Charging Unit Guidance Using User-State Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users of autonomous vehicles face challenges in finding operational charging units at charging stations, as not all charging units are operational and different units have varying charging rates, leading to inefficiencies and unnecessary travel to find a functioning unit.
Innovation Solution
A charging unit guidance system that utilizes a processor and memory to receive user state sequences, determine charging unit locations based on user position data and charging unit states, and upload this information to an edge computing system to provide guidance instructions to other autonomous vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users attempt to use multiple charging units at a charging station prior to finding an operational charging unit, then the user may find a functioning charging unit, but the user wastes time and effort traveling between multiple charging units
Solution Approach 1:
The system performs preliminary detection of charging unit operational status and charging rates before the user arrives. The processor receives charging rate data from multiple charging units and identifies operational units in advance, so when the user arrives at the charging station, they are immediately directed to a known operational unit, eliminating the need to trial multiple units sequentially.
Solution Approach 2:
The system introduces an intermediary guidance mechanism between the user and charging units. The processor acts as an intermediary that receives charging rate information, determines operational status, and provides guidance instructions to the user's autonomous vehicle, mediating the user's interaction with charging units to prevent wasted travel time.
2Adaptability or versatility
If charging stations include multiple parking spots with multiple charging units, then users have more options for charging, but users cannot distinguish between operational and non-operational units without attempting to use them
Solution Approach 1:
The system implements a feedback mechanism where charging units transmit their operational status and charging rate information back to the processor. The processor receives this feedback data and uses it to determine which charging units are operational, then communicates this information to users through guidance instructions, eliminating the information asymmetry between charging unit status and user knowledge.
Solution Approach 2:
The system performs preliminary assessment of charging unit operational status by receiving and analyzing charging rate data from all charging units at the station before the user needs to charge. This advance information gathering allows the system to identify operational units and provide accurate guidance, preventing users from attempting non-operational units.
3Productivity
If different charging units have different charging rates, then users can potentially find faster charging options, but users cannot identify high-rate operational units without trial and error
Solution Approach 1:
The system performs preliminary analysis of charging rate data from multiple charging units to identify both operational status and charging speed characteristics. The processor receives charging rate information and uses it to prioritize operational units with higher charging rates, providing guidance that directs users to the best available options before they arrive at the station.
Solution Approach 2:
The system uses charging rate as a key parameter to differentiate between charging units. By receiving and analyzing charging rate data, the processor can identify units with higher productivity characteristics and prioritize them in guidance instructions, allowing users to easily select optimal charging units based on quantifiable performance parameters rather than trial and error.
Data Source
AI summary
A charging unit guidance system includes a processor and a memory. The memory includes instructions that upon execution by the processor, cause the processor to receive a sequence of user states associated with a user of a first autonomous vehicle, each user state being one of a walking state and an at-charging-unit state and the sequence of user states being based on a sequence of observed user speeds associated with detected user position data associated with movement of the user from the first autonomous vehicle to a charging unit and at the charging unit, determine a charging unit location of the charging unit based on a correlation between the at-charging-unit states in the sequence of user states and the user position data, and upload the charging unit location associated with the charging unit to an edge computing system, the edge computing system being configured to provide guidance instructions to the charging unit to a second autonomous vehicle based at least in part on the charging unit location.