The Best Tesla Frunk (Trunk) or Treat Ideas & Halloween Decorations

By Karan Singh
Chrisheninger/Reddit

Every Tesla has a frunk storage, and people use them for everything under the sun. But today, it's not about the sun but rather what’s under the pumpkin moon.

Let’s take a look at some of the best Frunk (or Trunk) or Treat ideas we’ve seen in previous years, and maybe they’ll be just what you need for a little inspiration.

Jaws

One of the easiest things to do is to turn your car into a shark with some nice and spikey teeth. Chrisheninger on Reddit dresses up his Tesla with Shark teeth every year and parks it out front for the trick-or-treaters! Take a look at the hero image above for a preview!

And it's pretty easy to do, too – you just need some white posterboard, tape, and a pair of scissors to get started. Fold the posterboard in half, then cut it into triangles of various sizes. Tape your triangles to the top and bottom of the frunk, and voila! Jaws!

For the bottom side, you can wedge the teeth into the gap between the body and the frunk, so you may not need tape there.

You can also get some clear cellophane tape and cover up the headlights to give them a nice orange or red glow.

Toothless

Jen's Toothless Tesla Dragon
Jen's Toothless Tesla Dragon
jenstreet

This one is a bit of a bigger project. @jenstreet over on X posted an absolutely spectacular job of turning their Tesla into Toothless, from How to Train Your Dragon!  We’re not going to get into how to do this – instead, Jen posted her own guide on how they did the project. Props to them for the very detailed instructions!

This is an absolutely spectacular way to showcase your creativity! You can read their guide here.

Model X Vampire Bat

A Vampire Bat Model X
A Vampire Bat Model X
Not a Tesla App

If you’re a creative Model X owner, you can turn your Model X into a vampire bat! All it takes is a few pieces of cardboard for the teeth, like with the Jaws decoration above. While in the example below, the enterprising user placed more teeth on the gullwing doors of the Model X, we recommend draping a few black sheets from the gullwing doors to complete the look, especially if you tear them up at the ends a bit.

Combine this with a well-thought-out Tesla Lightshow (more on this later), and you’ve got a seriously cool-looking vampiric Model X in your driveway.

Lightning McQueen

Not a Tesla App

Here’s a great and simple one if you have a red Tesla — Lightning McQueen. It can be as simple as buying a Lightning McQueen sunshade for less than $20 (Amazon link) and sticking it in your car. You can also go to the other extreme, like S.E. Robinson Jr., and get custom decals for your Tesla. Although there hasn’t been a new Cars movie since 2017, these movies are still insanely popular with young kids.

SERobinsonJr

Other Ideas

Not a Tesla App

You can always use the frunk in other unique ways too – there’s quite a bit of space in there. Put in a decorative gravestone or ghost or cover it up in decorative spider webbing. You can do pretty much whatever your heart desires with the frunk. You can even put in some battery-powered lighting and fog generator and give it an ominous glow.

If you’ve got an older Model S or Model X with a nosecone, there are some unique ideas you can use that for too – including short teeth with googly eyes on the hood. Less scary, but definitely still fun!

Boombox

Using the Boombox feature on your Tesla, combined with keeping it turned on through Camp Mode, will allow you to play all the creepy Halloween music you want to get the atmosphere just right. Maybe throw in a fog generator somewhere, and you’ll have one of the best Halloween attractions on the block!

p1ngz

Lightshow

You can use Tesla’s Lightshow functionality to take it a step further and sync the music and lights of your car – and if you’ve got a Model X – the gullwing doors too! That’ll really complete the entire Halloween ensemble.

Sadly, there is one catch with this one – you’ll need to keep re-enabling the Lightshow manually from inside the vehicle. Tesla has not yet released functionality for Lightshows to be played remotely from the Tesla app.

I wonder what we’re going to see for this year’s Frunk or Treat? Personally, I have a few things planned for this year, and this is also the first year we’ll see Cybertrucks participating. We’re excited to see what people do with the Cybertruck’s huge and automated frunk and unique shape.

Given the Cybertruck’s frunk also has 120V power in it, there are even more unique and interesting things one can do.

Tesla Vehicle Data Report: How to Request It and What's Included

By Karan Singh
Not a Tesla App

If you’re ever involved in a collision with your Tesla, there’s a good chance you can retrieve dashcam footage of the incident—provided the USB drive and glovebox survive. However, sometimes they don’t, and even dashcam footage may not be sufficient.

