Fragmented road data may slow ADAS adoption in India: Here Technologies

The company said wider access to speed limits, road restrictions, lane information and road-sign data held by government agencies would help scale advanced driving applications

India’s fragmented road and mapping data could hinder the adoption of advanced driver assistance systems (ADAS) and autonomous vehicles, according to location-intelligence company HERE Technologies. Scaling these technologies, the firm noted, will require seamless access to government-held spatial data.

 

State governments and various agencies hold information such as speed limits and road restrictions in a fragmented manner, said Abhijit Sengupta, India head of HERE.

 

“It would be good for an application provider or solution provider to have such data accessible or made accessible because then it really helps to scale some of these use cases,” he said.

 

A central repository for such information will help technology providers build location-based applications such as speed-limit information and restrictions on trucks in a city. 

The challenge is complex as India moves towards greater vehicle automation levels. While L2 and L2 plus systems are assisted-driving technologies in which the driver makes decisions, moving towards L3 will require significantly more localised information on Indian roads, Sengupta said.

 

L1 handles either steering or braking, while L2 controls both but requires constant driver supervision. At L3, the system drives autonomously under specific conditions, though the driver must take over when alerted. 

Lane markings, road signs and information will be critical, with the development of such systems expected to begin on highways and expressways before moving into urban areas.

 

India’s road infrastructure and conditions add to the challenge. HERE identified delayed information on city roads and issues such as wrong-side driving among the location-data challenges that need to be addressed for advanced use cases.

 

Sengupta said high-definition mapping at centimetre-level precision is not necessary for every ADAS application. HERE sees “standard definition plus” mapping as sufficient for navigation and autopilot use cases, while more advanced systems will require greater availability of lane-level and road-sign information.

 

The company said such information is available at scale for highways and expressways, but is uneven for city roads.

 

The broader adoption of connected and electric vehicles (EVs) is also increasing demand for location intelligence. Sengupta said safety, real-time traffic information and route optimisation are becoming increasingly important to vehicle users.

 

For EV users, location intelligence can also help determine whether a vehicle has sufficient range for a journey, whether a detour is required and whether a charging point is available along the route.

 

Beyond automotive, HERE sees growing demand from logistics, ecommerce, quick commerce, ride-hailing and food-delivery businesses, particularly for first-, middle- and last-mile operations.

 

Sengupta said artificial intelligence could expand the role of location information by allowing users to make more contextual requests such as finding parking near a destination, checking whether a store will be open on arrival or identifying facilities on the appropriate side of a road.