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Tesla is starting to release a new Full Self-Driving (FSD) Beta software update that includes many high-level changes that should positively impact performance.

FSD Beta enables Tesla vehicles to drive autonomously to a destination entered in the car’s navigation system, but the driver needs to remain vigilant and ready to take control at all times.

Since the responsibility lies with the driver and not Tesla’s system, it is still considered a level two driver-assist system despite its name. It has been sort of a “two steps forward, one step back” type of program, as some updates have seen regressions in terms of driving capabilities.

Tesla has been frequently releasing new software updates to the FSD Beta program and adding more owners to it.

The company now has over 100,000 people in the FSD Beta program and plans to expand it to everyone who buys access in North America by the end of the year through a few more software updates to refine the system.

Considering we are already in November and it generally takes at least a month for Tesla to deliver a new FSD Beta update, we expect Tesla is one or two updates away from the promised wider release.

Today, the automaker has started pushing a new FSD Beta update (v10.69.3) to employees for internal testing, which generally means that it will expand to beta testers in the customer fleet soon.

According to the release notes below, the update doesn’t include any new features, but it includes a lot of high-level updates to Tesla’s neural nets to improve the overall performance of the system.

Tesla Full Self-Driving Beta Release Notes v10.69.3 Release Notes via Not a Tesla App:

– Upgraded the Object Detection network to photon count video streams and retrained all parameters with the latest autolabeled datasets (with a special emphasis on low visibility scenarios).

– Improved the architecture for better accuracy and latency, higher recall of far away vehicles, lower velocity error of crossing vehicles by 20%, and improved VRU precision by 20%.

– Converted the VRU Velocity network to a two-stage network, which reduced latency and improved crossing pedestrian velocity error by 6%.

– Converted the non-VRU Attributes network to a two-stage network, which reduced latency, reduced incorrect lane assignment of crossing vehicles by 45%, and reduced incorrect parked predictions by 15%.

– Reformulated the autoregressive Vector Lanes grammar to improve the precision of lanes by 9.2%, recall of lanes by 18.7%, and recall of forks by 51.1%. Includes a full network update where all components were retrained with 3.8x the amount of data.

– Added a new “road markings” module to the Vector Lanes neural network which improves lane topology error at intersections by 38.9%.

– Upgraded the Occupancy Network to align with road surface instead of ego for improved detection stability and improved recall at hill crest.

– Reduced runtime of candidate trajectory generation by approximately 80% and improved smoothness by distilling an expensive trajectory optimization procedure into a lightweight planner neural network.

– Improved decision-making for short-deadline lane changes around gores by richer modeling of the trade-off between going off-route versus trajectory required to drive through the gore region.

– Reduced false slowdowns for pedestrians near crosswalks by using a better model for the kinematics of the pedestrian.

– Added control for more precise object geometry as detected by the general occupancy network.

– Improved control for vehicles cutting out of our desired path by better modeling of their turning/lateral maneuvers thus avoiding unnatural slowdowns.

– Improved longitudinal control while offsetting around static obstacles by searching over feasible vehicle motion profiles.

– Improved longitudinal control smoothness for in-lane vehicles during high relative velocity scenarios by also considering relative acceleration in the trajectory optimization.

– Reduced best-case object photon-to-control system latency by 26% through adaptive planner scheduling, restructuring of trajectory selection, and parallelizing perception compute. This allows us to make quicker decisions and improves reaction time.

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Europe’s wind power hits 20%, but 3 challenges stall progress

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Europe’s wind power hits 20%, but 3 challenges stall progress

Wind energy powered 20% of all electricity consumed in Europe (19% in the EU) in 2024, and the EU has set a goal to grow this share to 34% by 2030 and more than 50% by 2050.

To stay on track, the EU needs to install 30 GW of new wind farms annually, but it only managed 13 GW in 2024 – 11.4 GW onshore and 1.4 GW offshore. This is what’s holding the EU back from achieving its wind growth goals.

Three big problems holding Europe’s wind power back

Europe’s wind power growth is stalling for three key reasons:

Permitting delays. Many governments haven’t implemented the EU’s new permitting rules, making it harder for projects to move forward.

Grid connection bottlenecks. Over 500 GW(!) of potential wind capacity is stuck in grid connection queues.

Slow electrification. Europe’s economy isn’t electrifying fast enough to drive demand for more renewable energy.

Brussels-based trade association WindEurope CEO Giles Dickson summed it up: “The EU must urgently tackle all three problems. More wind means cheaper power, which means increased competitiveness.”

Permitting: Germany sets the standard

Permitting remains a massive roadblock, despite new EU rules aimed at streamlining the process. In fact, the situation worsened in 2024 in many countries. The bright spot? Germany. By embracing the EU’s permitting rules — with measures like binding deadlines and treating wind energy as a public interest priority — Germany approved a record 15 GW of new onshore wind in 2024. That’s seven times more than five years ago.

If other governments follow Germany’s lead, Europe could unlock the full potential of wind energy and bolster energy security.

