CS/21CASE STUDY

Autonomous Mobility
Through Testing and Automation

A major automotive subsidiary pioneered a next-generation ride-sharing Proof of Concept using autonomous vehicles. We As Web delivered a multi-layered testing strategy — iterative functional testing, ECU Test automation, Canoe protocol validation, and structured Jira feedback loops — laying a scalable testing foundation for the long-term rollout.

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At a Glance
Capabilities
Iterative Functional Testing
ECU Test Automation
Canoe Protocol Validation
Structured Jira Feedback Loops
Technologies
Canoe (Protocol Validation)ECU TestJiraPython
Delivery Model
Dedicated team · PM + Test Manager + 5 QA Engineers + Hardware Engineers
[01]Business Context

A major automotive subsidiary pioneering autonomous ride-sharing

A major automotive subsidiary sought to pioneer a next-generation ride-sharing service utilizing autonomous vehicles. The core initiative was to create a Proof of Concept (PoC) that would allow for the remote supervision and control of vehicles during operational anomalies. Developing this capability was crucial for the client to enhance cost efficiency, improve overall fleet management, and uphold the highest safety standards in an autonomous driving environment.

Key Context
Early-stage autonomous vehicle ride-sharing PoC
Need for remote supervision and control during operational anomalies
High safety standards required for autonomous driving environments
Cost efficiency and fleet management are top business priorities
[02]Client Needs

What prompted the project

The client required a comprehensive testing framework to validate the PoC's functionality — with state management and remote escalation as the two top concerns.

N/01

State Management

Monitoring and managing the vehicle's operational state, including passenger boarding, secure door and trunk closures, and real-time fault detection.

N/02

Remote Escalation Protocols

Establishing protocols for situations where automated corrections failed (e.g., a prolonged door opening) so that remote operators could seamlessly intervene using live data streams.

[03]The Challenges

Why an expert partner was required

Testing an early-stage autonomous PoC presented two unique obstacles — ambiguous requirements and physical hardware constraints.

Pre-Project ChallengeEvolving Requirements
Ambiguous Initial Specs
Due to the early-stage nature of the project, initial requirements were ambiguous and subject to continuous refinement.
Constant Reassessment
The testing team had to constantly reassess and adapt their scope to align with emerging specifications.
Impact
A rigid test plan would have been obsolete within weeks.
Pre-Project ChallengeHardware Constraints
Large Heavy Test Rig
The initial testing infrastructure relied on a large and heavy test rig.
Logistical Difficulties
Introduced significant logistical and operational difficulties for the team.
Impact
Testing velocity was bottlenecked by how fast the rig could be reconfigured.
[04]Solutions Provided

What We As Web delivered

To navigate these complexities, We As Web deployed a multi-layered testing strategy that balanced functional validation with iterative automation.

S/01

Iterative Functional Testing

Proactively identified inconsistencies in fluid requirements, collaborating closely with stakeholders to refine expectations.

Proactively identified inconsistencies in fluid requirements.
Collaborated closely with stakeholders to refine expectations and validate core vehicle functions (boarding, door security, fault detection).
S/02

Test Automation

ECU Test as the primary framework for scripted test execution, supplemented by Python-based scripts for repetitive scenarios.

Utilized ECU Test as the primary framework for scripted test execution.
Supplemented by Python-based scripts to streamline highly repetitive test scenarios.
S/03

Protocol Validation

Canoe integration to validate communication protocols — ensuring robust interaction between software components.

Integrated Canoe to validate communication protocols.
Ensures robust and reliable interaction between various software components of the autonomous stack.
S/04

Structured Feedback Loops

Jira to continuously document testing insights and drive iterative improvements aligned with the evolving PoC.

Leveraged Jira to continuously document testing insights.
Drives iterative improvements aligned with the evolving PoC — every insight feeds back into the next test cycle.
S/05

Strategic Alignment

Weekly strategic discussions with the Test Manager to align priorities, mitigate roadblocks, and refine methodologies.

Held weekly strategic discussions with the Test Manager.
Align priorities, mitigate roadblocks, and refine execution methodologies as the PoC evolved.
[05]Results Achieved

A scalable testing foundation for the long-term rollout

While the overarching project remains in the PoC phase, the testing engagement has already achieved critical milestones.

R/01
Successful automation of complex test procedures

Successfully automated complex test procedures, drastically accelerating test execution and reliability.

R/02
Refined functional testing methodologies

Refined functional testing methodologies to better handle evolving requirements.

R/03
Systematic evaluation approach

Established a systematic, highly structured approach to evaluating autonomous system performance.

R/04
Scalable testing foundation for long-term rollout

Laid a comprehensive and scalable testing foundation necessary to support the long-term rollout of the autonomous ride-sharing service.

[06]Technology & Team

Multi-layered testing for autonomous systems

A focused automotive testing stack — Canoe for protocols, ECU Test for automation, Python for glue scripts, and Jira for traceability.

Technology Stack
Canoe (Protocol Validation)ECU Test (Test Automation)Python (Scripting)Jira (Requirements Tracking & Feedback)Hardware Test Rig Integration
Team Composition
Project ManagerTest Manager5 QA EngineersHardware Engineers
[07]Conclusion

When autonomous mobility needs a testing foundation, not a one-off

An autonomous vehicle PoC cannot rely on a one-off test pass — it needs a testing foundation that scales with the program. By deploying a multi-layered testing strategy with iterative functional testing, ECU Test automation, Canoe protocol validation, and structured Jira feedback loops, we gave this automotive subsidiary a testing capability that adapts as the PoC evolves.

The result is successful automation of complex procedures, refined methodologies for evolving requirements, and a scalable foundation for the long-term rollout. For any automotive or autonomous program in its early stages, this is what a testing partnership that grows with the program looks like in production.