Spot Speedy Experiment

Introduction
The speed of traffic in urban areas has been one concern amongst walking pedestrians, and more specifically walking pedestrians on stretches of Woody Hayes Drive and Olentangy River Road. To gauge whether or not traffic control is necessary, vehicles are timed at a specific interval to give a range of varying speeds; these speeds could then be compared to the set speed limit on the road. The purpose of this experiment was to determine if cars on Woody Hayes Drive needed additional traffic control to reduce speeding.
The sections that follow describe the process, calculations and answers to this experiment. Section 2 will describe the tools and step-by-step processes that’re required to replicate this study. Meanwhile, section
A speed trap of about 176ft with markers would also be important so there’s a way to gauge when a vehicle enters or leaves the trap. Next, one would need basic knowledge on how to calculate values such as average, mode, and how to determine standard deviation through calculations and graphically.
To begin the experiment, each member of the group discussed which role he/she would perform, as shown in Table A1. The group would then leave to the designated location previously marked alongside either Woody Hayes Drive or Olentangy River. The diagram of the Spot Speedy Study location is shown in Figure
Alongside of the mode, the calculated standard deviation was 4.84 mph, giving a new range to be ±4.84 from the average, 28.82 mph. Within the standard deviation, 68% of all vehicles were found between 23.98 mph and 33.66 mph.
Next, vehicles out of the determined range of standard deviation, the remaining 32% of the vehicles, would be factored by both the speed bump and the clear weather. Vehicles that were found out of the pace, and definitely speeding, could have been speeding due to safe road conditions or some other various reason, such as being late. Vehicles that were slower could have been because of the speed bump before the speed trap, or the traffic from rush hour.
Due to the experiment’s data being dependent on the time recorded, one error that would skew the data would be human reaction time. Within the experiment, the flagger’s reaction to a vehicle crossing the marker would slightly shorten the time that the timer would record. Next, the timer’s reaction to the flagger’s signal would shorten the time, while the timer’s reaction time to when the car crossed the exit marker would lengthen the recorded time. These three variables could potentially overestimate or underestimate the true time of the vehicle in the speed