Lab 3b - Spot Speed Lab - Cover Sheet.docx

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Ohio State University *

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Jan 9, 2024

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ENGR 1181 | Individual: Spot Speed Study - Professional Email - Team - O Accountability Acknowledgement: I declare and acknowledge that that the work I have submitted is my own. Name (typed) Signature Date Jack Olson Jack Olson 9/19/23

Experiment Analysis Email 19 September 2023 To: The Ohio State University and the Traffic Management Unit, City of Columbus From: J. Olson Subject: Spot Speed Lab Results Greetings to members of the Traffic Management Unit Team, This email is written to you as a report of the results of a spot speed experiment, conducted on a 100-meter stretch of the bridge on Woody Hayes Dr., with speeds from 54 cars collected. The data was collected on September 6 th of this year at around 10am, the weather was clear and road conditions were of good quality (smooth, largely without blemishes). The following sections detail aspects of the study analysis. The data implies of a central tendency, which is the inclination of samples in each measurement to cluster around a central value. This is evidenced by a peak relative frequency of 20% near the median, (occurs at 23 mph, median at 25 mph) and generally higher relative frequency values surrounding the median, the lowest values occurring near the edge of the data, with the 14.5 mph and 45 mph groups both having only 2 cars within their respective ranges. The relative frequency graph also shows a shape similar to a bell curve.

Dispersion refers to the amount of spread in a dataset about an expected value. The data showed a relatively large level of dispersion, highlighted by the percent of cars in pace being only 50%. The calculated standard deviation was 6.71 mph, also implying much of the data is spread among parts of the graph not within the pace (20-30 mph) and a generally higher dispersion. The experimental results indicated a close correlation to the posted speed limit of 25 mph, with average speed 26.4 mph and median speed of exactly 25 mph. This implies a relatively safe relationship between driver and pedestrian, as pedestrians can generally expect drivers near that segment of road to be on average, driving near the posted speed limit. Several factors came into play during data collection that likely had an impact on the results. One of such factors is the vehicle being driven, with average speeds changing between standard cars, trucks, buses, etc. In addition, weather conditions being clear would tend to increase average speeds, as rain or snow tends to influence drivers to have more caution. Whether or not the driver is aware of the experiment taking place also has an impact, likely influencing drivers to slow down if they know they are being timed/watched. Lastly for this experiment there was very little traffic, however average speeds could be significantly slowed under heavy traffic. The largest 3 sources of error within the experiment were all human-related yet cover different areas of the study. Firstly, flagging errors occurred when the flagger did not properly signal to their teammates when the vehicle reached the agreed upon point, with their arms moving slightly too quick or too slow. Second, reaction time of timers led to

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discrepancies in overall times, the delay of the human eye and brain coming into play to slightly alter the data. Thirdly selection of cars, some just turning onto the road, others driving straight through, and several beginning from a full stop. These differences in acceleration assuredly lowered the data overall. Key changes may reduce the impact of the errors described in the section above. First, clarification of which part of the flagger’s arm should be looked at, and the placement of the part when the vehicle enters the speed trap. Next, the use of an auditory start to a timer may decrease delays between visual stimuli and physical starting of the timer. This could be done through an outside application, where short words such as “go” or “now” could be said to start the timer, and this would likely increase precision of data. Last, have all teams only analyze vehicles that are not obviously still accelerating when entering the speed trap. Given $350 to supplement this experiment, a high-speed, high-resolution camera would be immensely helpful in collecting accurate data. The camera ($345), along with some cheap paint, will allow the analysists to see the exact 1/240 th of a second when the car’s front wheels cross into the trap and when they exit to the same time precision. https://www.amazon.com/GoPro-HERO11-Black-Commerce-Stabilization/dp/B0C6 RKLQHZ/ref=sr_1_8?keywords=high+speed+camera&qid=1695175116&refinements=p_36 %3A25000-35000&rnid=386442011&sr=8-8 Thank you all for reading this report, hopefully the data proves helpful in keeping the community safe and drivers accountable under the posted speed limits around campus. (Below are attachments that display relative and cumulative frequency graphs, as well as raw data and summary statistics from the experiment.)

Raw data: Summary Statistics: Speed Group Vehicles Min (mph) Max (mph) (#) 12 14 0 14 15 1 15 17 2 17 19 5 19 20 3 20 22 4 22 24 4 24 26 10 26 27 5 27 29 2 29 31 4 31 32 3 32 34 4 34 36 0 36 37 4 38 39 1 39 41 1 41 43 0 43 44 0 44 46 1 46 48 0 Mode: 25 mph 50th Percentile: 25 mph 10 mph pace: 20-30 mph Percent of Vehicles in Pace: 55% 15th Percentile: 18.375 mph 85th Percentile: 33 mph Average Speed: 26.4 mph Estimated Standard Deviation: 7.63 mph Calculated Standard Deviation: 6.71 mph

Important Calculations: Average Speed: Sum of all values (speeds) / total number of values (cars) ((1 x 14.5) + (2 x 16) + (5 x 18) + (3 x 19.5) + (4 x 21) + (4 x 23) + (10 x 25) + (5 x 26.5) + (2 x 28) + (4 x 30) + (3 x 31.5) + (4 x 33) + (4 x 36.5) + (1 x 38.5) + (1 x 40) + (1 x 45)) / 54 = 26.4 mph Estimated Standard Deviation: Range of the data / 4

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45 – 14.5 = 30.5 (Range) 30.5 / 4 = 7.63 mph Calculated Standard Deviation: Sqrt(|14.5-26.4|^2 + 2|16-26.4|^2 + 5|18-26.4|^2 + 3|19.5-26.4|^2 + 4|21-26.4|^2 + 4|23 – 26.4|^2 + 10|25-26.4|^2 + 5|26.5-26.4|^2 + 2|28-26.4|^2 + 4|30 – 26.4|^2 + 3|31.5 – 26.4|^2 + 4|33 – 26.4|^2 + 4|36.5 – 26.4|^2 + |38.5-26.4|^2 + |40 – 26.4|^2 + |45 – 26.4|^2) = 6.71 mph *"I hereby declare that no copy of this document was sent via email to any recipient”*