# Toward a Modern Last-Mile Delivery: Consequences and Obstacles of Intelligent Technology
## 3 Feasibility of Modern LMD
In 2019, Tesla also joined the humanless LMD trend, reflecting the growing trend of AI in LMD that has created a new industry [97]. Moreover, [PERSON] [98] states that Walmart promises to deliver orders within two hours, as their system includes an AI-powered vehicle route planning tool that provides the best route based on real-time information, such as weather, traffic, etc., for a given delivery location. Recently, airworthiness criteria for the type certification of delivery drones with an intent to initialize commercial operations was proposed. The delivery drone is an UAV used to transport packages, medical supplies, food, or other goods. Delivery drones are typically autonomous. Amazon has tested drone deliveries and delivered products within 30 min [99]. Many modern businesses pursue delivery time savings to gain a competitive edge and improve delivery service. According to the most recent Datex Corporation publications [100], many business models are being supplanted by AI-powered ideas, such as self-driving delivery robots and drones, which reduce the need for human interaction in delivery. Technological innovations are shifting from transactional to cognitive automation, with AI being used primarily in business decision making. Using autonomous drones reduces wage costs and human errors like negligence, disorientation, and wrong recipient delivery [101]. In fact, drones reduce wage costs and delivery times in urban areas because they are autonomous [101]. [PERSON] et al. [102] offer a robot autonomy module for localization and navigation to overcome routing challenges in LMD, which helps with delivery routing. [PERSON] et al. [103] suggested a novel technique that combines complicated network architecture and algorithms to produce the optimum route for delivery trucks and to guarantee items will reach customers on time while lowering trip lengths. The study found that LMD outperformed traditional systems and optimization results are unremarkable compared to AI savings. On the other hand, among its other impacts, AI improves visibility, risk management, sourcing, and distribution in supply chains [68], but also When it comes to AI and LMD, one of the key areas to be discussed is not only operational performance but also sustainability. It is forecasted that LMD demand will rise 78% by 2030, delivery traffic emissions will rise 32%, and congestion will rise 21%, so bringing AI into LMD is essential to achieving sustainability goals [104]. Most major cities are experiencing transportation and logistics issues due to population and vehicle growth, and LMDs increase traffic congestion and emissions. AI solutions are a valuable asset in addressing these issues, as AI with real-time vehicle data for traffic management can reduce congestion [105]. [PERSON], [PERSON], and [PERSON] [106] propose delivery simulation models and optimizations resulting in less congestion, lower emissions, and faster deliveries. [PERSON], [PERSON], and [PERSON] [107] view the issue in the context of using robots to reduce truck mileage, which lowers local emissions by up to 60%, according to the authors' calculations, and the authors hope their findings can guide the operation and planning of a truck-and-robot LMD system. Many companies struggle with fuel emissions in urban areas with heavy traffic because their vehicles spend so much time waiting, where AGVs are mostly electronic, making them a greener last-mile solution [41, 108]. In short, in conjunction with vehicle routing optimization, delivery robotsand drones can design the lowest-cost routes to meet customer demand, while reducing energy consumption and shortening delivery times [104]. AI assists businesses in lowering human costs, reducing failed deliveries, avoiding congestion, increasing speed, and lowering air emissions [109, 110]. Autonomous drones or robots may improve service by delivering quick home deliveries, even in rural areas [111].