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The impact of Gen AI on the next generation of transportation

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2024-03-06 14:50:13513browse

Next-generation transportation relies on electronics, sustainability, and experience at the core of its design, and Gen AI has an impact on every mode of the envisioned next-generation transportation ecosystem. The market has five specific focus areas: EV (electric vehicles), AV (autonomous vehicles), Micro mobility (first mile connectivity), Hyperloops (ultra-fast public transportation) and UAM (urban air mobility). There are many evolutions and changes, such as eVOLT (electric vertical takeoff and landing) or integrated signals for traffic control management. There are many areas that are evolving, such as intermodal integration (seamless route integration), sustainability (vehicle design), connectivity and automation (traffic management, alternatives), shared mobility (resource sharing and vehicle footprint reduction) . The transformation of the transportation sector provides endless opportunities for Gen AI as an important part of native technology.

Gen AI对下一代交通领域的影响

Gen AI has revolutionized the fields of autonomous driving, route optimization, obstacle avoidance and self-management (parking, blind spots, etc.). However, we need to expand our horizons to effectively manage the environment and achieve worry-free transportation. We will focus on 3 key areas: user experience, efficiency and performance, and security.

User Experience

The experience before taking a ride can be divided into two different areas: purchase experience and ride selection experience. Gen AI can influence purchasing decisions based on features, personal preferences, affordability, sustainability, and comprehensive insurance costs based on driving history. In this process, using VR/VR headsets for test drives and combined with historical data beyond social media aggregation, Gen AI can customize personalized character selections to change the overall ride experience.

The used car market size is expected to be 31.62 billion US dollars, so data analysis and recommendations for leasing, purchasing and used cars are performed through the Gen AI system, vehicle history analysis based on VIN and effective prediction of service life based on car models and vehicle usage The terrain, accident history, etc., can add value to the buyer.

Ride selection is another area where artificial intelligence will have a huge impact. Travel mode aggregation, environmental data aggregation, prediction of the most cost-effective transportation across segments, optimal timing, and transportation integration will be key to efficient transportation. Gen AI will play a key role in urban transportation with its ability to predict optimal routes and cost-effective transportation options. There are other areas including POI, travel/month and travel budget management that will be effectively offloaded to top Gen-AI based travel apps.

Efficiency and Performance

Efficiency and performance in urban transportation is another area with a range of use cases that can be effectively served through Gen AI integration. While predictive maintenance, remote inspection and analysis of internal components are in any case part of the standard. Gen AI can provide real-time guidance to drivers by recommending acceleration and braking, several key parameters that control the longevity of electric vehicles, based on the environment (traffic, weather) and expected traffic flow. Gen AI can help enable adaptive braking and regeneration mechanisms by determining the amount of energy temporarily stored and the mechanisms to dissipate or reintroduce it into the system based on the scenario. Gen AI can effectively manage powertrain control and adjust the delivered power by optimizing the torque delivered in specific situations based on predictions from real-time data.

The performance of a vehicle is affected by many factors, of which climate and terrain are the most important. A range is set for each vehicle change, but actual consumption depends on climate control and driving terrain. Compared with flat roads, driving on hilly terrain consumes 10%-20% more energy. Gen AI technology can be effectively used for trip planning, determination of charging frequency, and optimal distance and terrain selection based on routes. This advanced artificial intelligence system can analyze the actual situation of the vehicle and provide the driver with the best suggestions to improve driving efficiency and save energy consumption. With Gen AI’s intelligent computing power, driving

can easily complete a network consisting of docking stations, charging points, transportation integration, safety and terrain planning using Gen AI-based predictions, current inventory status of specific docking points Micromobility. Transfer times, average ride time based on age, gender, micromobility patterns, user health, etc.

Driving behavior can be adjusted based on the driver profile, including role, suspension control, steering, braking and acceleration, with precise predictions made through Gen AI.

Security

Next-generation security in transportation brings a wide range of opportunities through Gen AI, some of which are already implemented in easily accessible spaces such as facial recognition and door control. But on the other hand, the attack surface increases with external communications, including V2X using DSRC (Directed Short Range Communications) as well as standard WIFI and cellular technologies. GenAI can be integrated with security systems to play a key role in analyzing patterns and generating usable traffic. ECUs rely heavily on real-time operating systems such as Autosar, QNX or custom versions, and there is a range of possible security attacks. GenAI-based systems can detect traffic patterns and issue alerts or prevent non-standard parameter modifications. Gen AI, used to manage the valid state of various vulnerable parameters, can be managed in an isolated namespace and pass valid parameters back to the ECU for operation.

While Gen AI opens up many possibilities for transportation modernization, new mechanisms and synthetic data for effective modeling scenarios will take time. Hopefully, as Gen AI expands its capabilities and becomes more efficient in interpreting logic, it will be able to dramatically change the transportation industry in the coming years.

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