You have been given Network Survey Vehicle’s data

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

Part One:

You have been given Network Survey Vehicle’s data (2 files) for one entire highway stretch. NSV are specialised vehicles which run on highways to collect data on the condition of the pavement and furniture on the road. NHAI collects similar information for all the highways under NHAI on a routine basis.

 

Locations on a highway are identified through chainage, direction and lane depending on the data being collected. A chainage marks the location in meters from a reference point in a highway, the direction is in reference to the starting point and decides LHS or RHS and Lane decides the location within a direction.

 

For eg.

 

• Width of the shoulder is described between start chain-age and end chain-age and direction.

• Carriageway furniture such as information boards are having single chainage and direction.

 

For the problem statement, you need to identify the following things from the data:

 

1. Visualize the LaneIRI (roughness) as colour points depending on the value of IRI (choose the red-green scale but you’ll need to research about IRI to figure what colour to use for low or high numbers. Green should represent a smooth surface) on a map within your Python notebook. Each 100m stretch in a lane should be represented by a single point. You may choose the lat-long of the start chainage of the record. Basemap can be any.

 

2. List of continuous stretches where the LaneIRI in the lane has the same integer value (0, 1 or 2, floor value). The idea is to identify continuous stretches of similar IRI condition. Once each stretch has been identified:

2.1. Choose appropriate visualization to examine the relationship between the size of the stretches versus the common IRI of the said stretches and document insights if any.

2.2. Tabulate the number of continuous stretches in each IRI bracket (0, 1, 2… so on)

Attachments:

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