TCS AI-based Autonomous Vehicle Platform (TAAP)

TCS AI-based Autonomous Vehicle Platform (TAAP) is an AI-powered, data-centric engineering platform that helps automotive OEMs and Tier-1 suppliers accelerate development and validation of ADAS and Autonomous Driving systems. TAAP brings the complete AD/ADAS engineering lifecycle into one connected environment on AWS.

Development/Validation vehicles generate TBs of sensor data per vehicle per day. Engineering teams must ingest, synchronise, annotate and curate this data, locate relevant driving scenarios, train algorithms and validate across physical and virtual environments — today with fragmented tools and manual handoffs.

Four Engineering Phases:

• System Design & Algorithm Development – perception algorithms for RADAR, LiDAR and camera, sensor fusion, control, localisation, path planning, V2X
• Data Collection & Management – vehicle-side acquisition, edge transfer, bulk and event-driven ingestion, quality validation, cataloguing, lifecycle management.
• Data Analytics – metadata tagging, scene extraction, automated ground truth, 2D/3D annotation, semantic segmentation, scenario identification and search.
• Verification & Validation – remote execution and virtual validation spanning MIL, SIL, HIL and DIL, real-to-virtual and virtual sensor modelling, test matrix management.

Key Highlights of TAAP – AWS Integration

• Scalable AD/ADAS Data Foundation - Amazon S3 provides the central data lake for raw/event data, processed and curated engineering datasets, extracted scenarios, model artefacts and reports, with independently governed data zones.

• Intelligent & Event-Driven Ingestion - AWS IoT Core ingests event data from in-vehicle gateways; AWS CLI S3 Copy supports bulk transfer from copy stations; AWS Lambda triggers processing on raw, parsed and scene objects.

• Automated Workflow Orchestration - AWS Step Functions orchestrates scene extraction and identification workflows; Amazon MWAA (Managed Airflow) coordinates scheduled and dependency-driven engineering pipelines.

• Large-Scale Data Processing - Amazon EMR processes vehicle signal data across CAN, Ethernet, GPS and video; Amazon Bedrock supports generative-AI assisted auto-annotation of video and LiDAR; Databricks on AWS supported where selected for the customer deployment.

• Containerized Deployment - Amazon ECR stores TCS R-To-V, SIL and service container images; Amazon ECS / EKS run modular TAAP services with elastic scale.

• Security, Networking & Governance - AWS IAM for access control, AWS KMS and Secrets Manager for encryption and secrets, VPC with private subnets, AWS Direct Connect / Site-to-Site VPN for customer connectivity, CloudTrail and CloudWatch for audit and monitoring.