E-commerce has evolved with the digital technology revolution over the years. Last-mile logistics service contributes a significant part of the e-commerce experience. In contrast to the traditional last-mile logistics services, smart logistics service with autonomous driving technologies provides a promising solution to reduce the delivery cost and to improve efficiency. However, the traffic conditions in complex traffic environments, such as those in China, are more challenging compared to those in well-developed countries. Many types of moving objects (such as pedestrians, bicycles, electric bicycles, and motorcycles, etc.) share the road with autonomous vehicles, and their behaviors are not easy to track and predict. This paper introduces a technical solution from JD.com, a leading E-commerce company in China, to the autonomous last-mile delivery in complex traffic environments. Concretely, the methodologies in each module of our autonomous vehicles are presented, together with safety guarantee strategies. Up to this point, JD.com has deployed more than 300 self-driving vehicles for trial operations in tens of provinces of China, with an accumulated 715,819 miles and up to millions of on-road testing hours.
This paper investigates the end-user acceptance of last-mile delivery carried out by autonomous vehicles within the United States. A total of 296 participants were presented with information on this technology and then asked to complete a questionnaire on their perceptions to gauge their behavioral intention concerning acceptance. Structural equation modeling of the partial least squares flavor (PLS-SEM) was employed to analyze the collected data. The results indicated that the perceived usefulness of the technology played the greatest role in end-user acceptance decisions, followed by the inf…
Drones have been considered as an alternative means of package delivery to reduce the delivery cost and time. Due to the battery limitations, the drones are best suited for last-mile delivery, i.e., the delivery from the package distribution centers (PDCs) to the customers. Since a typical delivery system consists of multiple PDCs, each having random and time-varying demands, the dynamic drone-to-PDC allocation would be of great importance in meeting the demand in an efficient manner. In this paper, we study the dynamic UAV assignment problem for a drone delivery system with the goal of provid…
The logistics of transporting a package from a storage facility to the consumer's front door usually employs highly specialized robots often times splitting sub-tasks up to different systems, e.g., manipulator arms to sort and wheeled vehicles to deliver. More recent endeavors attempt to have a unified approach with legged and humanoid robots. These solutions, however, occupy large amounts of space thus reducing the number of packages that can fit into a delivery vehicle. As a result, these bulky robotic systems often reduce the potential for scalability and task parallelization. In this paper…
This paper describes an autonomous shuttle which targets providing last-mile transportation. Often, this involves operation in crowded areas with high levels of pedestrian traffic, and little to no lane markings or traffic control. We aim to create a functional shuttle to be improved upon in the future as new robust solutions are developed to replace the current components. An initial implementation of such a shuttle presented, detailing the overall architecture, controller structure, waypoint following, obstacle detection and avoidance, LiDAR based sign detection, and pedestrian communication…
UAS Technikum Wien（维也纳技术高等学院）；Ural Federal University（乌拉尔联邦大学）；Johannes Kepler University Linz（林茨约翰内斯开普勒大学）
In the context of Intelligent Transportation Systems and the delivery of goods, new technology approaches need to be developed in order to cope with certain challenges that last mile delivery entails, such as navigation in an urban environment. Autonomous delivery robots can help overcome these challenges. We propose a method for performing mixed reality (MR) simulation with ROS-based robots using Unity, which synchronizes the real and virtual environment, and simultaneously uses the sensor information of the real robots to locate themselves and project them into the virtual environment, so th…
OpenBench: A New Benchmark and Baseline for Semantic Navigation in Smart Logistics
Institute for AI Industry Research (AIR), Tsinghua University（清华大学人工智能产业研究院）；College of Information Science and Technology, Beijing University of Chemical Technology（北京化工大学信息科学与技术学院）；School of Astronautics, Harbin Institute of Technology（哈尔滨工业大学航天学院）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；School of Mechanical and Vehicular Engineering, Beijing Institute of Technology（北京理工大学机械与车辆学院）；School of Vehicle and Mobility, Tsinghua University（清华大学车辆与 mobility学院）
LogisticsVLN: Vision-Language Navigation For Low-Altitude Terminal Delivery Based on Agentic UAVs
School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所多模态人工智能系统国家重点实验室）；Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology（澳门科技大学创新工程学院工程科学系）；China Ship Research and Development Academy（中国船舶科研 Academy）；Obuda University（奥布达大学）；State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences（中国科学院复杂系统管理与控制国家重点实验室）
The Multi-Trip Time-Dependent Mix Vehicle Routing Problem for Hybrid Autonomous Shared Delivery Location and Traditional Door-to-Door Delivery Modes
Shenzhen Research Institute of Big Data（深圳大数据研究院）；School of Data Science, The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳）数据科学学院）；The University of Hong Kong（香港大学）
