Accelerate Connected Vehicle Development with Connected Mobility Solution on AWS and MongoDB Atlas

The Connected Mobility Solution on AWS (CMS on AWS) establishes the foundational components of a well-architected connected vehicle program for automotive companies. Automotive companies already using AWS can enable MongoDB Atlas from the AWS Marketplace and help accelerate their connected vehicle application development.

MongoDB Atlas was launched on AWS in 2016 and is now available in 31 AWS Regions globally. In 2023, MongoDB achieved the AWS Automotive Software Competency, a specialized designation from AWS that recognizes AWS Partner Network Partners with deep technical expertise and proven success in delivering automotive solutions on AWS. This helps customers have confidence when using MongoDB Atlas connected vehicle applications. Developer efficiency is at the core of MongoDB’s value proposition, and over the last several years, it has evolved from a well-known database technology provider into one of the leading developer data platform companies.

MongoDB Atlas and CMS on AWS, when used together, help remove the undifferentiated integration, or “technical plumbing” work, between vehicles and the cloud, helping accelerate the development of next-generation digital twin use cases and applications, including connected car use cases. MongoDB’s document model allows easy and flexible modeling and storage of connected vehicle sensor data. In this blog, we will look into how the MongoDB document model helps with data modeling of connected vehicles data and how this capability can be leveraged via AWS Automotive Cloud Developer Portal (ACDP).

Getting started with the Automotive Cloud Developer Portal to deploy Connected Vehicle Solution

The ACDP provides a single pane of glass for software engineers and developers to collaborate, curate, deploy, and operate their connected vehicle features (see figure 1 below). With the ACDP, developers can easily access and deploy complete solutions (templates), infrastructure (modules), and reusable code assets (components).

To create new components within the ACDP, developers can navigate to the “Create New Component” menu, where they’ll find a variety of available templates. The menu presents a selection of pre-configured templates such as CMS Alerts module, CMS API Module, and CMS Connect and Store on AWS.

Figure 1: CMS on AWS—Automotive Cloud Developer Portal

Developers, after setting up the Automotive Cloud Developer Portal in their AWS environment, need tools to accelerate end-to-end connected vehicle application development.

MongoDB Atlas Developer Data Platform

Automotive companies increasingly need to manage vast amounts of vehicle data in real-time. Use cases such as predictive maintenance, real-time diagnostics, and enhancing driver safety rely heavily on the ability to simulate and analyze a vehicle’s performance digitally. In these contexts, a flexible data platform to aggregate data from vehicles and transform it for multiple end-user applications becomes crucial.

There are three major types of challenges when creating a connected vehicle solution:

1. Data extraction challenges arise when dealing with diverse data sources and lack of data model standardization.
2. Data modeling challenges can arise as automotive frameworks are constantly evolving with new technologies and standards.
3. Data scalability challenges arise as the number of connected vehicles, and their associated data, increases.

MongoDB helps address the aforementioned challenges via the document model, highly available replica sets and horizontal scalability or zonal sharding capabilities. A traditional vehicle can have anywhere from 30 to 100 ECUs, and in more modern architectures, vehicles can have 100+ components across High-Performance Computing Units (HCPs), Domain Control Units (DCUs), and Zonal ECUs. A subset of these units generate data that need to be aggregated and transmitted to the cloud backend. Depending on the use case, the automotive developer can implement their own MQTT client for lightweight data transmission from the car to MongoDB in the AWS cloud or use AWS IoT FleetWise services to collect data from the vehicle. The AWS IoT FleetWise Edge Agent running on the vehicle can push data to MongoDB Atlas via AWS IoT Core and AWS Kinesis Data Firehose.

Before this data pipeline can be created, the vehicle engineer needs to build a virtual representation of the vehicle in the cloud. This is required to establish a common language across the vehicle fleet. The backend database needs to represent this common language in a flexible data model. In our case, we can follow Vehicle Signal Specification (VSS) by Connected Vehicle Systems Alliance (COVESA) to define a syntax and a catalog for vehicle signals. VSS includes standardized data definition for vehicle signals while ensuring same semantic understanding across different domains and also includes basic definition for interfaces working on vehicle data (w3c, etc.). Figure 2 shows how example vehicle signals can be modeled via VSS. In Figure 2, the vehicle is represented as the root node whereas all the subsystems in the vehicle are represented by various branches. We also can see attributes such as VIN, model, and brand represented as leaf nodes.

Figure 2: Example snapshot of a VSS tree

The MongoDB document model helps reduce the complexities when modelling VSS schema. Instead of storing the whole VSS schema as one big document in MongoDB, we can separate the static attributes (VIN, model, brand etc.) and sensor/telemetry data as two different data models. We do that because the connected vehicle is a write-heavy application and only the sensor data fields in the VSS data model are updated frequently. Storing small documents provides better read and write performance. Figure 3 shows the respective data models for attributes and sensor data. The attribute data model contains data that does not change whereas sensor data changes at regular intervals.

Figure 3: Separating attribute and sensor data in MongoDB

As vehicle data models evolve, MongoDB’s dynamic schema allows for easier schema redesign while minimizing application downtime. MongoDB has built-in zonal sharding to horizontally scale writes at global scale while keeping data local to the place of its origin. This provides more control over vehicle data locality.

An effective data tiering strategy can be established using MongoDB’s Atlas Online Archive. Cold data can be moved to a cost-effective object storage using Atlas Online Archive. Data tiering is a critical for connected vehicle use cases as the solution will need to hold petabytes of data once more connected vehicles come online.

Figure 4 shows an example architecture demonstrating how car telemetry can be collected and moved to the MongoDB Atlas for analysis and storage purposes. Once the data lands in a MongoDB collection, an aggregated document representing the vehicle’s data or the drivers’ data can be computed with the aggregation pipeline and stored in a physical collection or as a materialized view which can be accessed via an API endpoint. Historical telemetric data can automatically get archived into cold storage using Atlas Online Archive, This archived data is still accessible if needed via Atlas Data Federation.

Figure 4: High-level overview of MongoDB Connected Vehicle solution

Deployment of MongoDB Connected Vehicle solution on CMS on AWS

The Automotive Cloud Developer Portal uses the CMS on AWS Backstage module as its presentation layer to oversee the deployment of additional CMS on AWS modules, creating a configurable hub for developers. When you deploy the CMS on AWS, you will find the MongoDB Connected Vehicle solution as one of the options. Click on Choose and you will be redirected to the Atlas offerings on AWS Marketplace to set up your Atlas instance on AWS. With this solution, developers can focus more on innovation rather than setting up infrastructure. They can also extend the MongoDB connected vehicle solution with additional CMS on AWS modules. This helps save valuable time and resources.

Figure 5. MongoDB Connected Vehicle solution on CMS on AWS

Conclusion

Solutions like CMS on AWS and MongoDB Atlas provide customers with more efficient tools for managing and analyzing connected vehicle data. CMS on AWS helps customers achieve secure and efficient deployment and management of connected mobility features. By deploying the MongoDB’s connected vehicle solution through the CMS on AWS Automotive Cloud Developer Portal, developers can save time on setting up infrastructure and focus on innovation. To begin deploying your solution on CMS on AWS, visit Connected Mobility Solution on AWS.