The effect of reduced contrast on drivers' speed perception

It has been demonstrated, using abstract psychophysical stimuli, that speeds appear slower when contrast is reduced under certain conditions. Does this effect have any real life consequences? One previous study has found, using a low fidelity driving simulator, that participants perceived vehicle speeds to be slower in foggy conditions. We replicated this finding with a more realistic video-based simulator using the Method of Constant Stimuli. We also found that lowering contrast reduced participants’ ability to discriminate speeds. We argue that these reduced contrast effects could partly explain the higher crash rate of drivers with cataracts (this is a substantial societal problem and the crash relationship variance can be accounted for by reduced contrast). Note that even if people with cataracts can calibrate for the shift in their perception of speed using their speedometers (given that cataracts are experienced over long periods), they may still have an increased chance of making errors in speed estimation due to poor speed discrimination. This could result in individuals misjudging vehicle trajectories and thereby inflating their crash risk. We propose interventions that may help address this problem.

An Efficient and Verifiable Solution to the Millionaire Problem

A new solution to the millionaire problem is designed on the base of two new techniques: zero test and batch equation. Zero test is a technique used to test whether one or more ciphertext contains a zero without revealing other information. Batch equation is a technique used to test equality of multiple integers. Combination of these two techniques produces the only known solution to the millionaire problem that is correct, private, publicly verifiable and efficient at the same time.