Last Updated on June 18, 2026 by Statnzee Team
The Big Idea: Does Traveling 170 Miles in 2 Hours Prove I Drove 85 mph?
Suppose a driver is accused of speeding because:
- Total distance traveled = 170 miles
- Total time taken = 2 hours
Someone calculates:
Average Speed = Distance ÷ Time
= 170 ÷ 2
= 85 mph
The question is:
Does this prove that the driver was driving at exactly 85 mph at some point during the trip?
The Mathematical Answer
Yes — provided the vehicle’s speed changed continuously and there were no impossible jumps in speed.
This conclusion comes from a result in calculus called the Mean Value Theorem (MVT).
Understanding the Mean Value Theorem
Let:
s(t) = distance traveled at time t
At the start:
s(0) = 0 miles
After 2 hours:
s(2) = 170 miles
Average speed over the trip is:
(s(2) - s(0)) / (2 - 0) = 170 / 2 = 85 mph
The Mean Value Theorem says that if the distance function is smooth and continuous, then there must exist some moment c between 0 and 2 such that:
s'(c) = 85 mph
Since:
s'(t) = instantaneous speed
there must have been at least one instant when the vehicle’s speed was exactly 85 mph.
Why This Does Not Mean the Driver Was Always Driving 85 mph
The driver may have driven:
- 60 mph for some time
- 90 mph for some time
- 80 mph for some time
- Stopped at a traffic signal
Yet the theorem guarantees that somewhere during the journey the speedometer must have shown exactly 85 mph.
A Simple Example
Suppose the driver travels:
- First hour at 70 mph → 70 miles
- Second hour at 100 mph → 100 miles
Total:
70 + 100 = 170 miles
Average speed:
170 ÷ 2 = 85 mph
Since speed increased from 70 mph to 100 mph, the speedometer must have passed through:
71, 72, 73, ... 84, 85, 86, ... 99, 100
Therefore there was certainly a moment when the car was traveling exactly 85 mph.
Can This Be Used as Proof for a Speeding Ticket?
Not necessarily.
The Mean Value Theorem proves only that:
At some instant the speed was 85 mph.
It does not tell us:
- When that happened
- Where it happened
- Whether the speed limit there was lower than 85 mph
- How long the driver maintained that speed
In real life, traffic authorities usually rely on radar, cameras, GPS records, or speed sensors rather than average-speed calculations alone.
Business Application #1: Delivery Companies
Suppose a logistics company records:
- Delivery route length = 340 miles
- Completion time = 4 hours
Average speed:
340 ÷ 4 = 85 mph
Managers can conclude that at some point the truck was traveling at 85 mph.
This helps identify:
- Potential speeding behavior
- Safety risks
- Fuel-efficiency issues
Business Application #2: E-Commerce Delivery Optimization
Companies like courier services monitor delivery performance.
If a vehicle covers a long route unusually quickly, analytics systems can estimate average speeds.
The Mean Value Theorem implies that certain speeds must have been reached during the trip, helping auditors investigate route compliance.
Business Application #3: Manufacturing
Suppose a factory produces:
850 units in 10 hours
Average production rate:
850 ÷ 10 = 85 units/hour
The Mean Value Theorem says there was at least one moment when the production line was operating at exactly:
85 units/hour
Managers use this idea to study machine performance and efficiency.
Business Application #4: Website Traffic Analytics
Imagine a website receives:
8,500 visitors in 100 hours
Average traffic rate:
85 visitors/hour
Then there must have been some instant when traffic was arriving at exactly 85 visitors per hour.
Digital marketers use this principle when analyzing:
- Advertising campaigns
- Server capacity planning
- User engagement trends
Key Takeaway
The Mean Value Theorem tells us:
If a quantity changes continuously, then somewhere along the way its instantaneous rate of change must equal its average rate of change.
For the driving example:
170 miles in 2 hours Average speed = 85 mph
Therefore:
There was at least one instant during the trip when the vehicle’s speed was exactly 85 mph.
This beautiful calculus result connects mathematics to transportation, logistics, manufacturing, finance, and business analytics.
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