Self-Driving Vehicle Path Control for Wireless Coverage Gaps
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Self-propelled land vehicles face challenges in navigating environments with poor or absent wireless communication networks, leading to potential loss or inability to complete planned paths due to outdated maps and changing environmental conditions.
Innovation Solution
The method involves creating an augmented map with a Connectivity Reliability Index and using a microprocessor unit to choose a path that ensures a valid wireless connection, allowing for remote guidance or reporting, and autonomously recalculating a path if connection is lost, while considering energy consumption and environmental obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If self-propelled land vehicles navigate in completely autonomous way using path planning algorithms, then navigation autonomy is improved, but ability to be remotely controlled or recovered when lost is worsened
Solution Approach 1:
The system dynamically adjusts the level of autonomy based on connectivity conditions. When wireless connection is available, the vehicle operates in autonomous mode; when connection is lost, it transitions to a state where it can be remotely controlled, thus making the automation extent adjustable rather than fixed
Solution Approach 2:
The system changes the operational parameter of control mode based on the presence or absence of wireless communication. The microprocessor unit monitors connection status and switches between autonomous navigation and remote control modes, effectively changing the system's operational state based on external conditions
2Reliability
If self-propelled land vehicles are equipped with wireless communication network connection, then remote monitoring and control capability is improved, but ability to operate in areas with poor or absent wireless connection is worsened
Solution Approach 1:
The vehicle is pre-equipped with wireless communication capabilities and the system is designed to handle connectivity loss scenarios in advance. The microprocessor unit is programmed to detect connection loss and autonomously recalculate paths to areas with better connectivity, preparing the system for operation in varying connectivity conditions
Solution Approach 2:
When wireless connection is lost, the vehicle serves itself by autonomously recalculating its path to reach areas with better network coverage. The system independently monitors its own connectivity status and takes corrective action by rerouting, without requiring external intervention
3Measurement precision
If maps of environments are updated frequently, then navigation accuracy is improved, but data storage and processing requirements are worsened
Solution Approach 1:
Instead of uniformly updating entire environment maps, the system focuses on updating local areas where the vehicle is currently operating or where connectivity issues have been detected. This localized approach maintains navigation accuracy in relevant areas while reducing overall data storage requirements
Data Source
AI summary
A self-propelled land vehicle to which the control method described herein applies includes a memory containing a map of territories, a microprocessor unit coupled to the memory and connected to a wireless communication network, a location sensor configured to provide the microprocessor unit with a geographical position signal of the self-propelled land vehicle, an electric motor to move the land vehicle and a battery for the electric motor. The memory contains a map with information on a connection quality parameter to the wireless communication network in correspondence with the territories, so that for each territory a corresponding value of the connection quality parameter in that territory can also be read in the map. The choice of the path is preferably made such that there is always a good connection to a wireless network.