Autonomous Vehicle Control System for Guided-Path Collision Prevention
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Solution Overview
Problem
Existing control systems for guided-path vehicles in amusement parks rely heavily on operator skill and centralized computers, leading to challenges in preventing vehicle-to-vehicle and vehicle-to-obstacle collisions, particularly for large and heavy vehicles with slow propulsion systems, and struggle with efficient parking and navigation, especially in environments with limited visibility and curved paths.
Innovation Solution
A distributed control system is implemented on each vehicle, using GPS, inertial navigation, and communication modules to determine vehicle position and state, automatically maintaining safe distances and preventing collisions without human intervention, and enabling autonomous parking and navigation along predetermined paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If operator-driven control is used for guided-path vehicles, then human operators can manually control vehicle speed and position, but collisions between vehicles and obstacles cannot be reliably prevented
Solution Approach 1:
The control system enables vehicles to autonomously determine their own position using GPS and inertial navigation data, calculate distances to other vehicles and obstacles, and automatically adjust speed without continuous human intervention. Each vehicle independently manages its own safety and navigation, eliminating reliance on manual operator control for collision prevention.
Solution Approach 2:
The system continuously receives position data from GPS and inertial navigation sensors, processes this information through a control algorithm, and provides real-time feedback by automatically adjusting vehicle speed based on calculated distances to other vehicles and obstacles. This closed-loop feedback mechanism ensures reliable collision prevention through automated response.
2Reliability
If centralized control systems are used to detect vehicle positions and maintain safe spacing, then collision prevention is improved, but system complexity and response time increase
Solution Approach 1:
The control system is segmented and distributed across individual vehicles rather than centralized. Each vehicle independently executes the control algorithm using its own position data and calculated distance to other vehicles, dividing the control function into autonomous units that operate independently but coordinate through shared position information.
Solution Approach 2:
Each vehicle autonomously determines its position, calculates its distance to other vehicles using the formula distance = |position1 - position2|, and adjusts its speed without requiring centralized control decisions. The system distributes the control intelligence to individual vehicles, reducing central system complexity while maintaining safe spacing.
3Quantity of substance
If large and heavy vehicles with slow propulsion systems are used, then payload capacity is improved, but collision avoidance capability deteriorates due to slow response to propulsion commands
Solution Approach 1:
The control system continuously monitors position data and calculates potential collision risks in advance using the distance calculation algorithm. When a potential hazard is detected, the system initiates speed adjustment commands before a collision becomes imminent, allowing slow-response vehicles adequate time to react and maintain safe spacing despite their sluggish propulsion response characteristics.
4Ease of operation
If manual parking procedures are used at load and unload positions, then vehicle positioning can be adjusted, but ride throughput is reduced due to time-consuming manual parking operations
Solution Approach 1:
The control system enables vehicles to autonomously navigate to and park at load and unload positions by continuously monitoring position data, calculating distance to the target position, and automatically adjusting speed to achieve precise stopping. This eliminates manual parking operations and significantly improves ride throughput by reducing the time vehicles spend at stations.
Data Source
AI summary
A ride control system that uses a state determination assembly to determine vehicle position and speed of the vehicle. The control system automatically prevents collisions between the controlled vehicle and other vehicles and obstacles along the vehicle's path without human operator intervention based on its position and speed as well as that of the other vehicles and the position and current operating state of upcoming obstacles. The control system automatically maintains a predetermined clearance between the controlled vehicle and other vehicles and obstacles, such as on a ride path, without human operator intervention regardless of vehicle inertia. The control system may be configured to automatically position and/or park a vehicle anywhere along the ride path with a high degree of accuracy in a minimum amount of parking time, without human operator intervention, and regardless of vehicle inertia.