深圳无人车线路里程环比增近四成 无人车配送月“值”破千万

Core Insights - Shenzhen's autonomous vehicle industry is experiencing significant growth, with a nearly 40% increase in operational route mileage in October, and commercial value from deliveries surpassing 10 million yuan [1][2] Group 1: Operational Developments - In October, the number of operational autonomous vehicles in Shenzhen increased to 851, with 53 new vehicles added [1] - The logistics autonomous vehicles reached an operational scale of 484 units, marking a 12% increase month-over-month [1] - A total of 224 new operational routes were added, with a mileage increase of 1,330 kilometers, representing a 1,100% and 240% increase respectively [1] - Cumulatively, Shenzhen has opened 1,478 routes with a total mileage of 4,911 kilometers, reflecting a 37% increase in total open mileage [1] Group 2: Delivery Performance - The average daily operational time for autonomous delivery vehicles was 8.2 hours, with a monthly operational mileage of 160,000 kilometers [2] - The number of autonomous delivery orders exceeded 1.29 million, showing a 26% month-over-month growth, including 1.1 million express deliveries and 190,000 fresh food deliveries [2] - The commercial value generated from these deliveries was approximately 11.12 million yuan, a 28% increase, with cost savings of 1.2 million yuan [2] Group 3: Competitive Landscape - Major players in the market include Meituan, which led in fresh food delivery with 187,000 orders, and SF Express, which dominated express delivery with 681,000 orders [2] - Other competitors like JD and Yunda completed 139,000 and 98,000 orders respectively, while other express companies averaged around 50,000 orders [2] - New entrants are rapidly joining the industry, indicating a dynamic competitive environment [2] Group 4: Technological Advancements - New Stone Technology announced the commercial delivery of its self-developed L4 level map-free autonomous driving technology, which reduces reliance on high-precision maps [2] - This innovation is expected to lower operational costs and enhance vehicle adaptability in complex environments, facilitating a shift from "map-dependent" to "self-perception" in the industry [2]