Autonomous Follower Mode for Surface Street Navigation
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Solution Overview
Problem
Autonomous vehicles face challenges in safely navigating surface streets due to their narrower lanes, higher population density, and unpredictable features like unprotected left turns, crosswalks, and construction zones, leading to inefficiencies and costly infrastructure solutions or reliance on human drivers.
Innovation Solution
Autonomous vehicles transition from highway driving to a semi-autonomous follower mode by using visual fiducials to pair with a manually driven guide vehicle, allowing them to navigate surface streets based on both sensor data and the guide vehicle's behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous vehicles operate in fully autonomous mode on highways, then automation level is high, but navigation capability on surface streets deteriorates
Solution Approach 1:
The system dynamically transitions between fully autonomous mode and semi-autonomous follower mode based on the driving environment. On highways, the vehicle operates in fully autonomous mode with high automation level. When approaching surface streets, it transitions to semi-autonomous follower mode where it follows a guide vehicle, thereby adapting the automation level to match the environmental complexity and maintaining navigation capability.
2Productivity
If shipping facilities are constructed near highway exits, then delivery efficiency is improved, but infrastructure cost increases
Solution Approach 1:
A manually driven guide vehicle serves as an intermediary between the autonomous vehicle and the complex surface street environment. The guide vehicle leads the autonomous vehicle through challenging surface street conditions, enabling the autonomous vehicle to reach delivery destinations without requiring specialized infrastructure like shipping facilities near highway exits or transition stations, thereby reducing infrastructure costs while maintaining delivery efficiency.
3Adaptability or versatility
If human drivers take over during surface street portions, then navigation capability is improved, but operational cost increases
Solution Approach 1:
The autonomous vehicle creates a behavioral copy of the human driver by following the guide vehicle's actions. Instead of requiring a human driver to physically occupy the autonomous vehicle, the system uses sensors to detect and replicate the guide vehicle's driving behaviors, thereby achieving human-level navigation capability on surface streets without the operational cost of employing human drivers for each trip.
4Ease of operation
If transition stations are deployed, then driver transition is facilitated, but time efficiency deteriorates
Solution Approach 1:
The semi-autonomous follower mode enables continuous operation without interruption. The autonomous vehicle maintains continuous motion while following the guide vehicle through surface streets, eliminating the need to stop at transition stations for driver changes. This preserves time efficiency while still facilitating the transition from highway to surface street navigation through the guide vehicle's leadership.
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 approach eliminates the need for costly infrastructure and human intervention, enhancing efficiency and safety by enabling autonomous vehicles to navigate complex surface streets while reducing operational costs.
Implementation Method 1
The autonomous vehicle may locate the guide vehicle using one or more optical sensors, for example one or more cameras and/or one or more TOF sensors (e.g., LIDAR sensors). In some embodiments, the autonomous vehicle may locate the guide vehicle using one or more visual fiducials (e.g., a QR code or other optical code) provided on the guide vehicle.
Data Source
AI summary
An exemplary vehicle comprises: one or more sensors; one or more processors; and one or more computer readable media storing instructions that, when executed by the one or more processors, cause the vehicle to: operate in an autonomous driving mode, wherein an operation in the autonomous driving mode comprises performing one or more driving operations based on road and environmental conditions detected by the one or more sensors; detect, by the one or more sensors, a first visual fiducial; and in response to detecting the first visual fiducial, operate in a semi-autonomous follower mode, wherein an operation in the semi-autonomous follower mode comprises performing one or more driving operations based on road and environmental conditions detected by the one or more sensors and one or more behaviors of a guide vehicle.