By: Chiara Accardi
Dreams of driving a futuristic talking car, like KITT in the American action show Knight Rider with David Hasselhoff, sparked our imaginations and opened our minds to the possibilities of collaborative interactions with our vehicles. Amazingly, today’s advances in generative AI make these futuristic interactions with our vehicles a near-term reality. To examine how this is possible and to see what types of applications are possible in interactive vehicles, we interviewed Dr. Brian Glassman, an expert in generative AI and the automotive industry.
Dr. Glassman is a product management thought leader, a mechanical engineer, and holds a Ph.D. in Product Innovation from Purdue University. He is currently the Chief Product Officer at AInspire.ai, a generative AI products and consulting company. He began the interview by providing his background and experience in the automotive industry, then described how generative AI could improve the driving and mobility experience. Finally, he outlined a comprehensive series of high-impact use cases for applying generative AI to enhance various aspects of the driving experience.
We started the interview by soliciting Dr. Glassman’s background in the automotive domain. “My fascination with advancing vehicle technologies traces back to my undergraduate studies in mechanical engineering,” he stated. “As a contributing member of my university’s Formula SAE team during my undergraduate years, I had the invaluable hands-on opportunity to design and engineer several automotive systems.” He continued, “However, my thoughts on using technology to enhance the driving experience persisted through my graduate work and onto my doctoral degree in Product Innovation from Purdue University.”
“Interestingly enough, over the course of my career leading product management initiatives and departments, I cultivated a rather unique hobby,” Dr. Glassman added. “This hobby involved purchasing full-size race car kits, assembling them in my garage, and integrating the latest technologies into them, ranging from infotainment systems to telemetry instrumentation.”
Dr. Glassman stated, “Interestingly, my career trajectory has come full circle back to the automotive domain when I assumed a leadership role at an automotive software company developing artificial intelligence solutions for Tier 1 automotive suppliers. Our efforts at this firm center around crafting software-based applications that leverage AI technologies to enhance safety and the range of electric vehicles.”
“However, the immense potential of generative AI was too compelling to disregard, so I pivoted and established a new company, AInspire.ai, dedicated to developing high-value generative AI products and providing thought leadership on managing generative AI as a function,” Dr. Glassman mentioned. He elaborated on a recent project in which he led his team to create generative AI use cases for the automotive industry, particularly those focused on enhancing the driving experience. Under his supervision, they then systematically evaluated, prioritized, and examined the technologies needed to deploy each solution in modern vehicles.
Subsequently, we asked for Dr. Glassman’s perspective on how generative artificial intelligence can catalyze and shape the future of the driving experience. He provided the following background: “First, allow me to offer some contextual background on generative AI. There are several branches of this technology, with the prominent being large language models (LLMs), such as those popularized by OpenAI’s ChatGPT and Anthropic’s Claude.
As of mid-2023, certain LLMs have the capability to engage in vocal conversations through smartphone applications, facilitating fluid verbal bi-directional conversations. The speech-enabled features allow them to answer questions, perform translation to different languages, conduct web searches, answer complex questions, and more. This alone unlocks tremendous potential to enhance the automotive driving experience.”
He continued, “In the vehicle, engaging in spoken dialogue with the AI would be the preferred mode of interaction due to convenience and safety. Moreover, the vehicle’s interconnected systems, including navigation, infotainment, environmental control, and vehicle management, provide the AI with the necessary connectivity to cater to a wide range of driver and passenger needs when planning and carrying out the journey.”
When asked about specific use cases for in-vehicle generative AI, Dr. Glassman’s response was insightful. He categorized generative AI-powered automotive applications into seven distinct domains: navigation, vehicle diagnostics, environmental comfort, entertainment, driving safety and training, and autonomous mobility solutions. Within each of these areas, Dr.
Glassman identified his pick, the enjoyable solution, and finally the innovative implementation. The following section of the article provides his generative AI use cases for enhancing the driving experience.
Use Cases for Generative AI in Automotive Navigation
Collaborative Trip Planning
In a fluid conversation with the AI, you can inform your navigation system of your desired destination, the AI can provide routing options based on criteria such as the quickest, efficient, or scenic route along with arrival times all without looking at the navigation screen.
Virtual Tour Guide
Gone are the days of hiring a tour guide; your vehicle’s AI can now provide verbal city tours, complete with facts about historical sites, interesting trivia, and highlights of important places. It can even plan a navigation route around the area based on the time you have available.
