Is Software Reshaping and Redefining the Automotive Industry?

The automotive industry is currently undergoing a profound transformation. Traditionally, automobiles have been primarily viewed as mechanical engineering products, their value determined mainly by engine performance, chassis design, and body structure. However, this paradigm is being completely overturned. Software is not only becoming a standard feature of modern cars, but it is also redefining the essential form and development trajectory of automobiles. From Tesla’s full-vehicle over-the-air (OTA) updates to Volkswagen’s plan to increase the proportion of software developers to 60%, software is becoming the new core of value creation in the automotive industry.

The widespread adoption of software in automobiles is not accidental, but rather an inevitable result of multiple technological trends and market demands. Tesla, as a pioneer in this transformation, provides a highly compelling case study.

Tesla’s software-driven approach stands in stark contrast to traditional automakers . Its core innovation lies in building vehicles as “computers on wheels.” Tesla’s central computing architecture replaces the dozens of distributed electronic control units (ECUs) found in traditional cars. This centralized electrical and electronic architecture allows software updates to cover the entire vehicle system, not just the infotainment unit.

OTA (Over-The-Air) updates are a prime example of Tesla’s software advantage. While traditional cars have their functions fixed at the factory, Tesla owners receive regular updates that enhance functionality, optimize performance, and even introduce entirely new features. For instance, Tesla used OTA updates during the pandemic to add a “Bioweapon Defense Mode“ to its vehicles, significantly improving air filtration efficiency; software updates can also improve acceleration performance or driving range. This ability to continuously evolve fundamentally changes the lifecycle value curve of a car.

The reconstruction of the user interface and experience also highlights the central role of software. Tesla’s minimalist interior design is achieved because most functions are integrated into the central touchscreen and managed uniformly by software. This design not only reduces the complexity and cost of physical components but also creates space for personalized experiences.

From a broader industry perspective, several driving forces underpin the widespread adoption of software: advancements in semiconductor technology enable vehicles to process massive amounts of data; consumers’ expectations for personalized and intelligent experiences continue to rise; vehicle electrification reduces mechanical complexity, creating conditions for innovation in electronic and electrical architectures; and automakers’ need to transform their business models by seeking to build sustainable revenue streams through software services.

Vehicle-to-everything (V2X) technology transforms cars from isolated entities into network nodes. This connectivity has spurred three major changes:

First, enhanced safety features. The vehicle can communicate in real time with surrounding infrastructure (traffic lights, road sensors) and other vehicles to provide early warnings of potential hazards. For example, in the event of emergency braking, the vehicle can automatically send a warning signal to vehicles behind .

Secondly, improving traffic efficiency. Connected vehicles can receive real-time traffic data, optimize route selection, and reduce congestion. Urban traffic management systems can also adjust traffic light timings through vehicle data streams to achieve dynamic traffic flow optimization.

Third, a completely new service ecosystem. From real-time navigation updates and streaming entertainment to location-based business services, connected cars are transforming vehicles into mobile service platforms. Traditional luxury brands like BMW and Mercedes-Benz have already begun exploring new revenue models by offering software features such as heated seats and advanced driver assistance systems through subscription models.

Intelligent driving systems, especially autonomous driving technology, represent the most profound reconstruction of vehicle functionality by software.

A Revolution in Environmental Perception: Traditional driving relies on human senses, while intelligent driving systems use sensor arrays such as cameras, radar, and lidar, combined with complex computer vision algorithms, to build a 360-degree digital understanding of the surrounding environment. Tesla’s “pure vision” solution and Waymo’s multi-sensor fusion solution represent different technological paths, but their common core is advanced software for processing sensor data.

The Complexity of Decision-Making Algorithms: Perceiving the environment is only the first step; the real challenge lies in making safe, efficient, and ethical decisions in complex traffic scenarios. This requires machine learning algorithms to be trained on massive amounts of driving scenario data and continuously optimize the decision-making model. The development of autonomous driving software has become a frontier in the field of artificial intelligence.

Precision of Control Execution: Once a decision is made, the software needs to precisely control the steering, acceleration, and braking systems. Traditional automotive drive-by-wire technology provides the physical basis for software control, but ensuring both precise and smooth control response requires highly optimized control algorithms.

The evolution of intelligent driving will gradually change the fundamental attributes of automobiles. When autonomous driving reaches a sufficiently high level, the interior space of automobiles will be redesigned, shifting from a driver-centric approach to a passenger experience-centric approach, further expanding the boundaries of software-defined possibilities.

With automotive code now numbering in the hundreds of millions (far exceeding that of fighter jets or large passenger planes), security challenges have become unprecedentedly complex.

