Cooperative Trajectory Control for Retrofitted Self-Driving Vehicles
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Solution Overview
Problem
Conventional self-driving vehicles face challenges in maintaining high safety levels, especially in non-standard situations like construction sites or heavy weather conditions, leading to inefficiencies in traffic flow and potential safety issues, as they rely on individual vehicle strategies without adequate coordination.
Innovation Solution
A method involving retrofitting commercial vehicles with a combination of first and second localization sensors, such as ground-penetrating radar and cameras, and communicating with smart infrastructure to derive a cooperative strategy for trajectory organization, enabling self-driving at safety level L4 by combining vehicle and infrastructure data for accurate localization and status information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If self-driving vehicles use individual vehicle strategies with standard sensors, then device complexity is reduced, but safety level and reliability deteriorate in non-standard situations
Solution Approach 1:
The patent combines multiple localization sensors (first localization sensor for self-positioning and second localization sensor for object-localization) into a unified sensor system. This merging of sensors with different functionalities enables the vehicle to achieve high safety level L4 by comprehensively acquiring localization information, thereby resolving the contradiction between safety improvement and system complexity
Solution Approach 2:
The sensor system is designed with multi-functionality, where the first localization sensor determines self-positioning and the second localization sensor determines object positions. This universal sensor configuration can handle both standard and non-standard situations, achieving high reliability without requiring completely different sensor setups for different scenarios
2Reliability
If self-driving vehicles increase safety margins during acceleration, then safety level is improved, but traffic flow efficiency deteriorates due to ripple effect
Solution Approach 1:
The patent implements a feedback mechanism where localization data from multiple sensors continuously monitors the vehicle's position and surrounding objects. This real-time feedback enables dynamic adjustment of safety margins based on actual traffic conditions, allowing the vehicle to maintain high safety levels while adapting to traffic flow requirements and avoiding the ripple effect
Solution Approach 2:
The safety margin is made dynamic rather than static. The system adjusts safety margins in real-time based on localization data and traffic conditions, enabling the vehicle to optimize between safety and traffic flow efficiency. This dynamic approach resolves the contradiction by allowing safety margins to adapt to changing situations
3Adaptability or versatility
If conventional self-driving modes are used without infrastructure support, then ease of operation is maintained, but ability to handle unknown dangerous situations deteriorates
Solution Approach 1:
The patent introduces smart infrastructure as an intermediary that provides additional localization data and status information. This intermediary enables the vehicle to handle unknown dangerous situations by supplementing sensor data with infrastructure-provided information, thereby improving adaptability without requiring complex changes to the vehicle's core self-driving system
Data Source
AI summary
A method of organizing a trajectory of at least one self-driving vehicle including providing the vehicle having a first localization sensor and a second localization sensor, wherein the functionality of the sensors are different; driving the vehicle in a self-driving mode in a lane; determining the localization of the vehicle, using at least one of the first localization sensor and the second localization sensor, with an accuracy of at least 25 cm in order to obtain a first data set; providing a smart infrastructure in proximity to the lane comprising one or more status sensors arranged along the lane; determining a status information of the vehicle by the smart infrastructure, using the one or more status sensors, in order to obtain a second data set, and coordinating the first data set and the second data set to derive a cooperative strategy for organizing the trajectory of the vehicle.