Cargo Trailer Sensor Assembly Blind Spot Reduction
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Solution Overview
Problem
Semi-trailer trucks face significant safety risks due to large blind spots and complex low-speed maneuvering challenges, despite public safety measures, as existing technologies fail to adequately address these issues.
Innovation Solution
The integration of sensor assemblies on cargo trailers, which include cameras, LIDAR sensors, and communication interfaces, replacing traditional lamp assemblies to provide real-time sensor data to the self-driving tractor's control system, enhancing visibility and control during low-speed maneuvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor assemblies are integrated on cargo trailers to eliminate blind spots, then safety and visibility are improved, but device complexity increases
Solution Approach 1:
The sensor assembly integrates multiple functions including cameras, LIDAR sensors, and communication interfaces within a single modular unit that can replace traditional lamp assemblies. This multi-functional approach eliminates blind spots while managing complexity through consolidation of sensors, power management, and data transmission capabilities into unified components.
Solution Approach 2:
The sensor system is divided into discrete modular assemblies distributed at strategic locations on the cargo trailer. Each assembly operates independently but communicates with the tractor's control system, allowing the complex safety function to be broken into manageable segments that can be installed and maintained separately.
2Loss of information
If traditional lamp assemblies are replaced with sensor assemblies, then environmental data collection is improved, but manufacturing complexity increases
Solution Approach 1:
The sensor assemblies utilize standardized mounting interfaces and communication protocols that replicate existing lamp assembly form factors and electrical connections. This allows manufacturers to produce sensor units using similar manufacturing processes as traditional lighting components, reducing the impact on manufacturing ease while enabling comprehensive environmental data collection.
3Measurement precision
If sensor assemblies are used during low-speed maneuvers, then control precision is improved, but energy consumption increases
Solution Approach 1:
The sensor assemblies operate in periodic cycles, activating high-power sensors like LIDAR only when low-speed maneuvers are detected or during critical operational phases. During normal cruising, sensors operate at reduced power or in standby mode, maintaining measurement precision when needed while significantly reducing overall energy consumption.
Solution Approach 2:
The sensor system dynamically adjusts its operational state based on vehicle speed, maneuver type, and environmental conditions. Control precision is optimized during low-speed maneuvers through full sensor activation, while energy consumption is reduced during high-speed steady-state operation through selective sensor deactivation or reduced-power modes.
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 significantly reduces or eliminates blind spots and improves safety by providing the self-driving tractor with comprehensive environmental data, enabling safer operation and compliance with lighting requirements.
Implementation Method 1
The sensor assembly can include a LIDAR sensor
Data Source
AI summary
A sensor assembly can include a housing that includes a view pane and a mounting feature configured to replace a trailer light of a cargo trailer of a semi-trailer truck. The sensor assembly can also include a lighting element mounted within the housing to selectively generate light, and a sensor mounted within the housing and having a field of view through the view pane. The sensor assembly can also include a communication interface configured to transmit sensor data from the sensor to a control system of the self-driving tractor.