Errand Planner
Planning multiple stops can be challenging based on the time of day, traffic conditions, and store hours. In a conversation with an AI, you can inform it of your scheduled events and important errands, and the AI can plan a multi-phase trip that accomplishes all your goals in an optimized manner.
Use Cases for Generative AI in Vehicle Diagnostics
Your Maintenance Professional
Maintaining your vehicle is a chore, but now your AI can guide less handy drivers verbally on how to check their tires, maintain fluid levels, and conduct safety checks, especially for longer trips.
Vehicle Performance Insights
For driving enthusiasts, a vehicle’s performance is paramount. Now, your in-vehicle AI can provide engaging insights tailored to motoring enthusiasts, such as remaining range, assessed driving style analysis, and real-time engine health status – all available on demand through natural conversation.
AI Mechanic
Vehicle error codes or dashboard notifications to seek service are not just annoying, they can be a safety hazard. Having an AI that can verbally explain the error code and possible driving and safety implications is not only helpful in planning repairs, it is also key to increasing safety and the driver’s knowledge of the situation.
Use Cases for Generative AI to Enhance Vehicle Comfort
Personalized Climate Control
We all know someone who is particular about the temperature in their vehicle. Now, with AI that can recognize faces, voices, and the locations of passengers, the climate control system automatically adjusts to each person’s preferred settings, ensuring a comfortable ride for everyone.
Maximizing EV Range
Range anxiety is a common concern for electric vehicle drivers. With the help of AI recommendations, drivers can optimize cabin conditions to maximize their vehicle’s range while still maintaining a comfortable temperature. The AI will also provide information on the potential range gains from the adjustments made.
Use Cases for Generative AI in Creating Fun Driving Experiences
Trivia Games
Long road trips can get boring, but a trivia game can keep things lively. Your AI assistant can ask trivia questions based on categories the passengers enjoy, keep score, and even tell jokes to create a fun driving experience.
In-Car Karaoke
Everyone knows those who love to sing, and with an AI-powered karaoke system with lyrics pulled from the internet, trips become entertaining singalongs. Lyrics for songs from passengers’ devices display on the screens, turning drives into memorable bonding experiences.
Digital Storyteller
Keeping children engaged during long drives can be tough, but generative AI can create captivating stories with life lessons tailored to kids of all ages. This helps reduce stress on the driver and parents throughout the journey.
Use Cases for Generative AI that Improve Driver Safety
Situational Awareness
Late night drives and long trips can be tiring, making it easy to get distracted and encounter dangerous situations. Your AI assistant can stay alert, monitoring driving conditions and your attentiveness, gently notifying you of potential hazards when needed.
Driving Skill Gamification
New drivers looking to build their skills could benefit from an AI coach that encourages smooth, safe driving. Receiving real-time feedback and positive reinforcement of good habits is a fun, engaging way to develop better driving behaviors.
Use Cases for Generative AI that Improve Autonomous Driving
Voice Control for Self-Driving Cars
While self-driving technology is still evolving, autonomous vehicles will need to understand and follow verbal instructions as they interact with passengers, other drivers, pedestrians, and authorities on the roads. The AI system should be able to comprehend simple voice commands like “pull forward 10 feet” or orders from officials to “move and park elsewhere.” This voice control capability powered by AI will be essential for the future of self-driving cars.
Innovative Pick: Voice Control for Autonomous Comfort
Without a driver, smart AI-powered self-driving vehicles will need to allow passengers to control the interior environment using just their voice. From adjusting music and lighting to setting the air conditioning, the AI system must understand verbal commands in multiple languages, eliminating the need for touch screen interactions.
Summary
In summary of the interview, we asked Dr. Glassman about the possibilities of deploying some of these use cases in the near future. He stated, “My development team and I have verified that all of the mentioned use cases can be developed within the next two to five years. For instance, electric vehicles, with their more powerful infotainment systems, may be among the first to run
optimized large language models directly in the vehicles. This would avoid the expenses associated with connecting to internet-based generative AI systems.” This promising timeline fuels the dreams of countless consumers eagerly anticipating the arrival of futuristic,
‘AI-powered talking cars of tomorrow,’ destined to revolutionize their driving experiences.
Published by: Khy Talara
