Mobility Vehicle Path-Training Assistance for Safe Zone Control
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Solution Overview
Problem
Existing personal-mobility vehicles (PMVs) for individuals with reduced mobility face challenges in safe navigation due to user interaction difficulties with control interfaces, leading to potential risks for the user and others, especially in urban environments, and self-driving solutions are not sufficiently reliable for these users.
Innovation Solution
An assistance system for PMVs that includes sensors and a processing system to monitor vehicle state and user inputs, allowing path training to define allowed zones, and adjusts vehicle movement to maintain the user within these zones, providing alerts or operator control when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If self-driving PMVs are implemented, then user autonomy is improved, but safety and reliability deteriorate because self-driving cannot guarantee necessary safety in urban environments
Solution Approach 1:
The patent introduces an assistance system as an intermediary between the user and the environment. The processing system monitors sensor data, detects obstacles, and provides assistance signals to the user interface, acting as a safety mediator that enhances reliability without removing user control, thus resolving the contradiction between autonomy and safety
Solution Approach 2:
The system continuously monitors environmental data through sensors and provides real-time feedback to the user via the user interface. This feedback loop enables the user to make informed decisions while maintaining autonomy, yet the system's monitoring capability ensures safety by alerting users to potential hazards they might not perceive
2Ease of operation
If autonomous displacement is enabled, then mobility is improved, but safety deteriorates due to inability to guarantee safety of autonomous displacement
Solution Approach 1:
The assistance system serves as a mediator between autonomous vehicle operations and user safety. It continuously monitors environmental data through sensors, detects potential hazards, and provides real-time assistance signals to the user interface, enabling autonomous mobility while mitigating safety risks through active monitoring and user alerting
Data Source
AI summary
Described herein is an assistance system for an electric personal-mobility vehicle (1a) for a person with reduced mobility. The assistance system comprises sensors (50a) configured for supplying data on the current state of the electric vehicle (1a) and a processing system (60, 2, 3). During a path training step, the processing system monitors a control signal (S1; Da, Db) supplied by a user interface (10a) of the electric vehicle (1a) and drives at least one actuator (30) of the electric vehicle (1a) as a function of the control signal (S1; Da, Db). Moreover, the processing system acquires a plurality of positions of the electric vehicle (1a), processes such position data to generate data that define at least one allowed zone, and stores the at least one allowed zone in a memory (62). Instead, during a normal operating step, the processing system determines the current state of the electric vehicle (1a) as a function of the data supplied by the sensors (50a) and monitors the control signal (S1; Da, Db) supplied by the user interface (10a). On the basis of these data, the processing system estimates a future state of the electric vehicle (1a) and determines whether the future position of the vehicle is within at least one allowed zone stored in the memory (62). In the case where the future position is within at least one allowed zone, the processing system drives the at least one actuator (30) of the electric vehicle (1a) as a function of the control signal (S1; Da, Db). Instead, in the case where the future position is not within at least one allowed zone, the processing system may control the actuators for keeping the electric vehicle (1a) within at least one allowed zone and/or generate an alert signal.


