Rendezvous Queue Coordination for On-Demand Pickup Throughput

Solution Overview

Problem

Existing network-based on-demand transportation systems face inefficiencies in rendezvous throughput at common pick-up and drop-off areas, leading to traffic congestion and increased wait times for users and transport providers.

Innovation Solution

A network computing system that coordinates on-demand transportation by maximizing throughput at common rendezvous locations through application-based coordination, dynamic queue management, and real-time routing adjustments based on estimated times of arrival and traffic conditions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If multiple transport providers are routed to common pick-up and drop-off areas simultaneously, then service coverage is improved, but traffic congestion and wait times increase

Engineering Contradiction:

Improveservice coverageVSAvoidwait times

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system performs preliminary routing actions by assigning transport providers to sequential time slots for accessing common rendezvous locations. Before traffic congestion occurs, the backend computing system pre-coordinates arrival times, ensuring that multiple providers serving the same area do not arrive simultaneously, thereby reducing wait times while maintaining broad service coverage

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts routing instructions in real-time based on current traffic conditions, provider locations, and demand patterns. By continuously optimizing arrival times and rendezvous location assignments, the system adapts to changing conditions to minimize congestion and wait times while preserving service accessibility

Inventive Principle:

Principle #15Dynamics

2Adaptability or versatility

If multiple transport providers are routed to common pick-up and drop-off areas simultaneously, then service coverage is improved, but traffic congestion increases

Engineering Contradiction:

Improveservice coverageVSAvoidtraffic congestion

Core Design Contradiction:

Adaptability or versatilityVSObject-generated harmful factors

Solution Approach 1:

The system performs preliminary routing actions by assigning transport providers to sequential time slots for accessing common rendezvous locations. Before traffic congestion occurs, the backend computing system pre-coordinates arrival times, ensuring that multiple providers serving the same area do not arrive simultaneously, thereby reducing wait times while maintaining broad service coverage

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts routing instructions in real-time based on current traffic conditions, provider locations, and demand patterns. By continuously optimizing arrival times and rendezvous location assignments, the system adapts to changing conditions to minimize congestion and wait times while preserving service accessibility

Inventive Principle:

Principle #15Dynamics

3Productivity

If transport providers are sequentially routed through common rendezvous locations, then traffic flow is improved, but coordination complexity increases

Engineering Contradiction:

Improvetraffic flowVSAvoidcoordination complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The backend network computing system serves multiple functions simultaneously: it acts as a matching engine for provider-requester pairs, a traffic management system for sequential routing coordination, and a real-time communication hub. This multi-functionality allows the system to manage complex sequential routing without requiring additional specialized infrastructure, thereby improving traffic flow while containing coordination complexity within a single integrated platform

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250052585A1Coordinating transport through a common rendezvous location

Publication Date: 2025.02.13 UBER TECHNOLOGIES INC

AI summary

A computing system can maximize throughput for a common rendezvous location by determining estimated times of arrival (ETAs) to the common rendezvous location for matched users and/or transport providers. Based on the ETAs of each of the transport providers, the computing system can generate a dynamic queue comprising the transport providers for the common rendezvous location and manage the dynamic queue by routing the transport providers through the common rendezvous location. The computing system can further dynamically adjust the queue based on changes to the ETAs by transmitting updated navigation-related data to one or more of the matched transport providers.