When ADAS and Cruise Control Go Dark: AI Delivers a Breakthrough to Resolve a Chronic Failure

This is the final blog in a spotlight series showcasing real-life case studies of OEMs who were able to utilize their connected vehicle data, powered by ML and AI to detect component failures earlier, reduce warranty costs, and improve customer satisfaction at scale. 
Each case highlights how Upstream’s Proactive Quality Detection (PQD) solution helps OEMs to accelerate root-cause analysis (RCA), severity assessment, and prioritization of vehicle quality issues using AI-driven insights. 

Read the first blog here.
Read the second blog here.
Read the third blog here.

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Modern vehicles are more software-defined than ever before. From lane departure warnings to adaptive cruise control, advanced driver assistance systems (ADAS) sit at the heart of safety and customer trust. But when these systems intermittently fail, the result isn’t just driver frustration, it’s a potential safety hazard, a spike in warranty claims, and a dent in brand reputation.

This real-life case study highlights how a global OEM faced recurring ADAS and cruise control malfunctions across multiple vehicle models and geographies, and how advanced AI-powered helped uncover the true root-cause, prevent unnecessary part replacements, and restore driver confidence.

This case is also the fourth blog in a spotlight series showcasing real-life case studies of OEMs who were able to utilize their connected vehicle data, powered by ML and AI to detect component failures earlier, reduce warranty costs, and improve customer satisfaction at scale. 

Each case highlights how Upstream’s Proactive Quality Detection (PQD) solution helps OEMs to accelerate root-cause analysis (RCA), severity assessment, and prioritization of vehicle quality issues using AI-driven insights.

When Inconsistent ADAS Failures Undermine Safety and Customer Trust

Drivers began reporting sudden failures in their forward collision and lane departure systems, along with the inability to activate cruise control. Service technicians found a trail of error codes in the ADAS ECU, but the malfunctions were inconsistent, appearing in one visit and vanishing the next. That inconsistency complicated diagnosis and often led to inconclusive service outcomes.

The OEM’s field engineers, operating under pressure to keep customers safe and satisfied, cycled through potential fixes. Sensors were replaced, cameras swapped, and alignment checks carried out. Yet none of these interventions produced lasting results. The same vehicles came back to dealerships. Warranty claims mounted. And most concerning of all, drivers were left without critical safety features in situations where they were needed most.

What made the challenge particularly complex was its breadth. The fault appeared in different vehicle types, spanning multiple production years and global markets. Without a clear technical pattern, traditional investigation methods only prolonged the cycle of trial-and-error.

Illustration:Advanced Driver Assistance Systems (Source: Upstream)

Leveraging Live Vehicle Data and Service Data, Upstream’s PQD Exposed the Hidden Root-Cause 

The breakthrough came not from the service bay but from the data. By analyzing repair order histories, warranty claims, and connected vehicle telemetry at scale, a correlation emerged: the failures consistently traced back to a single version of the lane keep assist camera calibration software.

The calibration mismatch disrupted the delicate synchronization between sensors and the ECU, prompting the ADAS system to shut down and trigger a cascade of diagnostic trouble codes (DTCs). Once identified, the solution became clear. The OEM initiated an over-the-air (OTA) campaign to update the calibration software fleet-wide, restoring ADAS functionality without the need for hardware interventions. For vehicles unable to receive the update remotely, a technical service bulletin provided dealerships with clear instructions to apply the fix during service appointments.

Equally important, the OEM set up ongoing monitoring to ensure that any future reoccurrences would be detected quickly and addressed proactively.

The Outcome: Transforming Recurring Failures into Targeted, Lasting Fixes

The results were significant. By shifting from manual troubleshooting to AI-powered and data-driven analysis, the OEM was able to isolate the problem in weeks rather than months. Customers saw their ADAS and cruise control systems restored to reliable operation, and dealerships finally had a consistent path to resolution. Warranty costs declined as unnecessary parts replacements were avoided, and the brand was able to demonstrate responsiveness and accountability to its drivers.

The issue reinforced that after-sales quality is no longer limited to mechanical systems. In modern architectures where safety-critical functions are deeply tied to software, identifying and addressing defects requires new tools and new approaches.

This case shows how a recurring, difficult-to-diagnose failure can become an opportunity to strengthen both processes and technology. By drawing on telemetry, DTC analytics, and repair data, the OEM not only resolved a persistent issue but also built capabilities to detect similar problems earlier in the future.

As automakers move further into the era of EVs, hybrids, and software-defined vehicles, these capabilities are not optional. They are essential to maintaining safety compliance, preserving customer trust, and protecting warranty budgets. Software failures, left undetected, can ripple quickly across fleets. But with advanced analytics in place, OEMs can catch those failures before they become systemic, turning what once might have been a reputational crisis into a demonstration of resilience and technical leadership.

Explore Upstream’s PQD platform to see how early quality issue detection and contextual analysis can support faster RCA, reduce warranty exposure, and improve customer satisfaction.