In such cases, you can request a full recording from Tesla, along with a detailed data report showing comprehensive information about your vehicle’s performance during the collision. Shortly after any impact, your Tesla automatically uploads its crash log and related data to Tesla’s servers when possible, even using the low-voltage battery if the high-voltage pyro fuses are triggered.

Hopefully, you’ll never need this, but here’s how to request a Tesla Vehicle Data Report and what you can expect in the report.

How to Request a Report

Tesla has a simple, automated process for owners to request a Vehicle Data Report. To do so, simply go to Tesla’s Data Association Page and log into your Tesla Account.

From there, you’ll see a form that contains several options. Under “Regarding,” you’ll choose “Data Privacy Request,” and in the next selection, choose “Obtain a Copy of My Data.”

Tesla will then ask you to choose a vehicle that’s attached to your account and a range of dates for which you want data.

Tesla will provide details for the whole date range you specify, so it’s best to keep it small. Once you hit Submit, Tesla will start processing the request. Collision data is kept for an extended period of time, enabling people to go back and find data as required.

The summary page for the Vehicle Data Report
The summary page for the Vehicle Data Report
@bilalsattar on X

Within 30 days, and often much sooner, Tesla should e-mail you back with the report in PDF format and a CSV sheet containing all the raw information related to the request. This information is available for any country in which Tesla sells cars. If your country is outside of Tesla’s regular sales zones, you can try reaching out anyway, but we’re not sure if they will retain your data or not.

Tesla can also send you footage and data even if the incident wasn’t recorded as a collision – they’ll send you whatever is available – for any specific timeline you request.

Tesla Vehicle Data Report

The report is several pages long and comes in a nicely formatted PDF package. It breaks down the incident into various sections that help highlight what happened during the event. The first page summarizes the incident by highlighting key events and metrics like Autopilot use and speed.

Summary & Event Information

The Summary and Event Information sections are on the left side of the first page. The summary section is a text version of what happened during the event, reporting the time of the incident, speed, and whether seat belts were used, among other details.

The event information section includes some high-level information, such as the location of the incident, whether dashcam recordings are available, and the date and time.

Driver Log Data Overview

The Driver Log Data Overview section focuses on a few Tesla features and shows whether they were enabled at the five-second mark before the incident, one second before the incident occurred, or at the time of the incident. Tesla will show whether Autosteer / FSD, Driver Monitoring, Cruise Control, and Manual Brakes were used at all of these points. They will also show the status of the driver’s seat belt. Later in the report, Tesla will show graphs for each of these features so that you can see if they changed over the course of the incident.

Speed and Collision

The Vehicle Data Report's formatting
The Vehicle Data Report's formatting
@bilalsattar on X

The Speed and Collision section shows a timeline-based graph of the vehicle’s speed at the time of collision, four seconds before the collision, and four seconds after. The vertical line on the graph represents the collision, giving you a better understanding of what happened before and after the incident. However, in the following pages of the report, Tesla provides numerous time-based graphs that highlight many other metrics, including brake pedal use, accelerator, steering wheel torque and more.

Area of Detected Impact

This area of the report shows the vehicle from the top-down view and which areas detected an impact.

Time-Based Graphs

The rest of the report includes detailed graphs showing various vehicle metrics before, during, and after the incident.

Some of these graphs include the vehicle’s speed, steering wheel torque, steering wheel angle (how much the wheel was being turned and in which direction), accelerator and brake pedal usage, and pressure of the brake master cylinder. Tesla will even show whether any doors were opened during the seconds leading up to or following the incident.

If Tesla has a video of the incident, that will also be provided as a link for you to download. All the other information - the charts and graphs - raw information is also provided in a CSV file, which you can open in software like Microsoft Excel or Google Sheets.

Not a Tesla App

To wrap up, Tesla is currently the only car manufacturer in the world that can provide this information to its customers at the drop of a hat. This information is immensely valuable, and it could be the difference between someone paying an insurance claim or being charged with a crime.

Tesla produces some of the safest vehicles on the planet, and their commitment to safety and reporting is spectacular. We’re happy to see Tesla continue to take steps to better help their customers.

Thanks to Nic Cruze Patane for sharing the report. We hope you never need to use this, but it’s good to know that it’s available.

Inside Tesla’s FSD: Patent Explains How FSD Works

By Karan Singh
Not a Tesla App

Thanks to a Tesla patent published last year, we have a great look into how FSD operates and the various systems it uses. SETI Park, who examines and writes about patents, also highlighted this one on X.

This patent breaks down the core technology used in Tesla’s FSD and gives us a great understanding of how FSD processes and analyzes data.

