienkamp Johannes Betz and their amazing team. They deserve the glory. This is the beauty of this circus: hard but fair competition. A bit of a pity seeing EU teams struggling to find sponsors and funds, while they keep leading this incredibly difficult race. This tells you something about EU. Hope we will wake up and the trend will change. https://lnkd.in/dhDYud8U
So proud of you guys!!! Unimore Racing Università degli Studi di Modena e Reggio Emilia Alessandro Toschi Ayoub Raji Davide Malvezzi Francesco Prignoli Francesko Hyso Alessandro Canossa Michele Pestarino Nicola Musiu Maria Vittoria Cavicchioli Federico Sacco Pietro Musso Eugenio Mascaro Niccolò Enrico Marcati Silvia Severi Francesco Amerotti Giovanni Lambertini Andrea Bernardi Francesco Gatti Micaela Verucchi Massimiliano Bosi Paolo Falcone Luca Bartoli Fabio Bagni Francesco Moretti Girolamo Oddo Valentina La Gamba Matteo Pini