>We introduce a theoretical approach that uses temporal coarse-graining akin to Einstein’s kinetic theory of Brownian motion
Since when did Brownian motion smoke and air particles have eyes and need to stand on two legs?
I sometimes think scientists need to get out more, maybe attend Glastonbury, where you are walking from the Pyramid Stage to the Other Stage, after its rained heavily and Eavis hasnt given the order to put any or enough straw down, so everyone is concentrating on staying upright by looking down at the mud swamp that will consume their next step and wellington boot whilst also briefly but hesitantly looking at the person or persons immediately in front of them in order to facilitate their escape.
Sure arena's are less likely to be water logged mud swamps, but outdoor puddles introduce their own obstacles as do cambers of the surface. Get past ticket control, enter big atriums and newbies will pause in awe of the size whilst also getting their bearings, regulars will know where to go. I see this behaviour in every major train station or airport, especially as the signs are generally up high, diverting their gaze from taking the next step, thus slowing down the flow of people.
I dont see any of these factors being accounted for in this paper.
And its for the above mentioned reasons, namely not accounting for the proper metrics that count, that some self driving vehicle companies are not going to succeed any time soon at level 5, because their algorithm weighting is all wrong.
Since when did Brownian motion smoke and air particles have eyes and need to stand on two legs?
I sometimes think scientists need to get out more, maybe attend Glastonbury, where you are walking from the Pyramid Stage to the Other Stage, after its rained heavily and Eavis hasnt given the order to put any or enough straw down, so everyone is concentrating on staying upright by looking down at the mud swamp that will consume their next step and wellington boot whilst also briefly but hesitantly looking at the person or persons immediately in front of them in order to facilitate their escape.
Sure arena's are less likely to be water logged mud swamps, but outdoor puddles introduce their own obstacles as do cambers of the surface. Get past ticket control, enter big atriums and newbies will pause in awe of the size whilst also getting their bearings, regulars will know where to go. I see this behaviour in every major train station or airport, especially as the signs are generally up high, diverting their gaze from taking the next step, thus slowing down the flow of people.
I dont see any of these factors being accounted for in this paper.
And its for the above mentioned reasons, namely not accounting for the proper metrics that count, that some self driving vehicle companies are not going to succeed any time soon at level 5, because their algorithm weighting is all wrong.