The past year has been tumultuous for the automotive industry. The recession has had a dramatic impact on the market, as have the ongoing issues of chip shortages, rising interest rates, and an overall economic uncertainty. Chip shortages, stemming from supply chain disruptions, have persisted since the pandemic and are now further compounded by various geopolitical factors. As a result, we’ve witnessed a substantial reduction in vehicle availability over the last year as well as inflated prices. It is also worth mentioning that in an effort to combat inflation, central banks have increased interest rates which are negatively impacting loan affordability. All this has deterred buyers and resulted in lower car sales across the US and Europe.
While many companies may not want to acknowledge it publicly, they have had to discontinue numerous promising projects. However, despite these challenges, there have been quite a few positive developments and a great deal of technological advancement. Certain trends have become more firmly established, and we fully anticipate them to become even more prevalent in 2024. Today, we will highlight 3 of those trends.
Trend #1: ADAS advancement and more L3 cars
Last year, we saw an increasing number of manufacturers intensifying efforts to build L3 capabilities. Consequently, we anticipate exciting advancements in advanced driver-assistance system [ADAS] technologies in 2024.
For instance, BMW is evidently on the verge of releasing an L3 vehicle with autonomous features that is not limited to specific highways (as was the case previously), but extends to other types of roads, provided specific conditions are met. Following this, we expect close competitors such as Mercedes-Benz and Volkswagen AG to follow suit.
What technologies should we be ready for in L3 vehicles?
First of all, it’s the high-definition maps (HD Maps). Going beyond traditional GPS, these maps offer centimeter-level precision with lane markings, traffic lights, and obstacles. This year, we are likely to see a deeper integration of this tech with ADAS and autonomous driving systems that will enhance localization, route planning, etc.
LiDARs and camera sensors are both extensively used already. While still expensive, LiDAR sensors offer advanced 3D imaging capabilities, making them a compelling choice for L3 car manufacturers, especially since they are able to handle challenging weather conditions and complex environments. In 2024, we might finally see more affordable solid-state LiDAR solutions entering the market.
On the other hand, there’s also a growing interest in just using stereo cameras with neural networks for L3 cars. Avenga conducted a feasibility study and developed a Proof of Concept (PoC) demonstrating that, despite computation limitations in runtime environments on embedded devices, it is possible for auto manufacturers to integrate sophisticated ADAS and autonomous driving functionalities into their vehicles while only using relatively inexpensive camera sensors and neural nets. Wide-mounted stereo cameras are effective in producing high-resolution depth maps and are comparable to those obtained with LiDARs.
In line with this trend, we also anticipate significant innovations in human-machine interfaces (HMI), which will probably include advancements in natural language interfaces (NLIs) with AI.
This would enable a more intuitive experience and allow users to adjust ADAS settings with voice commands for a smoother and more natural experience, thus being less reliant on menus.
Augmented Reality (AR) Displays are worth mentioning too. The futuristic displays overlayed on windshields that provide relevant information about traffic signals, lane changes, and surrounding objects may finally become available in some relatively affordable vehicles and not just exist in concept cars.
L3 for the people
In 2024, we might finally witness the democratization of L3.
Initially exclusive to luxury cars, L3 functionality is expected to gradually trickle down to more affordable models as costs decrease and production scales up. This could accelerate a broader adoption. And once adoption becomes widespread enough, commercial vehicles like trucks and buses will also benefit greatly from L3’s efficiency and safety gains. As a result, we might see pilot L3 fleet programs emerging with early deployments in controlled environments such as highways or dedicated routes.
However, certain issues need to be dealt with before that can happen. While there is a United Nations Economic Commission for Europe (UNECE) framework for L3, countries are still developing their own regulations, which is creating inconsistencies and delays for manufacturers targeting global markets. Additionally, ethical dilemmas surrounding the responsibility in an L3 accident need addressing before we can anticipate broader public acceptance.
Trend #2: lots of AI, with GenAI leading the way
In 2023, numerous Western and Asian car companies embraced advanced AI technologies for both internal operations and customer-facing applications, a trend that is likely to strengthen further this year.
Internal applications
- Design and engineering. AI analyzes vast datasets of design parameters and simulations in order to optimize aerodynamics, fuel efficiency, and safety features. GenAI can generate innovative lightweight material designs and prototype ideas.
- Manufacturing and supply chain. AI-powered robots automate paint application, welding, and assembly tasks, enhancing efficiency and accuracy. Predictive analytics optimize inventory management and prevent production line disruptions.
- Quality control and maintenance. AI analyzes real-time sensor data to detect potential malfunctions and predict component failures, preventing costly breakdowns and repairs.
- Cybersecurity. AI monitors vehicle networks for suspicious activity, protecting against cyberattacks, and ensuring data and passenger safety.
- Employee training and optimization. AI-powered training platforms tailor learning programs to individual technicians’ needs, upskilling the workforce and optimizing performance.
Customer-facing applications
- Personalized driver assistance. AI personalizes ADAS features based on individual driving styles and preferences, enhancing safety and comfort. GenAI can generate contextual recommendations for route optimization and real-time alerts for hazards.
- Predictive maintenance and service scheduling. AI analyzes vehicle data to predict maintenance needs and automatically schedules appointments, ensuring optimal vehicle performance and customer convenience.
- Virtual showrooms and test drives. GenAI creates immersive virtual showrooms where customers can explore and configure vehicles, even taking virtual test drives through various scenarios.
- Personalized after-sales support. AI-powered chatbots answer customer questions, schedule appointments, and diagnose minor issues remotely.
The use of AI for infotainment deserves special attention, being as it is one of the most popular AI applications in the automotive industry. Here’s how AI algorithms are being used:
Personalized experiences
- Virtual assistants like Amazon’s Alexa and Google Assistant understand natural language commands, allowing drivers to control car functions without taking their hands off the wheel or their eyes off the road.
- AI analyzes the driver’s data to personalize the infotainment experience, suggesting specific music playlists or preferred routes based on past driving habits.
Optimized navigation and routing
- AI-powered navigation systems analyze real-time traffic data, weather conditions, and road closures to provide efficient and up-to-date routes.
- AI predicts traffic patterns and congestion, suggesting alternative routes to save time and reduce frustration.
Enhanced safety features
- AI-powered cameras and sensors detect signs of drowsiness or distraction, alerting the driver or activating safety features to prevent accidents.
- AI analyzes sensor data to identify potential hazards, providing real-time alerts or taking evasive action to prevent collisions.
Examples of AI-powered infotainment systems