Autonomous Rail Vehicle Dynamic Scheduling via Sensor Fusion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current railway systems lack the flexibility and efficiency in managing autonomous vehicles, as they are often restricted to fixed schedules and lack advanced sensor technologies for real-time navigation and anomaly detection, which limits their ability to adapt to dynamic environments and passenger demands.
Innovation Solution
The implementation of a system that combines active and passive sensors with artificial intelligence to enable autonomous vehicles to dynamically detect and respond to events on railway tracks, allowing for on-demand movement and flexible scheduling by using sensor arrays with processors and memory devices to adjust movement based on detected reflectance data from various events, including anomalies and stationary features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional fixed railway schedules are used, then operational simplicity is maintained, but system adaptability and responsiveness to passenger demands deteriorate
Solution Approach 1:
The railway system transitions from static fixed schedules to dynamic on-demand scheduling. The autonomous vehicles continuously receive sensor data from sensor arrays and adjust their routes, speeds, and timing in real-time based on current conditions, passenger demands, and detected events, making the entire system adaptive and responsive rather than rigid and predetermined
Solution Approach 2:
The system implements continuous feedback loops where sensor arrays detect events and conditions, processors analyze the data, and the autonomous vehicles adjust their operations accordingly. This closed-loop control enables the system to respond to changing conditions and optimize performance dynamically while maintaining operational coherence
2Measurement precision
If advanced sensor arrays with multiple sensor systems are implemented, then measurement precision and event detection capability are improved, but device complexity and cost increase
Solution Approach 1:
The patent combines multiple sensor types (active sensors like radar/LiDAR and passive sensors like cameras) into an integrated sensor array system. These diverse sensors work together synergistically to detect various events and conditions, achieving comprehensive monitoring capability while sharing processing resources and data fusion algorithms to manage complexity
Solution Approach 2:
The sensor array system is designed to perform multiple functions: detecting events, tracking vehicles, monitoring passenger conditions, navigating tracks, and identifying anomalies. This multi-functional approach allows a single integrated system to replace multiple specialized systems, improving measurement precision across different detection tasks while avoiding the complexity of separate independent systems
3Adaptability or versatility
If autonomous vehicles operate mechanically disconnected from other vehicles on the rail, then operational flexibility and on-demand scheduling are improved, but coordination difficulty and potential conflicts increase
Solution Approach 1:
The system introduces a central control server as an intermediary that coordinates between mechanically disconnected autonomous vehicles. The server receives data from all vehicles and sensor arrays, processes routing and scheduling information, and issues coordination commands to prevent conflicts and optimize overall system efficiency while maintaining the operational independence of individual vehicles
Solution Approach 2:
The system performs preliminary routing calculations, conflict detection, and scheduling decisions before vehicles execute their movements. The central server pre-coordinates routes and timing for multiple vehicles to prevent conflicts, allowing each vehicle to operate independently while maintaining system-wide coordination through advance planning
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 solution enables autonomous vehicles to operate more safely and efficiently by dynamically adjusting their movement in real-time, creating a demand-based schedule rather than a fixed one, and allows for seamless integration with adjacent transportation systems like roadways or waterways, enhancing passenger convenience and system adaptability.
Implementation Method 1
dynamically detect a reflectance of an event from a plurality of events, the event being selected from an anomaly, a stationary feature, or a location of one of the other plurality of vehicles
Data Source
AI summary
The present invention provides an autonomous vehicle (“AV”) configured on a railway system. The 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, 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.