[Rino Showcase] A New Solution for Campus Delivery! Rino.ai Autonomous Delivery Vehicle Enables Self-Service Delivery, Reshaping Campus Food Delivery Fulfillment

Campus lunch and dinner peak hours are highly concentrated, and dormitories are widely distributed. Traditional delivery relying on manual tricycles for round trips has long faced multiple operational challenges, including high cost, safety risks, unstable capacity, and difficulties in staff retention.

Based on mature L4 autonomous driving technology, Rino.ai has developed a campus-specific unmanned delivery system, building an end-to-end autonomous logistics link from canteen to dormitory buildings. With a lightweight deployment solution, the system simultaneously achieves four major upgrades: cost reduction, efficiency improvement, safety enhancement, and convenience optimization.

Severe Pain Points: Traditional Delivery Undermines Campus Logistics Efficiency

Campus delivery systems traditionally rely on a fixed setup of “dedicated couriers + electric bikes,” where staff repeatedly shuttle between canteens and dormitories to deliver meals. This model has long faced four major operational bottlenecks:

???? High fixed labor costs
Monthly courier salaries alone amount to several thousand RMB per person. Year-round labor expenses place a stable financial burden on campus logistics and compress canteen profit margins.

???? High turnover and rising management costs
Due to intensive workload during meal peaks, employees face heavy physical strain and high turnover rates. Schools must continuously invest in recruitment, onboarding, and management, resulting in unstable delivery capacity.

???? Safety risks in campus mobility
Electric bikes operating in densely populated campus roads pose safety risks, especially during peak class transition periods, increasing the likelihood of collisions and traffic incidents. This conflicts with refined campus safety management requirements.

???? Peak-hour capacity saturation and inefficiency
A single courier has a limited number of trips per cycle. During lunch and dinner peaks, order backlogs accumulate, delivery times increase significantly, and student waiting times deteriorate, negatively impacting dining experience.

Model Innovation: Autonomous Self-Service Delivery Reshaping the Entire Campus Logistics Flow

Rino.ai designs a dedicated unmanned delivery solution for closed-campus environments, eliminating the need for dedicated couriers to accompany transport throughout the process. It builds a simplified end-to-end chain of “canteen loading → autonomous vehicle transport → student self-service pickup.”

Five key operational values are achieved:

✅ Simplified labor workflow
Canteen staff can directly load meals onto autonomous vehicles without dedicated personnel shuttling between dormitories. This frees up manpower to focus on core tasks such as food preparation and counter service, significantly reducing delivery labor requirements.

✅ Self-service fixed-point pickup
Autonomous vehicles precisely stop at dormitory entrances. Students can pick up meals at their own time after class instead of waiting for couriers to deliver building by building, greatly improving flexibility for fragmented campus schedules.

✅ All-weather operation without disruption
Equipped with full-scenario autonomous driving perception systems, the vehicles operate safely at low speeds within campus environments. They remain operational in extreme conditions such as heat, rain, and snow, enabling uninterrupted year-round service.

✅ Monthly cost savings per vehicle exceed RMB 1,000
At scale, each autonomous vehicle can reduce labor-related expenses by over RMB 1,000 per month, eliminating ongoing recruitment and training costs and significantly improving long-term operational efficiency.

✅ Improved peak-hour delivery efficiency
The system calculates optimal campus routes autonomously, avoids congestion, and enables multi-vehicle coordination to distribute workload, effectively reducing order backlog and improving overall delivery speed.

Campus-Specific Deployment Advantages: Tailored for Closed-Campus Fine-Grained Management

Unlike urban open-road delivery vehicles, Rino.ai’s unmanned delivery system is specifically designed for enclosed university environments, with deployment advantages aligned with campus management needs:

???? Eliminating on-campus traffic safety risks
Replacing electric tricycles with low-speed intelligent autonomous vehicles helps avoid collision risks caused by mixed pedestrian-vehicle traffic, aligning with campus safety management standards.

???? Simplifying logistics and facility management workflows
By removing reliance on dedicated delivery couriers, the system significantly reduces workload related to attendance tracking, turnover, and rehiring, lowering overall campus logistics management complexity.

???? Scalable peak-hour capacity support
Multiple autonomous vehicles can be dispatched in parallel to handle concentrated lunch and dinner peak demand, ensuring stable fulfillment of real-time student dining needs across campus.

In the future, Rino.ai will continue to optimize its product capabilities for campus scenarios, expanding coverage across comprehensive universities, vocational colleges, and enclosed campus parks.

Built on L4 autonomous driving technology, the company provides a low-cost, high-safety, and high-efficiency intelligent fulfillment solution for campus logistics, driving the digital and intelligent upgrade of university campus support services.