Here, we would like to take the opportunity to showcase some of our reference projects:
IoT connectivity, Cloud Platform, Function Development
NISAR and e:fs join forces:
Combining new ideas from the startup ecosystem with extensive experience in series development and validation we strive to change the way how automotive software is developed today.
– Test car for data recording, remote connectivity
– Cloud platform
– IoT connectivity for car-pc to cloud platform
![](https://nisar.ai/wp-content/uploads/2024/01/efs_Connectivity_data.png)
![](https://nisar.ai/wp-content/uploads/2024/01/efs_Connectivity_main.png)
Traffic Scenario Recorder based on Ring-Buffer
NISAR and e:fs join forces:
Combining new ideas from the startup ecosystem with extensive experience in series development and validation we strive to change the way how automotive software is developed today.
![](https://nisar.ai/wp-content/uploads/2024/01/efs-rungbuffer-main.png)
-Sparse Scenario Recording
-Do not record hundreds of hours and km, just record what is relevant
-Store vehicle sensor and bus data in ring buffer
-Store ring buffer content based on triggers, i.e. sharp braking
![](https://nisar.ai/wp-content/uploads/2024/01/efs-rungbuffer-data.png)
ECU remote monitoring & flashing on production line
Monitoring & flashing ECU already on the production line
Software for ECUs is increasing rapidly in size. And so is the flashing time needed at End-of-line flashing stations.
![](https://nisar.ai/wp-content/uploads/2024/01/cbox-factory.png)
With our IoT connector the ECU is already flashed while on the line, saving time at EOL.
![](https://nisar.ai/wp-content/uploads/2024/01/cbox_factory-1024x259.png)
XDP Showcase with TogetherOS
Member of the Horizon Ecosystem
Code Generation for Horizon TogetherOS from Software Architecture i.e. for a camera fusion system.
Built into NISAR Architect Design Studio
![](https://nisar.ai/wp-content/uploads/2024/01/TROS-1.png)
![](https://nisar.ai/wp-content/uploads/2024/01/TROS-ADS.png)
![](https://nisar.ai/wp-content/uploads/2024/01/TROS-Code.png)
XDP Showcase with AUTOSAR
![](https://nisar.ai/wp-content/uploads/2024/01/ads-autosar.png)
Phase 1:
Integrating Nisar ADS with ETAS AUTOSAR Toolchain, enabling the generation of AUTOSAR code from abstract architectures
Phase 2:
Enabling the bridge from pre-development in ROS to AUTOSAR via the abstract architecture
![](https://nisar.ai/wp-content/uploads/2024/01/ads-autosar_code.png)
Multi Radar Sensor Fusion
Creation of a central 360° environmental model from several corner radars in ROS
Two variants:
1.Free-Space model using occupancy grid maps
2.Geometrical obstacle representation using bounding polygons
![](https://nisar.ai/wp-content/uploads/2024/01/radar-fusion.png)
Surround View and Parking Assistant
![](https://nisar.ai/wp-content/uploads/2024/01/parking.png)
Creation of a central 360° environmental model from several cameras
Three steps:
1. Bird-eye view for the driver by merging 6 cameras
2. Detecting of free and occupied parking spaces
3. Dubbin / Reed based trajectory planner
Simulation and real vehicle
Radar-Camera-Fusion & Object-Tracking
Car equipped with radar and cameras, each with their own object tracking
• Fusion of the tracks
• Increased accuracy
• Increased robustness
• Tracking beyond the limits of the sensors’ fields of view
• Tracking of lanes and assignment of objects
• Planning the navigable space taking into account the objects’ own movement and prediction
![](https://nisar.ai/wp-content/uploads/2024/01/radar_camera.png)
AI-based Cyber Security
AI-based design wizards to enable integrating Cyber Security already in early design phases while at the same time easing the task for Cyber Security Engineers
![](https://nisar.ai/wp-content/uploads/2024/01/THI.jpg)
![](https://nisar.ai/wp-content/uploads/2024/01/cybersec-1024x412.png)
Published at AI.BAY conference, 2023, with TH Ingolstadt CARISSMA, D.Bayerl
Our test vehicle in Shanghai
![](https://nisar.ai/wp-content/uploads/2024/01/MG.png)
Test Vehicle Platform
– MG4 Mulan
Sensor Setup
– 7 Cameras – 2-8M Pixels
– 4 Fisheye cameras
– 3 LRR-Radars
Software Components integrated
– BEV Model for Perception
– HD Map Fusion
– Radar + Camera Object Fusion
– NoA Navigation on Autopilot
– Middleware: TROS, ROS and Autosar
Current Hardware Platforms
– HR J5 x 2 256 TOPs + Semidrive X9U
– HR J5 x 1 + NXP SR32G
– NVIDIA Orin + TC397
– HR J3 x 1 3 TOPs + Aurix
…additional impressions…
![](https://nisar.ai/wp-content/uploads/2024/01/additional-impressions-1024x450.png)