Functional Safety Standards: The automotive industry has established stringent standards, such as ISO 26262, covering the entire system development cycle from hardware to software. These standards require a systematic approach to identify, assess, and mitigate risks, including Failure Mode and Effects Analysis (FMEA) and Fault Tree Analysis (FTA).

Redundancy and Fault Tolerance Design: Critical systems such as braking and steering employ dual hardware and software redundancy. For example, Tesla’s Autopilot computer uses a dual-chip design, with each chip operating independently and verifying the other’s calculations. When an inconsistency is detected, the system safely degrades to a conservative mode.

Continuous Monitoring and Updates: Software-defined vehicles can monitor their own status in real time and detect anomalies through onboard diagnostic systems. More importantly, manufacturers can quickly fix discovered security vulnerabilities via OTA (Over-The-Air) updates, eliminating the need for owners to visit service centers. This forms a closed-loop security enhancement mechanism of “detection-repair-deployment.”

Network security architecture: Modern vehicles employ a layered defense strategy, including network segmentation (isolating critical control systems from infotainment systems), security gateways (monitoring in-vehicle network communications), intrusion detection and prevention systems (IDS/IPS), and secure boot mechanisms (ensuring that only verified software can run).

Data Encryption and Privacy Protection: Sensitive data collected by vehicles (location, driving habits, biometric information) must be encrypted during transmission and storage. Regulations such as the EU’s General Data Protection Regulation (GDPR) require automakers to clearly disclose the scope of data collection and provide user control options. For example, BMW allows owners to precisely control vehicle-sharing permissions and time limits via digital keys.

Secure Development Lifecycle (SDL): This involves considering security requirements from the design phase, including threat modeling, code security review, and penetration testing. Industry organizations such as Auto-ISAC (Automotive Information Sharing and Analysis Center) promote the sharing of security threat information among manufacturers to jointly address emerging risks.

Evolution of the Regulatory Framework: The United Nations Economic Commission for Europe (UNECE) Regulation R155 requires automakers to establish cybersecurity management systems and obtain type approval. The United States is also pushing for related legislation to ensure minimum standards for automotive cybersecurity.

Faced with increasingly complex software functions, ordinary car owners can make informed choices based on the following dimensions:

Understanding Core Software Capabilities: Car owners should focus on the vehicle’s fundamental software architecture, rather than just specific functions. Key questions include: Does the vehicle support OTA updates? What is the update frequency and history? Is the electronic and electrical architecture traditionally distributed or centralized? The latter typically has stronger long-term software upgrade capabilities.

Assess User Data Control: Carefully review the vehicle’s privacy policy to understand what data is collected, how it is used, and with whom it is shared. Prioritize brands that provide a clear data control interface, such as allowing users to selectively disable data sharing or view collected data.

Consider Long-Term Software Support: The lifespan of a software-defined vehicle depends not only on hardware durability but also on ongoing software support. Understand the manufacturer’s software support policies for older models, including security update deadlines and the likelihood of feature updates.

Approach Autonomous Driving Promises Rationally: Distinguish between currently available features (such as adaptive cruise control and lane keeping assist) and future promises. Focus on the system’s performance in real-world road tests, rather than simply believing marketing claims. Understand the system’s limitations and the effectiveness of driver monitoring mechanisms.

Balancing Functionality and Complexity: More software features may mean more potential points of failure and learning curves. Choose features based on actual needs and avoid paying a premium for unnecessary complexity.

Focus on Maintainability and Data Portability: As software becomes increasingly important, the issue of “right to repair” is becoming more prominent. Choose vehicles that allow third-party repairs (including software-level repairs) and ensure that personal data (such as seat settings and navigation preferences) can be easily transferred when changing vehicles.

The reshaping of automobiles by software is still in its early stages. In the future, vehicles will evolve into truly “intelligent spaces,” continuously learning to adapt to owner preferences and habits; the automotive ecosystem will become more open, with third-party developers potentially creating applications for specific car models; and the integration of vehicles with other smart devices and smart cities will give rise to entirely new service models.

However, this transformation also faces challenges: the explosive growth in software complexity may lead to unpredictable interaction failures; over-reliance on software may result in the degradation of basic driving skills; and the digital divide may make it difficult for some groups to adapt to highly digitized cars.

Ultimately, successful automakers will be those that find a balance between mechanical engineering traditions and software innovation capabilities. For consumers, understanding how software defines the car is not only necessary for choosing the right product, but also essential for adapting to a new era in which the role of the automobile is being fundamentally redefined.

Software is no longer just a component of cars—it is becoming the brain, nervous system, and even the soul of cars, determining where this century-old industrial product will go.

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