Chinese startup DeepRoute.ai recently unveiled its next-generation driver-assistance platform, DeepRoute IO 2.0, featuring its self-developed VLA (Vision-Language-Action) model. The company claims this architecture breaks through the interpretability and generalization bottlenecks of traditional end-to-end (E2E) systems. The new platform integrates visual perception, semantic understanding, and action decision-making, offering functions such as spatial semantic comprehension, irregular obstacle detection, traffic sign text recognition, and memory-based voice control. This delivers a more humanlike and safer advanced driver-assistance experience. Compared with current market solutions, DeepRoute IO 2.0 offers greater technical transparency and stronger mass-production adaptability, having secured five design-win projects and approaching 100,000 vehicles in deployment. The company also plans to accelerate passenger car applications and expand into Robotaxi operations as part of its roadmap toward Road AGI (Artificial General Intelligence for Roads).

Among the hottest topics in today’s industry, the application of AI across various fields is revealing the potential to revolutionize existing practices. In the field of intelligent transportation, AI’s potential is particularly vast. At the ongoing ITS World Congress in Atlanta, USA, Sony Semiconductor Solutions is showcasing two smart city pilot projects that demonstrate how its advanced edge AI sensing technology helps local governments improve traffic safety, enhance roadway efficiency, and support infrastructure decisions with high-precision, long-term data—creating new opportunities for both the automotive and transportation sectors.

As autonomous driving technology edges closer to commercial deployment, U.S. ride-hailing platform Lyft has announced the launch of its inaugural Driver Autonomous Forum, a new initiative specifically designed for seasoned drivers on the platform. The goal is to give human drivers a voice in the transition process as robotaxis are gradually integrated into Lyft’s service system, allowing them to participate in decision-making and influence future strategy.

As autonomous vehicle (AV) technology moves closer to commercial deployment, cities around the world face the challenge of incorporating this innovative technology into their public transportation systems while maintaining fairness and safety. Seattle, Washington, is attempting to take a different approach. Instead of allowing policies to be shaped solely by technical experts or industry stakeholders, the city has chosen to begin with its citizens—engaging diverse communities in the policy-making process and aiming to develop a truly human-centered AV integration plan. In doing so, it has introduced seven key priorities for AV development. This article explores what lessons Taiwan might draw from Seattle's approach as it charts its own path in autonomous mobility.

As autonomous driving technology moves steadily toward commercialization, Alphabet’s self-driving unit Waymo has taken another critical step forward. According to a recent announcement, Waymo has received approval from the California Public Utilities Commission (CPUC) to expand its robotaxi operations across a broader area of the San Francisco Peninsula, extending further south to include the tech hub of San Jose. This decision reflects the California government’s growing confidence in the safety and market potential of autonomous services, and it further consolidates Waymo’s dominant position in the U.S. robotaxi landscape.

On 30th April, Toyota and Waymo officially announced that they have reached a preliminary agreement to collaborate on accelerating the development and application of autonomous driving technologies. The partnership will also include Woven by Toyota, the automaker’s strategic subsidiary, to further integrate advanced software development and mobility innovation resources—demonstrating a strong commitment by both industry giants to advancing the future of self-driving mobility.

Nissan recently announced that it will introduce a next-generation ProPILOT system starting from fiscal year 2027. In today's rapidly evolving landscape of autonomous driving technologies, this move has sent shockwaves throughout the automotive world. This upgrade is not just about enhancing sensors or hardware—it marks a fundamental shift from “rule-based” to “learning-based” technology, deeply integrating artificial intelligence into vehicle decision-making systems. The new system combines Nissan’s in-house Ground Truth Perception technology with AI Driver software developed by British startup Wayve, aiming to bring human-like intuition and responsiveness to autonomous driving.