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Roadio has front and rear facing cameras with AI driven object detection to help keep cyclists and motor scooter riders safer.
Garmin (amongst others) has had a rear mounted radar (and bike light) system for a while. They also have one with a camera built in.
> We then log a sensor events [sic] if the majority of cells in the sensor frame agree to the same value within a threshold parameter [...]. This ensures that sensor events are only logged when large objects like cars block the sensor’s field-of-view , i.e., one or more small objects like branches or distance pedestrians in the sensor’s field-of-view will not trigger this condition. While there is no guarantee that this approach strictly identifies cars, we empirically saw during testing that passing cyclists and pedestrians rarely satisfied this condition at the typical passing distance due to the wide field-of-view of the VL53L8.
Also interesting that it's quite cheap to build:
> The whole system can cost less than $25 [...]
From the paper https://dl.acm.org/doi/10.1145/3706598.3713325
Having biked a lot in SF, my impression is the best protected bike lanes are on wide roads like Folsom/Howard, Fell/Oak, etc. where proximity isn’t generally an issue, but I’d expect intersections to be riskier due to higher car speeds. While cars passing on isn’t an issue on the Wiggle with a critical mass of riders, on neighborhood streets where sharing the road is obligated the drivers can be scariest, especially in the Sunset. In NYC, an abundance of one lane, one way streets make controlling an entire street easier.
The reality of city design at the moment is almost any bike route will require the sharing the road with cars at some point, usually at the start and end of a ride, because bike lane and “bike route” coverage is often poor in residential areas and business districts.
I live in a country that is cycling walhalla, where there are more bikes than citizens, where a good chunk of the population go to work and do groceries by bike and we do all of the above.