AImpowering Sustainable Mobility

Artificial Intelligence (AI) is reshaping the landscape of smart mobility, offering innovative solutions that can make transportation more efficient, safer, and sustainable

In recent years, Artificial Intelligence (AI) has been a game-changer for smart mobility, presenting exciting possibilities to revolutionize transportation systems. AI can be used to assist drivers, optimize traffic flow, and improve safety in smart cities. AI is also being used to develop autonomous vehicles, which can help reduce congestion and pollution, and improve the overall passenger experience. In fact, the global AI in transportation market size was valued at USD 2.3 billion in 2021 and is expected to reach around USD 14.79 billion by 2030, poised to grow at a compound annual growth rate (CAGR) of 22.97% over the forecast period 2022 to 2030.* Here are just a few of the ways that, with AI on our side, we can make transportation more efficient, safer, and environmentally friendly.

Congestion, Traffic Management, and Emissions Reduction

One of the key challenges in urban areas is congestion, which not only wastes time and fuel but also contributes to air pollution. AI-powered systems can analyze real-time traffic data from various sources, such as sensors, cameras, and GPS, to optimize traffic flow. AI can identify traffic patterns, predict congestion hotspots, and dynamically adjust traffic signal timings to reduce bottlenecks and improve overall traffic efficiency. By optimizing bus routes, adjusting frequencies based on demand, and predicting ridership patterns, AI can enhance the efficiency and reliability of public transit. This not only encourages more people to choose public transportation but also reduces traffic congestion and carbon emissions associated with private vehicle usage.

One innovative example of an AI-based traffic solution is NGV portfolio company NoTraffic, which digitizes road infrastructure management, allowing cities to manage their entire grid at the push of a button. NoTraffic optimizes traffic lights in real-time based on smart sensors, preparing road infrastructure for the connected and autonomous era. Relatedly, Waycare, which was acquired by Rekor, offers a cloud-based SaaS platform that uses AI and proprietary algorithms to produce valuable insights for the traffic management industry. Their solution integrates data from a variety of sources such as navigation apps, city infrastructure, connected vehicles, weather forecasts, traffic detectors, and more.

With a novel approach to reducing congestion, Autofleet’s platform dynamically leverages vehicle supply from large global fleets — rental companies, car-sharing operators, OEMs, public transportation operators, energy utilities, etc. — to enable fleets to optimize existing operations and open new, on-demand mobility business models. Using advanced machine learning algorithms, they are able to support demand prediction, dynamic pricing, optimized vehicle servicing, automated fleeting/defleeting and demand-supply matching optimization in real-time.

AI can also directly contribute to reducing emissions, for example by optimizing vehicle routing to minimize fuel consumption, taking real-time traffic conditions, weather data, and historical patterns into consideration. The AI-based system of the NGV portfolio company Clearly tackles the challenge another way, providing precision-measuring, real-time alerts, simulated insights, and ongoing emission management at the trip level to help business fleets achieve net-zero emissions.

Electric Vehicles

Electric vehicles (EVs) are a key component of sustainable mobility. AI can play a crucial role in facilitating the widespread adoption of EVs. AI algorithms can analyze data from EVs, charging infrastructure, and user behavior to optimize charging station locations, predict demand, and manage energy distribution more efficiently. Another portfolio company, Make My Day, introduces a first-of-its-kind AI algorithm that connects factual battery consumption data with optimized route planning for EV charging, supporting EV efficiency and, ultimately, adoption.

Further, AI can assist in developing better EV battery management systems, enabling longer battery life and improved performance. By accelerating the transition to electric vehicles, AI can help reduce dependency on fossil fuels and mitigate the environmental impact of transportation.

Vehicle Health

AI-based predictive maintenance systems can monitor vehicles’ health in real-time by analyzing sensor data and identifying potential issues before they become major problems. By detecting anomalies and predicting maintenance needs, AI can optimize maintenance schedules, reduce downtime, and improve vehicle reliability. Our portfolio company, Nemodata, powers the next generation of fleet maintenance and operations, driven by data and AI. Nemodata increases uptime & profitability for fleets through cutting-edge AI software that leverages data from OEMs, aftermarket telematics, and fleet management systems.

Autonomous Driving

AI can enhance safety by analyzing sensor data from vehicles and infrastructure to detect potential hazards, alert drivers, and even enable autonomous emergency maneuvers. Through advanced machine learning algorithms, AI enables cars to analyze and interpret vast amounts of data collected from various sensors. This allows for intelligent decision-making and real-time responses, such as adaptive cruise control, collision avoidance, lane-keeping assistance, and driver monitoring. To bridge the transition to full autonomous driving, Ottopia has developed an AI-based teleoperation platform to meet the operation and safety standards of the automotive industry today. Plus, Foretellix leads the industry in AI-based safety testing tools for ADAS and autonomous vehicle simulations, accelerating the testing process — and, thus, adoption — for these systems.

In-Car Applications

AI impact on in-car applications is truly remarkable, achieving an astonishing level of insight. Our portfolio company, CorrActions presents a novel approach to driver monitoring that enables vehicles to understand drivers’ cognitive states and act accordingly — limiting the speed, increasing braking distance, etc. The wide range of detected states includes everything from intoxication to fatigue, drowsiness, and inattention.

Furthermore, AI-powered voice recognition systems enable drivers to control various functions, such as navigation, entertainment, and climate control, through natural language commands, making the driving experience more intuitive and hands-free. Our portfolio company Kardome’s AI-driven spatial hearing and noise reduction technology facilitate a seamless voice recognition experience in any acoustic environment, from the quiet to the chaotic. With AI, in-car applications are transforming the way we drive, making it safer, more enjoyable, and paving the way for a future of fully autonomous transportation.

Artificial Intelligence, a Powerful Force

The power of AI for sustainable smart mobility is immense. From optimizing traffic flow and intelligent route planning to promoting electric vehicle adoption, enhancing safety, and optimizing public transportation, AI can revolutionize the way we move and contribute to a greener and more sustainable future. As AI continues to evolve, its potential impact on smart mobility is only set to grow, bringing us closer to a world where transportation is efficient, environmentally friendly, and accessible for all.

*Source: Precedence Research, “Artificial Intelligence in Transportation Market,” (Report), August 2022.

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Tali Rosenwaks