Yes the headline is exaggerating the evidence presented in the article - (I’m shocked /s).
I think the authors are confident that the observed crash rate seems to be higher for eBikes . . . but that’s not enough to say which is more dangerous.
I’d think rider attitudes will be one of the main things here - take a negligent or reckless eBiker and put them on an eScooter and I’m pretty sure they’ll find a way to crash it. It’s not obvious to me that they used trip average speed as a proxy for this - I think they should at least have tested if their ratios were the similar when comparing fast with fast and slow with slow - that’d have been easy enough and they probably have the sample size to do that.
They mention high-res GPS data so they could maybe have done a better “driving characteristics” thing - using acceleration and braking data as a proxy for riders who are either bad at reading the road - or are impatient. That might be where they’d need more data, as they’d probably need to establish a “normal” profile for each route - to benchmark the extremes of behaviour.
I guess that’d have taken a lot longer and the funding only goes so far.
Interesting dataset they have for sure - maybe they’ll do some more papers on it in future.
Yes the headline is exaggerating the evidence presented in the article - (I’m shocked /s).
I think the authors are confident that the observed crash rate seems to be higher for eBikes . . . but that’s not enough to say which is more dangerous.
I’d think rider attitudes will be one of the main things here - take a negligent or reckless eBiker and put them on an eScooter and I’m pretty sure they’ll find a way to crash it. It’s not obvious to me that they used trip average speed as a proxy for this - I think they should at least have tested if their ratios were the similar when comparing fast with fast and slow with slow - that’d have been easy enough and they probably have the sample size to do that.
They mention high-res GPS data so they could maybe have done a better “driving characteristics” thing - using acceleration and braking data as a proxy for riders who are either bad at reading the road - or are impatient. That might be where they’d need more data, as they’d probably need to establish a “normal” profile for each route - to benchmark the extremes of behaviour.
I guess that’d have taken a lot longer and the funding only goes so far. Interesting dataset they have for sure - maybe they’ll do some more papers on it in future.