Robot-Assisted Curbside Delivery for Dynamic Parking Allocation
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Solution Overview
Problem
Urban areas face challenges in curb space management due to long durations of delivery vehicle parking, variability in goods delivery times, and competition for curb space between delivery vehicles and other users, exacerbated by the vertical dimensions of buildings and increased demand in downtown areas.
Innovation Solution
The implementation of robot-assisted package delivery systems integrated with curbside parking monitoring and optimization, utilizing real-time and predictive analytics to determine optimal drop-off and pick-up locations, communicating with smart parking systems, and leveraging machine learning for improved curb space allocation and traffic simulation modeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If delivery vehicles park at curbside locations for goods delivery, then delivery operations can be completed, but curb space is occupied for long durations creating competition with other curb space users
Solution Approach 1:
The delivery process is segmented into two independent phases: (1) vehicle drops off robot at curbside and departs, (2) robot completes delivery independently. This segmentation allows the vehicle to occupy curb space only briefly for robot transfer, while the robot handles the time-consuming delivery tasks, thereby resolving the contradiction between completing delivery operations and minimizing curb space occupation duration
Solution Approach 2:
A delivery robot serves as an intermediary between the delivery vehicle and the final delivery location. The robot is transferred from the vehicle to the curbside, performs the delivery independently, and returns to the vehicle. This intermediary approach separates the vehicle's curb space occupation from the delivery duration, allowing the vehicle to leave immediately after dropping off the robot
2Ease of operation
If traditional policies allocate curb real-estate for delivery vehicles, then delivery operations are supported, but curb usage is sub-optimized due to lack of coordination with robot/vehicle allocation
Solution Approach 1:
The system implements dynamic curb space allocation where robots and vehicles can be assigned to different curbside locations based on real-time conditions, delivery patterns, and availability. This dynamic allocation replaces static traditional policies, optimizing curb space utilization while maintaining ease of operation through adaptive coordination between vehicles, robots, and curbside locations
Solution Approach 2:
The system incorporates feedback mechanisms that track robot and vehicle locations, curbside occupancy, and delivery completion data. This feedback enables continuous optimization of curb space allocation by adjusting assignments based on observed performance, thereby improving productivity while maintaining operational ease through data-driven decision making
3Productivity
If multiple delivery vehicles operate in downtown areas with high demand, then more deliveries can be completed, but competition for curb space intensifies with other curb space users
Solution Approach 1:
Delivery robots perform self-service by independently navigating from the curbside drop-off location to the final delivery destination and returning. This self-service capability allows multiple vehicles to operate simultaneously in downtown areas without proportionally increasing curb space competition, as each robot handles its own delivery tasks without requiring continuous vehicle presence at the curb
Solution Approach 2:
The system transitions from a two-dimensional curbside interaction model to a three-dimensional model by deploying robots that operate in the space between the curbside and building entrances. This dimensional expansion allows deliveries to be completed without additional curb space occupation, enabling increased delivery volume while reducing harmful curb space competition
Data Source
AI summary
Robot-assisted package delivery with integrated curbside parking monitoring and curb operations optimization is disclosed herein. An example method includes dispatching a delivery vehicle and delivery robot to a delivery location, the delivery location including a parking location for the delivery vehicle that allows for deployment of the delivery robot on a delivery mission, determining occupancy of the parking location, the delivery vehicle parking at the parking location when the parking location is unoccupied, the delivery robot being deployed upon parking of the delivery vehicle, and instructing the delivery vehicle to remain parked during the delivery mission or to leave the parking location and return at later point in time based on an estimated time of arrival of the delivery robot after the delivery mission.