Through technological innovations including artificial intelligence (AI), the internet of things (IoT) and 5G mobile network technology, the connected vehicle industry is evolving and improving the safety and efficiency of transportation, according to a new report from GlobalData.

The term connected vehicles refers to communication technologies for enhanced functionality and safety of vehicles.

GlobalData’s Wheels of Change: startups revolutionizing mobility, offers insights into innovative startups across 14 emerging trends in mobility, delving into their key offerings, partners and funding trends. Connected vehicles was one of the emerging trends identified, with startups such as Nauto, Sonatus, Aurora Labs and Sibros featuring.

“The connected vehicles industry is rapidly evolving, propelled by technological innovations and consumer demand for smarter transportation,” explains Vaibhav Pralhad Gundre, disruptor analyst at GlobalData and author of the report.

“We are witnessing the rising adoption of connected vehicle solutions across various use cases, including V2V (vehicle to vehicle) communication and V2I (vehicle to interface) integration.”

Vehicle-to-everything communication

The integration of vehicle-to-everything (V2X) communication is gaining momentum in the industry, according to Gundre.

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This, he explains, is due to “its potential to significantly improve road safety, traffic efficiency, and overall transportation systems.”

V2X can enable vehicles to communicate with each other and with infrastructure, providing real-time data on road conditions, and potential hazards, and optimizing traffic flow.

“This connectivity is crucial for enhancing smart transportation solutions,” says Gundre.

“V2X facilitates the development of autonomous and connected vehicles, paving the way for advanced mobility solutions. With V2X, autonomous vehicles can receive data beyond their onboard sensors’ range, enhancing their perception of the environment and enabling them to anticipate and respond to situations more effectively.”

“V2X communication can further enable emergency vehicles to communicate their location and status to surrounding vehicles, allowing them to clear the path and make way for emergency services quickly and efficiently.”

Nauto (AI-enabled safety)

Nauto is an AI-powered fleet and driver safety platform based in the United States offering real-time solutions to predict and mitigate high-risk events in mobility.

Founded in 2015, Nauto has partnered with numerous companies including the BMW Group, Toyota, Stellantis and the SoftBank Group. The company has received a total of $173.6m in funding since 2015.

Nauto’s service offers predictive collision alerts, driver behaviour alerts, incident reporting, self-guided and manager-led coaching as well as on-demand videos. This allows incidents to be recorded and reported swiftly as well as mitigating the possibility of potential collisions by undertaking risk assessments in real time.

Following strategic investment from Stellantis Ventures in the summer of 2023, the company announced new telematic abilities allowing potential visibility into vehicle tracking, utilisation, misuse, and maintenance planning.

In October 2023, Nauto then partnered with Stellantis to introduce a vehicle safety solution explicitly designed for fleet customers.

Sonatus (in-vehicle and cloud software)

Sonatus is a US-based company founded in 2018. It provides in-vehicle and cloud solutions for software-defined vehicles. Its key offering is the Sonatus Vehicle Platform, which includes cloud and in-vehicle software services. Alongside side this, Sonatus also offers software-defined components, vehicle personalisation, and zonal architecture.

The company has received funding from the likes of LG, Translink Capital and NEC totalling $110m of funding over two separate rounds in 2021 and 2022. Among known partners are Google Cloud Partner, AWS, Hyundai and Microsoft Partner.

At the start of 2024, Sonatus introduced Updater for managing comprehensive vehicle software updates over the air following the launch of its Software Defined Component Solution and the Vehicle Personalization Solution.

Aurora Labs (self-healing software)

Almost a decade old, Aurora Labs supplies self-healing software for connecting cars allowing manufacturers to adapt to future vehicle software needs. Focussing on autonomous systems AI and machine learning, the firm offers auto-validation, auto-detection and auto-updates for faults within the systems.

The company has had four rounds of funding since 2016, amassing a total of $97.2m, with the most recent one in 2022 attracting $63m alone. Key investors identified in the report include Porsche SE, Moore Ventures, LG Technology Ventures, UL Solutions and Toyota Tsusho Corporation.

Recent collaborations and partnerships include Aurora Labs’ strategic cooperation with NTT Data to benefit from AI technology and 5G, a partnership with Deloitte on processes for Software-Defined Vehicles. In January, Aurora Labs’ most recent collaboration was with Infineon intending to provide better predictive maintenance solutions for the automotive industry.

Sibros Technologies (IoT for software-defined mobility)

Sibros Technologies, also founded in 2018, offers a cloud-based connected vehicle ecosystem that provides over-the-air updates alongside fleet management and data analytics from the industry. Transforming vehicle data into AI-enabled insights, Sibros’ solution allows OEMs to compose continuous product updates for connected vehicles.

The company’s key offering is a deep connected platform, logger, update and commander. With $85.5m total funding from $70m through a Series B financing in 2022 from investors such as Google, Qualcomm Ventures, Global Brain and Energy Impact Partners.

At the start of 2024, Sibros partnered with Continental Engineering Services to deliver connected vehicle technologies to a wider market.

Themes in connected vehicles

Gundre also advised that startups in the connected vehicle space should consider trends such as advancing autonomous driving capabilities through sensor fusion, computer vision and decision algorithms and leveraging vehicle data for insights into traffic patterns, vehicle performance and user behaviour alongside other measures.