Li Yalin rarely encountered such a tricky case.
In the past, tricky cases were due to too few clues, such as incomplete fingerprints and shoe prints, blurry surveillance footage and so on, but this time was different. This time, there were too many clues, so many that it made one’s scalp tingle.
The surveillance videos showed dozens of identical cars gradually entering the highway, then choosing different directions at forks or exiting the highway.
The most astonishing thing was that they all impersonated the same car’s ETC system.
This meant they had also hacked into the highway toll system.
He now had too many directions to investigate, such as the driving trajectories of each car that day, as well as the origins and destinations of these vehicles. He could investigate who bought so many identical commercial vehicles, check which vehicle management offices recently registered the same model vehicles, or examine if the hackers left any traceable traces in the ETC system.
However, when there were too many clues, it was not much different from having no clues at all.
Every clue could be pursued, but no one knew if investigating it would lead to a dead end or into another trap set by the opponent.
If they traced the vehicle owners and then checked the owners’ information, what if the information was forged?
If they found the hacker’s traces, but the information left by the hacker was deliberately set as a trap, what then?
Therefore, Li Yalin did not want to diverge his thinking at this time. What he hoped most was that the AI could locate the vehicle where Xiao Churan was truly in, through extremely subtle anomalies, so subtle that humans could not detect them.
If they could peel away the layers from dozens of cars and select the unique one, everything would be much simpler.
So, he inputted all the video materials into the AI model, letting the AI model analyse the differences in these vehicles itself.
The AI immediately analysed these vehicles from multiple dimensions. The AI believed there were no differences in the vehicle appearances, not even different stains could be found. This proved they had thoroughly cleaned the vehicles before departure.
If needed, the AI could judge based on the suspension posture during driving. For example, the AI could use the videos to judge road undulations, estimate the slope of the road undulations, and then, based on the vehicle’s speed, judge the suspension’s fluctuation state when passing a certain degree of undulation.
Whether it was ordinary spring suspension, or air or electromagnetic suspension, when the vehicle drove on undulating roads, the body would compress or release the suspension with the undulations.
The major factors determining the fluctuation amplitude were the road undulation slope, the vehicle’s driving speed, the suspension tuning, and the vehicle’s curb weight.
Among these four points, if any one differed, the suspension performance would be different.
The AI’s entry point was that since they were all the same model, their suspensions must be the same. The road slope and driving speed could be calculated by the AI for their linkage relationship, to determine if the same cars showed the same reaction coefficient at different speeds over different slopes.
The only variable that could not be calculated was the vehicle’s curb weight.
The heavier the car, the lower the fluctuation degree when dealing with undulations, and vice versa, just like a fully loaded ship handling waves more steadily.
The AI listed a bunch of its own entry points, which made Li Yalin feel very reasonable, so he immediately authorised the AI to analyse along this line of thought.
However, after the AI ran at full power for dozens of seconds, the feedback conclusion was: “Through calculating the road slope in the videos, the vehicle driving speed, and the body fluctuation degree, I obtained a reaction coefficient. After comparison, I found that all vehicles’ reaction coefficients are the same. This does not conform to common sense.”
Li Yalin immediately asked: “What does not conforming to common sense mean?”
The AI replied: “If all vehicles’ reaction coefficients calculated from these three points are the same, it can only prove that all vehicles’ curb weights are almost identical. If their vehicle weights differed greatly, each car’s reaction coefficient should be different. Vehicles with smaller weight have higher reaction coefficients, vehicles with larger weight have lower reaction coefficients.”
