RF Proximity Detection for Urban Mobility Location Accuracy
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Solution Overview
Problem
In urban areas, GPS signals are often blocked by skyscrapers or attenuated in crowded environments, leading to difficulties for drivers and riders in shared mobility services like Uber and Lyft to locate each other, resulting in wasted time, increased CO2 emissions, and a poor user experience, especially at night or in bad weather.
Innovation Solution
The CarFi system uses Wi-Fi channel state information (CSI) from multiple antennas coupled with a moving vehicle and a data-driven technique to determine the street side of a potential rider, employing an LSTM classifier to process CSI amplitude and phase data, providing accurate rider side determination with 95.44% accuracy in both line of sight and non-line of sight conditions without requiring privacy-invasive personal information or heavy computation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS signals are used for location, then location accuracy is improved, but GPS signals are blocked by buildings and attenuated in crowded environments
Solution Approach 1:
The patent introduces RF transceivers and Wi-Fi signals as intermediary systems to replace GPS for location determination. Instead of relying on satellite signals that are blocked by buildings, the system uses local RF communications between driver and rider devices to determine proximity and location, serving as a mediator that works in urban canyons and crowded environments where GPS fails
Solution Approach 2:
The patent replaces the GPS satellite-based electromagnetic system with a local RF-based proximity detection system. By substituting GPS with RF signal strength measurement and Wi-Fi channel state information, the system achieves location determination without relying on satellite signals that are vulnerable to blockage in urban environments
2Loss of time
If drivers and riders use traditional location methods, then they can locate each other, but it wastes time and increases CO2 emissions due to idle time
Solution Approach 1:
The system performs preliminary location determination using RF transceivers and Wi-Fi signals before the driver arrives at the pickup location. By continuously monitoring signal strength and determining rider proximity in advance, the system eliminates idle waiting time and reduces unnecessary vehicle movement, thereby reducing energy consumption and CO2 emissions
Solution Approach 2:
The RF transceivers and Wi-Fi systems in driver and rider devices automatically perform location determination and proximity detection without requiring manual intervention. The system self-services by continuously exchanging signals and calculating positions, eliminating the time waste associated with traditional location methods
3Loss of information
If GPS is used for location determination, then location can be found, but it does not work at night or in bad weather
Solution Approach 1:
The patent uses RF transceivers and Wi-Fi signals as intermediary systems that operate independently of environmental conditions. These local communication systems serve as mediators that provide location information through signal strength measurement, working reliably at night or in bad weather when GPS satellite signals may be weakened or blocked
4Measurement precision
If CarFi system uses Wi-Fi CSI and LSTM classifier, then rider side determination accuracy is improved to 95.44%, but computation complexity increases
Solution Approach 1:
The patent transforms complex Wi-Fi channel state information into simplified amplitude and phase parameters that can be processed by the LSTM classifier. By changing the representation parameters of the RF signals and focusing on key features like signal strength and phase difference, the system achieves high accuracy while managing computation complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
CarFi effectively determines the rider's side with high accuracy, reducing the time spent on location and emissions, while maintaining user privacy and efficiency, even in challenging environments, and can be implemented on embedded GPUs for real-time operation.
Implementation Method 1
a mobile device includes a long-range transceiver, a medium-range transceiver, and a controller. The controller is configured to receive, from the long-range transceiver, a target ID associated with a remote medium-range transceiver
Implementation Method 2
extract received signal strength indicator (RSSI) data from the packets, filter the RSSI data to obtain a maximum RSSI signal within a window of time, in response to the maximum RSSI signal exceeding a threshold, output a signal indictive of the remote system being less than a predetermined distance away
Data Source
AI summary
In one embodiment a mobile device includes a long-range transceiver, a medium-range transceiver, and a controller. The controller is configured to receive, from the long-range transceiver, a target ID associated with a remote medium-range transceiver of a remote system, transmit, via the long-range transceiver, an ID, channel, and band of the medium-range transceiver of the remote system, receive packets from the remote medium-range transceiver on the channel, extract received signal strength indicator (RSSI) data from the packets, filter the RSSI data to obtain a maximum RSSI signal within a window of time, in response to the maximum RSSI signal exceeding a threshold, output a signal indictive of the remote system being less than a predetermined distance away.