To make this easily understandable, we’ll divide it up into sections and break down how each section impacts FSD.

Vision-Based

First, this patent describes a vision-only system—just like Tesla’s goal—to enable vehicles to see, understand, and interact with the world around them. The system describes multiple cameras, some with overlapping coverage, that capture a 360-degree view around the vehicle, mimicking but bettering the human equivalent.

What’s most interesting is that the system quickly and rapidly adapts to the various focal lengths and perspectives of the different cameras around the vehicle. It then combines all this to build a cohesive picture—but we’ll get to that part shortly.

Branching

The system is divided into two parts - one for Vulnerable Road Users, or VRUs, and the other for everything else that doesn’t fall into that category. That’s a pretty simple divide - VRUs are defined as pedestrians, cyclists, baby carriages, skateboarders, animals, essentially anything that can get hurt. The non-VRU branch focuses on everything else, so cars, emergency vehicles, traffic cones, debris, etc. 

Splitting it into two branches enables FSD to look for, analyze, and then prioritize certain things. Essentially, VRUs are prioritized over other objects throughout the Virtual Camera system.

The many data streams and how they're processed.
The many data streams and how they're processed.
Not a Tesla App

Virtual Camera

Tesla processes all of that raw imagery, feeds it into the VRU and non-VRU branches, and picks out only the key and essential information, which is used for object detection and classification.

The system then draws these objects on a 3D plane and creates “virtual cameras” at varying heights. Think of a virtual camera as a real camera you’d use to shoot a movie. It allows you to see the scene from a certain perspective.

The VRU branch uses its virtual camera at human height, which enables a better understanding of VRU behavior. This is probably due to the fact that there’s a lot more data at human height than from above or any other angle. Meanwhile, the non-VRU branch raises it above that height, enabling it to see over and around obstacles, thereby allowing for a wider view of traffic.

This effectively provides two forms of input for FSD to analyze—one at the pedestrian level and one from a wider view of the road around it.

3D Mapping

Now, all this data has to be combined. These two virtual cameras are synced - and all their information and understanding are fed back into the system to keep an accurate 3D map of what’s happening around the vehicle. 

And it's not just the cameras. The Virtual Camera system and 3D mapping work together with the car’s other sensors to incorporate movement data—speed and acceleration—into the analysis and production of the 3D map.

This system is best understood by the FSD visualization displayed on the screen. It picks up and tracks many moving cars and pedestrians at once, but what we see is only a fraction of all the information it’s tracking. Think of each object as having a list of properties that isn’t displayed on the screen. For example, a pedestrian may have properties that can be accessed by the system that state how far away it is, which direction it’s moving, and how fast it’s going.

Other moving objects, such as vehicles, may have additional properties, such as their width, height, speed, direction, planned path, and more. Even non-VRU objects will contain properties, such as the road, which would have its width, speed limit, and more determined based on AI and map data.

The vehicle itself has its own set of properties, such as speed, width, length, planned path, etc. When you combine everything, you end up with a great understanding of the surrounding environment and how best to navigate it.

The Virtual Mapping of the VRU branch.
The Virtual Mapping of the VRU branch.
Not a Tesla App

Temporal Indexing

Tesla calls this feature Temporal Indexing. In layman’s terms, this is how the vision system analyzes images over time and then keeps track of them. This means that things aren’t a single temporal snapshot but a series of them that allow FSD to understand how objects are moving. This enables object path prediction and also allows FSD to understand where vehicles or objects might be, even if it doesn’t have a direct vision of them.

This temporal indexing is done through “Video Modules”, which are the actual “brains” that analyze the sequences of images, tracking them over time and estimating their velocities and future paths.

Once again, heavy traffic and the FSD visualization, which keeps track of many vehicles in lanes around you—even those not in your direct line of sight—are excellent examples.

End-to-End

Finally, the patent also mentions that the entire system, from front to back, can be - and is - trained together. This training approach, which now includes end-to-end AI, optimizes overall system performance by letting each individual component learn how to interact with other components in the system.

How everything comes together.
How everything comes together.
Not a Tesla App

Summary

Essentially, Tesla sees FSD as a brain, and the cameras are its eyes. It has a memory, and that memory enables it to categorize and analyze what it sees. It can keep track of a wide array of objects and properties to predict their movements and determine a path around them. This is a lot like how humans operate, except FSD can track unlimited objects and determine their properties like speed and size much more accurately. On top of that, it can do it faster than a human and in all directions at once.

FSD and its vision-based camera system essentially create a 3D live map of the road that is constantly and consistently updated and used to make decisions.

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