Vehicle-Assisted User Localization for GPS-Blocked Pickup Zones
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous vehicles face challenges in accurately determining user locations in dense urban environments or areas with signal blockage, leading to unreliable GPS information, which can impact pickup efficiency and accuracy.
Innovation Solution
The use of vehicle-obtained localization information, shared with user devices in real-time, to enhance or replace client device GPS, allowing for accurate positioning within 1.0-1.5 meters, and pseudorange error corrections to improve GPS signal reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If satellite-based GPS is used for localization, then coverage area is large, but measurement precision deteriorates in dense urban environments or enclosed areas
Solution Approach 1:
The patent introduces autonomous vehicles as intermediary localization sources. Instead of relying solely on satellite GPS signals that are blocked in urban canyons or enclosed areas, the system uses vehicles equipped with high-precision localization (via GPS when available, visual odometry, or other sensors) as mobile reference points. The client device measures distance to these vehicles using wireless signals (WiFi, Bluetooth, cellular), and triangulates its position based on multiple vehicle positions. This intermediary approach bypasses the need for direct satellite visibility while maintaining high localization accuracy.
2Measurement precision
If vehicle-based localization is used, then measurement precision improves to within 1.0-1.5 meters, but device complexity increases due to multiple sensors and processing requirements
Solution Approach 1:
The patent implements self-service by having autonomous vehicles provide their own high-precision localization data to the system. The vehicles continuously determine their positions using their onboard sensors (GPS receivers, visual odometry systems, inertial measurement units) and share this information via wireless communication. Client devices then use this pre-processed vehicle position data along with measured distances to calculate user positions. This eliminates the need for complex infrastructure and allows the system to leverage the vehicles' own localization capabilities without requiring additional dedicated localization infrastructure.
Solution Approach 2:
The autonomous vehicles serve multiple functions: they perform their primary autonomous driving tasks while simultaneously acting as mobile localization beacons for the pickup/dropoff system. The same onboard sensors used for navigation and obstacle detection are also utilized for providing position information to client devices. This multi-functionality reduces overall system complexity by repurposing existing vehicle capabilities rather than adding separate dedicated localization infrastructure.
3Reliability
If continuous localization updates are performed, then reliability of location information improves, but use of energy increases for processing and communication
Solution Approach 1:
The system implements periodic localization updates rather than continuous real-time tracking. The autonomous vehicles periodically broadcast their position information and measured distances to client devices at scheduled intervals. Client devices periodically request and process updated position data. This periodic approach maintains sufficient localization reliability for pickup/dropoff operations while significantly reducing the processing load and energy consumption compared to continuous high-frequency updates.
Data Source
AI summary
The technology provides enhanced localization approaches using vehicle-obtained information in place of or to enhance global positioning information to localize a user's position. Such information can be shared with the user's client device in real-time prior to pickup or meeting at a selected location. This can supplement or replace inaccurate localization information available at the client device, and can be done as needed when the user is within a threshold range of one or more autonomous vehicles. A client device of a user can compute its position using the vehicle positioning information. The vehicle positioning approach may be performed when the user is within a certain range of one or more vehicles. Vehicle localization information may also be used to correct the client device's localization information. Here, using hyper-accurate vehicle positioning, one or more vehicles can compute pseudorange errors for each “visible” satellite in a global positioning service.