Grid connections: a growing crisis

Access to the electricity grid is now the biggest obstacle to deploying wind energy. And it’s not just about long queues — Europe’s grid infrastructure isn’t expanding fast enough to keep up with demand. A glaring example is Germany’s 900-megawatt (MW) Borkum Riffgrund 3 offshore wind farm. The turbines are ready to go, but the grid connection won’t be in place until 2026.

This issue isn’t isolated. Governments need to accelerate grid expansion if they’re serious about meeting renewable energy targets.

Electrification: falling behind

Wind energy’s growth is also tied to how quickly Europe electrifies its economy. Right now, electricity accounts for just 23% of the EU’s total energy consumption. That needs to jump to 61% by 2050 to align with climate goals. However, electrification efforts in key sectors like transportation, heating, and industry are moving too slowly.

European Commission president Ursula von der Leyen has tasked Energy Commissioner Dan Jørgensen with crafting an Electrification Action Plan. That can’t come soon enough.

More wind farms awarded, but challenges persist

On a positive note, governments across Europe awarded a record 37 GW of new wind capacity (29 GW in the EU) in 2024. But without faster permitting, better grid connections, and increased electrification, these awards won’t translate into the clean energy-producing wind farms Europe desperately needs.

Investments and corporate interest

Investments in wind energy totaled €31 billion in 2024, financing 19 GW of new capacity. While onshore wind investments remained strong at €24 billion, offshore wind funding saw a dip. Final investment decisions for offshore projects remain challenging due to slow permitting and grid delays.

Corporate consumers continue to show strong interest in wind energy. Half of all electricity contracted under Power Purchase Agreements (PPAs) in 2024 was wind. Dedicated wind PPAs were 4 GW out of a total of 12 GW of renewable PPAs. 

Read more: Renewables could meet almost half of global electricity demand by 2030 – IEA


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Podcast: New Tesla Model Y unveil, Mazda 6e, Aptera solar car production-intent, more

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Podcast: New Tesla Model Y unveil, Mazda 6e, Aptera solar car production-intent, more

In the Electrek Podcast, we discuss the most popular news in the world of sustainable transport and energy. In this week’s episode, we discuss the official unveiling of the new Tesla Model Y, Mazda 6e, Aptera solar car production-intent, and more.

The show is live every Friday at 4 p.m. ET on Electrek’s YouTube channel.

As a reminder, we’ll have an accompanying post, like this one, on the site with an embedded link to the live stream. Head to the YouTube channel to get your questions and comments in.

After the show ends at around 5 p.m. ET, the video will be archived on YouTube and the audio on all your favorite podcast apps:

We now have a Patreon if you want to help us avoid more ads and invest more in our content. We have some awesome gifts for our Patreons and more coming.

Here are a few of the articles that we will discuss during the podcast:

Here’s the live stream for today’s episode starting at 4:00 p.m. ET (or the video after 5 p.m. ET):

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BYD’s new Han L EV just leaked in China and it’s a monster

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BYD's new Han L EV just leaked in China and it's a monster

The Chinese EV leader is launching a new flagship electric sedan. BYD’s new Han L EV leaked in China on Friday, revealing a potential Tesla Model S Plaid challenger.

What we know about the BYD Han L EV so far

We knew it was coming soon after BYD teased the Han L on social media a few days ago. Now, we are learning more about what to expect.

BYD’s new electric sedan appeared in China’s latest Ministry of Industry and Information Tech (MIIT) filing, a catalog of new vehicles that will soon be sold.

The filing revealed four versions, including two EV and two PHEV models. The Han L EV will be available in single- and dual-motor configurations. With a peak power of 580 kW (777 hp), the single-motor model packs more power than expected.

BYD’s dual-motor Han L gains an additional 230 kW (308 hp) front-mounted motor. As CnEVPost pointed out, the vehicle’s back has a “2.7S” badge, which suggests a 0 to 100 km/h (0 to 62 mph) sprint time of just 2.7 seconds.

BYD-Han-L-EV
BYD Han L EV (Source: China MIIT)

To put that into perspective, the Tesla Model S Plaid can accelerate from 0 to 100 km in 2.1 seconds. In China, the Model S Plaid starts at RBM 814,900, or over $110,000. Speaking of Tesla, the EV leader just unveiled its highly anticipated Model Y “Juniper” refresh in China on Thursday. It starts at RMB 263,500 ($36,000).

BYD already sells the Han EV in China, starting at around RMB 200,000. However, the single front motor, with a peak power of 180 kW, is much less potent than the “L” model. The Han EV can accelerate from 0 to 100 km/h in 7.9 seconds.

BYD-Han-L-EV
BYD Han L EV (Source: China MIIT)

At 5,050 mm long, 1,960 mm wide, and 1,505 mm tall with a wheelbase of 2,970 mm, BYD’s new Han L is roughly the size of the Model Y (4,970 mm long, 1,964 mm wide, 1,445 mm tall, wheelbase of 2,960 mm).

Other than that it will use a lithium iron phosphate (LFP) pack from BYD’s FinDreams unit, no other battery specs were revealed. Check back soon for the full rundown.

Source: CnEVPost, China MIIT

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