1. Fresh unplowed snow where there are no lane markers visible.
2. Significant banks that take up half a lane with two lanes in each direction.
3. Ice (often one doesn't start going through an intersection on a green until you're 100% sure that every car has cleared - I've been on both sides of this, where you don't go because there's a car sliding through, and the car sliding through because slick ice doesn't care about brakes)
4. Hard braking (the "drive slow and use the brakes lightly for a long while")
5. Cold car things. Electric battery life in the cold (heater for the passengers). Wipers frozen to the windshield. Accumulation of snow on the window. Excess snow on top of the car (considered an insecure load).
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Tangent for the "how do you handle lanes when you can't see any" ... old school approach: https://ieeexplore.ieee.org/document/833362
> Driving a snowplow during whiteout condition is one such example. In order to improve the safety and efficiency of the snow removal operation, a supplemental steering guidance display was proposed and instrumented in a Caltrans snowplow. The guidance information was calculated based on the magnetic markers embedded under the roadway. Operations were successfully conducted on a 6.25 km freeway over Donner Summit on Interstate 80 in California during the 1998-1999 winter season.
Forget unplowed snow. Often in Calgary where I live there's no lane markers visible under the snow for months at a time, even if it's plowed regularly
When snowing in Toronto you usually cannot see the painted lines on the road, there's just the lines from cars driving through the snow that you follow. Sometimes two lane roads become an unofficial one lane road depending on what feels safe.
The falling snow also bounces the laser pulses(?) back at the lidar. Snow fall can be pretty heavy and make it difficult to see objects far ahead. Not sure how well their handling of rain ports over to snow, but it will be interesting to see!
https://path.berkeley.edu/automation/development-advanced-ro...
It had hands free operation (still needed someone in the seat to control the plow) and lane assist in whiteout conditions when the outside edge of the lane had a cliff (much worse than driving into the ditch).
https://path.berkeley.edu/automation/development-advanced-ro...
> This project is one of the first real-world applications derived from PATH/Caltrans research in the area of automated vehicle control. A modified snowblower with add-on sensors, actuator, computer and driver interfaces was developed, and initial field tests were conducted along the 8 guardrail sections between Kingvale and Soda Springs on the shoulders of Interstate-80 near Donner Summit.
https://path.berkeley.edu/wp-content/uploads/2024/11/develop...
> Various lateral sensing and referencing technologies were investigated for this application; what was found was that machine vision does not penetrate snow, and that the GPS system does not provide sufficient reliability under possible multipath and blockage scenarios. A magnetic-marker-based sensing system was chosen for the initial implementation primarily because of its high reliability and accuracy (better than 1 cm) under all weather conditions. The mountainous highway I-80 near Donner Summit (close to Lake Tahoe) was chosen to be the first field test site. In 2001, magnets were installed along the eastbound and westbound guardrails of I-80, at 4 feet apart and 4 feet away from the guardrail. Binary coding of the magnetic markers was designed (north pole up vs. south pole up) to provide information about guardrail characteristics, such as the shoulder side (right or left of the blower) and the end of guardrail. Eight sections of the guardrail were equipped with magnets for the initial feasibility operations with a total length of 1.46 km (0.9 mile) between Soda Springs and Kingvale.
Lidar is cool when you want to get a point cloud from a fixed location, or dealing with perfectly uniform surfaces (which cars don't because humans can't do this either), but beyond that there are better ways to do things.
“Why, thank you, Camera! You are doing a wonderful job of seeing everything in your FOV!”
“Ahh, you are very flattering, LIDAR! It’s an endearing quality in you, for sure!”
LIDAR: blushes
Not always. Definitely not all freeways.
> And every car has its own lights for seeing where you are driving
Not always far enough. Especially at freeway speeds on unlit freeways.
If humans don't have lidar but can drive it's an existence proof of the viability of that approach.
Lidar is superhuman vision.
The real answer is very simple: safe drivers slow down to adapt to poor conditions (including visibility). Lidar might reduce how much it needs to slow down but I don't think it will be eliminated because you can't drive with only lidar.
I smell smoke before I see it. Useful if there's a forest fire up ahead.
Burning rubber or smoke from the engine is an indicator of a mechanical issue.
> you can't drive with only lidar.
Nobody said you could. This is a strawman.
Tesla stans are the only ones trying to convince everyone you can only drive with cameras. Everyone else is pretty united on the usefulness of multiple inputs.
Didn't mean it in that way. I meant a car with camera+lidar would realistically still slow down because of the reduced camera visibility.
> Tesla stans are the only ones trying to convince everyone you can only drive with cameras. Everyone else is pretty united on the usefulness of multiple inputs.
Ignore them. The latest Model S and X have radar again, but possibly unused right now, so they are probably going to roll that out in a refresh of the 3 and Y eventually.