Road Train Dolly Collision Avoidance Using Tractor-Mounted Sensors
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Solution Overview
Problem
Existing collision avoidance systems for road trains, particularly airport cargo tractors pulling dollies, face challenges due to practical and geometrical constraints that prevent the installation of sensors on dollies, making it difficult to detect collisions between dollies and obstacles.
Innovation Solution
A collision avoidance system for road trains that relies on sensors installed on the tractor, using exteroceptive and proprioceptive sensors to detect environmental data, compute trajectories, and determine potential collisions, with an interface to alert the operator or autonomously actuate brakes to avoid collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are installed on dollies to detect collisions, then collision detection accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The patent extracts the sensing function from the dollies and relocates it to the tractor. The exteroceptive sensors (cameras, LIDAR, radar) are mounted on the tractor to detect obstacles in the environment, while proprioceptive sensors on the tractor monitor the road train's own position and orientation. This eliminates the need for sensors on each dolly, reducing system complexity while maintaining collision detection capability through centralized sensing and distributed trajectory computation.
Solution Approach 2:
The tractor-mounted sensors serve multiple functions: they detect obstacles for the entire road train, monitor the environment for all dollies, and provide data for computing trajectories of the tractor and each dolly. This multi-functional approach replaces what would otherwise require separate sensor systems on each dolly, reducing overall system complexity while improving measurement precision through higher-quality sensors on the tractor.
2Loss of information
If rearview mirrors are installed to allow operator viewing of dollies, then operator awareness is improved, but geometrical constraints prevent practical installation
Solution Approach 1:
The patent replaces the mechanical optical system of rearview mirrors with an electronic sensing and computation system. Exteroceptive sensors (cameras, LIDAR) capture environmental data, while proprioceptive sensors provide position and orientation information. The processor computes the trajectories of all dollies based on this data and detects potential collisions algorithmically, eliminating the need for physical mirrors and providing superior awareness capability.
3Reliability
If sensors are installed on each dolly for independent detection, then collision detection reliability is improved, but ease of manufacture and deployment deteriorates
Solution Approach 1:
The patent merges all sensing functions into the tractor, combining exteroceptive sensors for environmental detection and proprioceptive sensors for self-monitoring into a single centralized system. The processor on the tractor computes trajectories for the entire road train, including all dollies, based on this unified sensor data. This merged approach simplifies manufacturing and deployment, as only the tractor needs to be equipped with sensors, while maintaining reliability through comprehensive environmental awareness and accurate trajectory computation for all components.
Data Source
AI summary
A collision avoidance system for road trains that relies strictly on sensors installed on the tractors yet is effective at avoiding collisions between the dollies and obstacles and a method for operating the system are disclosed. The collision avoidance system includes at least one exteroceptive sensor mounted to the tractor and configured to acquire environmental data, at least one proprioceptive sensor mounted to the tractor and configured to acquire a tractor direction, a tractor speed and/or a tractor velocity, and at least one processor configured to detect objects based on the environmental data, compute a trajectory of each of the at least one dolly based on dimensions of the tractor, dimensions of the at least one dolly, a number of the at least one dolly, the tractor direction, the tractor speed and/or the tractor velocity, and determine whether the trajectory intersects a boundary of one of the objects.