Current research in semantic bird's-eye view segmentation for autonomous driving focuses solely on optimizing neural network models using a single dataset, typically nuScenes. This practice leads to the development of highly specialized models that may fail when faced with different environments or sensor setups, a problem known as domain shift. In this paper, we conduct a comprehensive cross-dataset evaluation of state-of-the-art BEV segmentation models to assess their performance across different training and testing datasets and setups, as well as different semantic categories. We investigate the influence of different sensors, such as cameras and LiDAR, on the models' ability to generalize to diverse conditions and scenarios. Additionally, we conduct multi-dataset training experiments that improve models' BEV segmentation performance compared to single-dataset training. Our work addresses the gap in evaluating BEV segmentation models under cross-dataset validation. And our findings underscore the importance of enhancing model generalizability and adaptability to ensure more robust and reliable BEV segmentation approaches for autonomous driving applications. The code for this paper available at https://github.com/manueldiaz96/beval .

This paper aims to provide a quick review of the methods including the technologies in detail that are currently reported in industry and academia. Specifically, this paper reviews the end-to-end planning, including Tesla FSD V12, Momenta 2023, Horizon Robotics 2023, Motional RoboTaxi 2022, Woven Planet (Toyota): Urban Driver, and Nvidia. In addition, we review the state-of-the-art academic studies that investigate end-to-end planning of autonomous driving. This paper provides readers with a concise structure and fast learning of state-of-the-art end-to-end planning for 2022-2023. This article provides a meaningful overview as introductory material for beginners to follow the state-of-the-art end-to-end planning of autonomous driving in industry and academia, as well as supplementary material for advanced researchers.

At Woven Planet Level 5, we're using machine learning (ML) to build an autonomous driving system that improves as it observes more human driving. This is based on our Autonomy 2.0 approach, which leverages machine learning and data to solve the complex task of driving safely. This is unlike traditional systems, where engineers hand-design rules for every possible driving event. Last year, we took a critical step in delivering on Autonomy 2.0 by using an ML model to power our motion planner, the core decision-making module of our self-driving system. We saw the ML Planner's performance improve as we trained it on more human driving data.

Woven Planet is building the safest mobility in the world. A subsidiary of Toyota, Woven Planet innovates and invests in new technologies, software, and business models that transform how we live, work and move. With a focus on automated driving, smart cities, robotics and more, we build on Toyota's legacy of trust and safety to deliver mobility solutions for all. For nearly a century, Toyota has been delivering products and services that improve lives. Automation that originated to increase the efficiency of daily activities has evolved into the safe, reliable, connected automobiles we enjoy and depend on today.

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Woven Planet is building the safest mobility in the world. A subsidiary of Toyota, Woven Planet innovates and invests in new technologies, software, and business models that transform how we live, work and move. With a focus on automated driving, smart cities, robotics and more, we build on Toyota's legacy of trust and safety to deliver mobility solutions for all. For nearly a century, Toyota has been delivering products and services that improve lives. Automation that originated to increase the efficiency of daily activities has evolved into the safe, reliable, connected automobiles we enjoy and depend on today.

Woven Planet is building the safest mobility in the world. A subsidiary of Toyota, Woven Planet innovates and invests in new technologies, software, and business models that transform how we live, work and move. With a focus on automated driving, smart cities, robotics and more, we build on Toyota's legacy of trust and safety to deliver mobility solutions for all. For nearly a century, Toyota has been delivering products and services that improve lives. Automation that originated to increase the efficiency of daily activities has evolved into the safe, reliable, connected automobiles we enjoy and depend on today.

Woven Planet is building the safest mobility in the world. A subsidiary of Toyota, Woven Planet innovates and invests in new technologies, software, and business models that transform how we live, work and move. With a focus on automated driving, smart cities, robotics and more, we build on Toyota's legacy of trust and safety to deliver mobility solutions for all. For nearly a century, Toyota has been delivering products and services that improve lives. Automation that originated to increase the efficiency of daily activities has evolved into the safe, reliable, connected automobiles we enjoy and depend on today.

Woven Planet is a software-first subsidiary of Toyota whose vision is to create safe mobility of people, goods, and information that everyone can enjoy and trust. Level 5, part of Woven Planet, is developing self-driving technology using a state-of-the-art machine-learned approach. Our goal is to deliver advanced and self-driving capabilities to personally-owned and mobility-as-a-service vehicles to improve transportation on a global scale. As part of Woven Planet, Level 5 has the backing of one of the world's largest automakers and the opportunity for near-term product impact and revenue -- a combination rarely seen in the AV industry. Level 5 is looking for doers and creative problem solvers to join us in improving mobility for everyone with self-driving technology.

Woven Planet is a software-first subsidiary of Toyota whose vision is to create safe mobility of people, goods, and information that everyone can enjoy and trust. Level 5, part of Woven Planet, is developing self-driving technology using a state-of-the-art machine-learned approach. Our goal is to deliver advanced and self-driving capabilities to personally-owned and mobility-as-a-service vehicles to improve transportation on a global scale. As part of Woven Planet, Level 5 has the backing of one of the world's largest automakers and the opportunity for near-term product impact and revenue -- a combination rarely seen in the AV industry. Level 5 is looking for doers and creative problem solvers to join us in improving mobility for everyone with self-driving technology.