Case study

ADAS Solution for Electric Vehicles

We enriched an electric vehicle’s braking, steering, lighting, and power supply systems for safer and more efficient driving

Key features

  • Activate automatic braking in emergency situations

    Activate automatic braking in emergency situations

  • Extend visibility with adaptive headlights

    Extend visibility with adaptive headlights

  • Provide smarter battery power consumption

    Provide smarter battery power consumption

Industry: Automotive, LBS
Headquarters: US
Market: US
Team size: 5 members
Cooperation: 2017 – present

ADASIS / AWS / Docker / OpenGL / Python / Qt

About the client 

A young Silicon Valley startup, our client is renowned for their ambitious fully electric hypercar concepts that are destined to define our future. Fusing the best from the tech and automotive domains, the company is working hard to bring electric vehicles mainstream with exceptional IoT connectivity. Our client’s prototypes boast more energy by weight than their closest competitors and feature extended connectivity, state-of-the-art infotainment systems, a neat interior design, and even aromatherapy.

The company is rapidly growing and crossed the thousand-employee mark just two years after its inception. They’re currently developing their first manufacturing facility, with planned investments topping one billion US dollars.

ADAS Solution for Electric Vehicles

Our client came with the challenge

The automobile is accelerating into a new era. The electricity is hot on the heels of gasoline and diesel as the main source of energy in cars. At the same time, highly automated systems are taking over from humans as the main operators of motorized vehicles. 

Recognizing this, our client has invested lots of effort into developing cutting-edge electric vehicle prototypes equipped with advanced driver assistance systems (ADAS). On the rocky road to fully automated driving, our client needed expert help implementing a navigation component and a digital horizon solution. Pulling accurate map and traffic data from the cloud, this digital horizon solution would allow cars to view the road a few kilometers ahead and react preemptively for better safety, efficiency, and comfort. 

Map data, along with navigation and digital horizon software development kits, were supplied by the industry leader in location-based services (LBS) and a significant actor in the ADASIS forum. We had already worked with this LBS provider, so integrating their map data and SDKs for our new client simply built on our past experience. 

Intellias developed the solution 

One of the key challenges that we faced lay in implementing the latest ADASIS v3 protocol. This protocol enables ADAS apps to access map data, vehicle positions, and vehicle speed for smarter emergency braking, better predictive headlights, and lower power consumption. At the time, v3 existed only as a specification, however, while v2 had long been in operation. Compared to ADASIS v2, the newer v3 offered benefits such as detailed lane and line geometry, centimeter-level resolution, enhanced vehicle position messages, and complete intersection messages.  

We started by analyzing the ADASIS v3 specification to learn how protocol data was structured and what it was used for. Next, we filled the data structures that formed ADASIS messages with definite values coming from map, traffic, and vehicle sensor data. As a result, we deployed a fully viable v3 implementation, entirely tested and adapted to our client’s requirements. Our team has become one of the first to implement this new standard in the automotive industry. 

We also developed a custom positioning engine that reads a vehicle’s exact coordinates from our client’s legacy positioning service, converts them to the new format, and communicates them to ADASIS. We came upon one significant obstacle while developing this engine, however: we didn’t have sufficient access to our client’s positioning service through their low-level API due to unforeseen technical issues. To get around this, we used the Android Location API to get position updates. Although this workaround was prone to causing time delays and poor performance of the coordinate converter, it was sufficient to unblock our work during the initial development phase.

We’ve achieved great results together 

Working with our client in a distributed development environment, Intellias has allowed our LBS partner’s core team to stay focused on their main responsibilities: eliciting requirements, integrating map data and navigation solutions, managing releases, and deploying products.

Our engineering DNA and expertise in developing location based solutions for the automotive industry enabled us to bring our client’s ADAS solution for electric vehicles to life. Our client is benefiting from increased output, improved flexibility in handling ever-changing development goals, and decreased administrative overhead. 

Our expertise has helped our client 

  • Increase bandwidth 100 times compared to the classic CAN bus thanks to Ethernet support 
  • Overcome the CAN bus 8-byte message limit  
  • Share predictive information to assist drivers’ decision-making 
  • Fine-tune active safety aids for adaptive cruise control and headlights 
  • Embed features for more efficient battery power consumption and regeneration 
  • Implement high-precision distance computations and lane markings for ADAS 
  • Reduce data volumes for intra-vehicle communication 
  • Design a proprietary positioning engine that takes full advantage of ADASIS v3 


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