Autonomous Vehicle Sensor Array for On-Demand Rail Scheduling
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Solution Overview
Problem
Current technologies for autonomous vehicles on tracks, such as trains, face limitations in providing flexible and safe transportation due to fixed schedules and limited sensor data quality, which can lead to unsafe operations.
Innovation Solution
The implementation of a system using a combination of sensing and artificial intelligence techniques, including active and passive sensors, allows autonomous vehicles to dynamically detect and respond to events on the track, enabling on-demand scheduling and safe navigation by adjusting movement based on real-time sensor feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed schedules are used for train operations, then operational simplicity is maintained, but flexibility and adaptability to real-time conditions deteriorate
Solution Approach 1:
The system implements continuous feedback loops where sensor data from multiple vehicles and track conditions are constantly monitored and fed back to the central controller. This enables dynamic schedule adjustment based on real-time conditions while maintaining operational simplicity through automated decision-making algorithms.
Solution Approach 2:
The scheduling system transitions from static fixed schedules to dynamic adaptive scheduling. The system continuously adjusts vehicle routes, speeds, and timing based on real-time sensor feedback, passenger demand, and track conditions, enabling flexibility without proportionally increasing system complexity.
2Measurement precision
If limited sensor systems are used in trains, then device complexity is reduced, but measurement precision and detection capability deteriorate
Solution Approach 1:
The patent combines multiple sensor types (active sensors like LiDAR and radar, passive sensors like cameras) into an integrated sensor array system. This merging approach enhances measurement precision and detection capability while managing complexity through unified processing and fusion algorithms.
Solution Approach 2:
The sensor array system is designed with multi-functionality, where the same sensor suite serves multiple purposes: obstacle detection, passenger monitoring, track condition assessment, and communication with other vehicles. This universal approach maximizes measurement precision without proportionally increasing system complexity.
3Reliability
If autonomous vehicles operate independently without coordination, then system complexity is reduced, but safety and reliability deteriorate due to undetected events
Solution Approach 1:
Vehicles continuously exchange sensor data and status information with each other and the central controller through a communication network. This feedback mechanism enables coordinated safety responses to detected events while maintaining operational independence, improving reliability without excessive complexity.
Solution Approach 2:
A central controller or cloud-based platform acts as an intermediary that receives data from all vehicles, processes information using AI algorithms, and coordinates safety responses. This intermediary approach enhances reliability by enabling system-wide awareness and coordination while keeping individual vehicle complexity manageable.
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
This approach enables flexible, on-demand transportation while ensuring passenger safety by dynamically adjusting vehicle movement in response to detected events, improving operational efficiency and safety on railway and adjacent systems.
Implementation Method 1
dynamically identify reflectance of the event from a plurality of events using a sensor array system
Data Source
AI summary
In an example, the autonomous vehicle (“AV”) can be configured among the other vehicles and railway to communicate with a rider on a peer to peer basis to pick up the rider on demand from a location on a track, like a railway, tram or other track, rather than the rider being held hostage to a fixed railway schedule. The rider can have an application on his/her cell phone, which tracks each of the AVs, and contact them using the application on the cell phone. In an example, the AV is configured for both on-track and off track operation with different operating parameters for on-track and off track, including speed, degree of autonomy, sensors used etc.