PMV Fleet Repositioning Using Sensor-Based Utilization Monitoring
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Solution Overview
Problem
Conventional approaches for managing fleets of personal mobility vehicles, such as e-bikes and scooters, require significant human effort to monitor and manage their deployment and status, which becomes inefficient as the fleet size increases.
Innovation Solution
A fleet of vehicles equipped with sensors like optical cameras, LiDAR, radar, and ultrasound equipment senses and navigates environments to monitor personal mobility vehicles, determining their presence and states, and communicates this information to a transportation management system for automated management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual monitoring and management methods are used for personal mobility vehicles, then operational control can be maintained, but human effort and time consumption increase significantly as fleet size grows
Solution Approach 1:
The personal mobility vehicles are equipped with sensors and computing systems that enable them to autonomously monitor their own operational status, location, and environmental conditions. The vehicles self-report this data to the transportation management system, eliminating the need for manual monitoring and allowing the fleet to manage itself
Solution Approach 2:
Manual mechanical monitoring methods are replaced with automated electronic sensor systems and digital communication networks. Sensors detect vehicle status and environmental data, which are then transmitted electronically to the management system, substituting human observation and manual record-keeping with automated detection and data transmission
2Quantity of substance
If fleet size increases to improve service coverage, then more vehicles are available for use, but manual management becomes increasingly inefficient
Solution Approach 1:
The transportation management system serves multiple functions simultaneously: it monitors vehicle locations, tracks operational status, analyzes utilization metrics, determines optimal deployment strategies, and coordinates vehicle redistribution. This multi-functional automated system can efficiently manage large fleets without proportionally increasing management resources
Solution Approach 2:
The system continuously collects data from sensors on all fleet vehicles, processes this information to determine utilization metrics and operational status, and uses this feedback to automatically adjust vehicle deployment and distribution. This closed-loop feedback mechanism enables scalable management where the system adapts to fleet size changes without manual intervention
3Productivity
If automated sensor systems are deployed to monitor vehicles, then management efficiency improves, but system complexity increases
Solution Approach 1:
The monitoring system is divided into independent modular components: sensors mounted on individual vehicles, onboard computing systems for data processing, communication modules for data transmission, and a central management system for analysis and decision-making. Each component performs a specific function and can be independently configured or replaced, reducing overall system complexity through functional segmentation
Data Source
AI summary
A computer-implemented method is disclosed for managing personal mobility vehicles (PMVs) across a geographic region. One or more sensor-equipped vehicles traverse the region and collect sensor data, which is used by a computing system to determine the respective state and location of PMVs. Based on these determinations, the system generates a utilization value for the PMVs and compares it to a predefined utilization metric reflecting desired deployment levels. The system then provides instructions to reposition PMVs within the region to satisfy the utilization metric, enabling automated, demand-responsive fleet balancing and reduced reliance on manual monitoring.