Road Geometrics Design Basis in India Explained

Designing road geometrics, such as lane width, curves, and sight distance, requires considering the traffic volume the road will carry. It's impractical and economically unfeasible to design a road to handle the absolute peak traffic volume that might occur only a few times a year.

Instead, highway engineers use a specific traffic volume called the Design Hourly Volume (DHV). The DHV represents a traffic volume that is exceeded only for a certain number of hours per year. This approach balances the cost of construction with the desired level of service for the road users.

In India, as per standard practices (often aligned with IRC guidelines), the road geometrics are designed based on a specific percentile of the highest hourly traffic volumes recorded over a year.

Let's look at the options and what they represent:

• 98^th highest hourly traffic volume: This is very close to the absolute peak hour. Designing for this volume would result in very wide roads and high construction costs, which might not be justified for the few hours a year this volume occurs.
• 85^th highest hourly traffic volume: This is still a very high volume, meaning the road would be designed for conditions that occur only for a limited number of hours annually.
• 50^th highest hourly traffic volume: This represents the median or average of the highest hourly volumes. Designing for this might lead to congestion during the actual peak hours.
• 30^th highest hourly traffic volume: This volume is the standard commonly adopted for geometric design in India. It represents the traffic volume that is exceeded only for 29 hours in a year (365 days * 24 hours = 8760 hours in total; the 30th highest hour volume means the volume is higher than this for the top 29 hours). Designing for this volume provides a reasonable level of service for the majority of the year without excessive construction costs.

The choice of the 30^th highest hourly volume as the basis for road geometric design is a widely accepted practice in highway engineering. It provides a good compromise between the cost of construction and the operational performance (level of service) of the road for a significant portion of the year.

Therefore, the road geometrics in India are designed for the 30^th highest hourly traffic volume.

Revision Table: Road Geometrics Design Traffic

Additional Information on Traffic Volume for Highway Design

Understanding traffic volume is crucial for highway design. Here are some additional points:

• Annual Average Daily Traffic (AADT): This is the total volume of traffic for one year divided by the number of days in the year. While AADT gives a general idea of the road's usage, it doesn't capture the peak hour variations needed for geometric design.
• Hourly Volume: Traffic volume varies significantly throughout the day and year. Peak hours, typically during morning and evening commutes, have much higher volumes than off-peak hours.
• K-factor: This is the ratio of the Design Hourly Volume (DHV) to the Annual Average Daily Traffic (AADT). It represents the proportion of daily traffic occurring during the design hour. $K = \frac{\text{DHV}}{\text{AADT}}$. The K-factor is used to estimate DHV if only AADT data is available.
• Directional Distribution (D): On many roads, traffic is heavier in one direction during the peak hour (e.g., inbound in the morning, outbound in the evening). The directional distribution factor (D) is the percentage of DHV travelling in the peak direction. $D = \frac{\text{Peak Direction Hourly Volume}}{\text{DHV}}$. The design of the number of lanes often considers the peak directional hourly volume.
• Level of Service (LOS): This is a qualitative measure describing operational conditions within a traffic stream and their perception by motorists and passengers. LOS ranges from A (free flow) to F (forced flow/breakdown). Geometric design based on the 30^th highest hourly volume aims to provide a desirable Level of Service during this design hour.

The choice of the 30^th highest hour is based on extensive studies showing that providing capacity for volumes higher than this yields diminishing returns in terms of user benefits compared to the increased construction costs. Conversely, designing for a lower percentile would lead to frequent congestion and poor Level of Service.