Traffic variation through the year: Which statements correctly describe typical seasonal patterns of traffic volume (e.g., mid-winter vs. mid-summer) relative to the annual average on many Indian roads?

Introduction / Context:
Traffic engineering uses seasonal adjustment factors to convert short-term counts to annual average daily traffic (AADT). Understanding when volumes are near average versus distinctly high or low helps schedule counts and interpret data correctly.

Given Data / Assumptions:

• Typical Indian road networks with monsoon, summer, and winter patterns.
• Seasonal travel behaviour (school terms, holidays, agricultural cycles).
• No extraordinary local events skewing traffic.

Concept / Approach:

Count programmes seek months representative of annual average. Many agencies prefer shoulder seasons, avoiding extremes. April and November often sit close to the AADT in numerous regions. Conversely, winter lulls and summer peaks (school vacations, tourism, festival travel) commonly shape the seasonal curve.

Step-by-Step Reasoning:

Verification / Alternative check:

Seasonal adjustment tables from traffic agencies frequently show these trends, though exact shapes vary by region and corridor type (urban commuter vs. recreational routes).

Why Other Options Are Wrong:

• “None of these” would ignore well-documented seasonal variation patterns.

Common Pitfalls:

• Applying a single seasonal factor across very different corridors.
• Counting during holidays and assuming volumes are typical.

Final Answer:

All the above.