In-Vehicle Passenger Counting for Missed Re-Boarding Detection
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Solution Overview
Problem
Existing vehicle systems fail to accurately identify and re-board passengers who temporarily alight at intermediate stops and re-board later, leading to potential missed pickups.
Innovation Solution
A vehicle system that uses cameras and AI agents to photograph and analyze the interior, check passenger numbers, and communicate with passengers through facial expressions, gestures, and speech messages to guide re-boarding, including identifying re-boarding points and notifying passengers of their location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing vehicle systems only notify remaining passengers without monitoring re-boarding, then the system complexity is low, but passengers who temporarily alight and fail to re-board are not identified
Solution Approach 1:
The system continuously monitors passenger numbers at multiple stops and provides feedback by comparing expected vs. actual passenger counts. When a discrepancy is detected (passenger not re-boarded), the system notifies the driver and provides re-boarding guidance, creating a closed-loop monitoring system that improves reliability without requiring complex manual intervention
Solution Approach 2:
The system automatically performs passenger counting, comparison, and notification functions without requiring manual intervention. The passenger monitoring system serves itself by autonomously detecting missing passengers and initiating re-boarding procedures, reducing the need for additional complex monitoring infrastructure
2Reliability
If the vehicle stops frequently to pick up passengers, then all passengers can be ensured to re-board, but the travel time increases
Solution Approach 1:
The system performs preliminary identification of passengers who need to re-board by analyzing passenger count changes at intermediate stops. By detecting missing passengers before the vehicle departs, the system enables targeted stops only when necessary, rather than making routine stops at every location, thus maintaining reliability while minimizing time loss
Solution Approach 2:
The system dynamically adjusts the stopping schedule based on real-time passenger monitoring data. Stops are made selectively only when passenger count analysis indicates someone needs to re-board, rather than following a fixed schedule. This dynamic approach ensures all passengers are picked up while optimizing travel time by avoiding unnecessary stops
3Measurement precision
If the system monitors all passengers at every stop, then no passenger is missed, but the processing time and computational load increase
Solution Approach 1:
The system extracts and focuses monitoring efforts only on relevant stops where passenger count changes indicate potential missed passengers. By analyzing delta changes in passenger numbers rather than counting all passengers at every stop, the system maintains high measurement precision while significantly reducing processing time and computational load
Data Source
AI summary
A vehicle, in a temporary stop state during driving, is configured to identify a passenger failing to re-board after alighting, and communicate with the passenger to guide the passenger to re-board the vehicle. A method of controlling the vehicle includes primarily checking a number of passengers inside the vehicle through analysis of a first image obtained by photographing an interior of the vehicle when the vehicle enters a stop state during driving; in response to the vehicle being restarted after the stop, secondly checking the number of the passengers inside the vehicle through analysis of a second image obtained by photographing the interior of the vehicle; and in response to the secondly checked number of the passengers being less than the primarily checked number of the passengers, identifying that the passenger failing to re-board after alighting from the vehicle exists.