Objective- Attenuating post lockdown vehicular speed by employing visual reaction time as a tool to prime the citizens for creating decorum of driving and checking the road traffic fatalities.Background- It is indispensable to curb the driving speed post lockdown to avoid accidents. Even though, the impact of inactivity on RT has been well established, an insight into the new method can deal with the gross issue of road traffic casualty worldwide. Method- Using a web-based platform (http://physicsiology.com), quantification of post lockdown speed was achieved for 643 participants under average speed before lockdown and RT measurement. Results- Compared to pre lockdown vehicular speed, reduced post lockdown speed was well calculated and suggested. Also, there was a correlation between RT, age, and days of lockdown.Conclusions- Containment of speed can be achieved to prime people through RT. Additionally, RT can determine the rate of change of frequency (ROCOF) for detecting the swiftness of action (i.e., the brain's ability to deal with the transition between reaction times of different events) required for averting road traffic collisions. Compelling to suggest a need for a humanoid simulator that can garner real-time data.Application- Suggesting a fresh outlook for designing a contraption for a better appraisal of the fleet in driving skills, thus beaconing the course towards restraining road traffic fatalities

Objectives- Attenuating the vehicular speed after lifting of lockdown during Covid-19, by employing visual reaction time (RT) as a tool to prime citizens for creating decorum of driving and checking the road traffic fatalities.Background- It is indispensable to curb the driving speed post lockdown to avoid accidents. Even though, the impact of inactivity on RT has been well established, an insight into the new method can deal with the gross issue of road traffic casualty worldwide. Method- Using a web-based platform (http://physicsiology.com), RT was derived by visual stimulation test. Of which, the slowest and the fastest RT were obtained. Using these and prefeed average vehicular speed before lockdown in the website the post lockdown vehicular speed were quantified for the participant. Apart from spreading awareness the website has also collected data for age and days of lockdown.Results- Compared to pre lockdown vehicular speed, reduced post lockdown speed was well calculated and suggested. Furthermore, from 643 participants, there was a correlation between RT, age, and days of lockdown.Conclusion- Containment of speed can be achieved through RT to prime people for prevention of road traffic collision after lifting of Covid-19 lockdown.

Objective – Suggesting an approach to determine the rate of change of brain’s frequency (ROCOF). Background – Reaction time (RT) is mostly well estimated in any driving simulator, especially the visual reaction time. However, an appropriate representation of RT in a driving simulator can help determine the changes in brain’s frequency. Method – We propose, use a driving simulator which can efficiently measure and record the participant’s reaction times for the rapidly successive tasks in a simulator. A reciprocal presentation of each RT can be used as the brain’s frequency for performing that task. Using this concept, a simulator software can calculate the brain’s frequencies for all the tasks. While its graphical representation over time can yield time frequency distribution (TFD). Results – Analysis of this time frequency representation (TDR) of RT may help to study the pattern of brain activity and to derive ROCOF, which can be used to classify the drivers.

Objective – Suggesting an approach to determine the rate of change of brain’s frequency (ROCOF).Background – Reaction time (RT) is mostly well estimated in any driving simulator, especially the visual reaction time. However, an appropriate representation of RT in a driving simulator can help determine the changes in brain’s frequency. Method – We propose, use a driving simulator which can efficiently measure and record the participant’s reaction times for the rapidly successive tasks in a simulator. A reciprocal presentation of each RT can be used as the brain’s frequency for performing that task. Using this concept, a simulator software can calculate the brain’s frequencies for all the tasks. While its graphical representation over time can yield time frequency distribution (TFD). Results – Analysis of this time frequency representation (TDR) of RT may help to study the pattern of brain activity and to derive ROCOF, which can be used to classify the drivers.