Vehicle-to-Cloud Traffic Map Generation for Autonomous Driving
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Solution Overview
Problem
Autonomous driving vehicles (ADVs) face challenges in detecting real-time road conditions and routing efficiently due to limited perception with current sensor technologies, struggling to navigate through unusual conditions like temporary road construction zones without real-time traffic information.
Innovation Solution
A vehicle-to-cloud system that uses sensors on ADVs to detect real-time road conditions, transmitting data to a central monitoring system to generate and broadcast updated traffic maps among ADVs, allowing them to plan and control routes based on real-time information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ADVs rely only on onboard sensors for navigation, then the vehicle can operate autonomously with minimal human interaction, but the perception range is limited to certain distance and cannot detect unusual road conditions miles away
Solution Approach 1:
The patent introduces a cloud-based traffic information server as an intermediary between ADVs and real-time traffic conditions. The server collects, processes, and distributes traffic information from multiple sources to ADVs, extending their perception capability beyond physical sensor range. This mediator enables ADVs to access traffic conditions miles away without compromising their autonomous navigation capability.
2Ease of operation
If ADVs use only their own sensor data for routing decisions, then the vehicle maintains operational independence, but it cannot route the smartest or fastest route without real-time road/traffic conditions information
Solution Approach 1:
The system implements a feedback mechanism where ADVs transmit their sensor data and detected traffic conditions to the cloud server, which processes this information and feeds back optimized routing recommendations to the ADVs. This closed-loop feedback enables routing optimization based on real-time road conditions while maintaining the ADVs' operational independence through intelligent decision support.
3Measurement precision
If ADVs transmit all sensor data to cloud server for map updates, then real-time traffic information accuracy improves, but data transmission volume and network bandwidth consumption increase
Solution Approach 1:
The patent extracts and transmits only the essential traffic information elements to the cloud server, such as detected unusual road conditions, traffic patterns, and relevant environmental data, rather than transmitting complete sensor datasets. This selective extraction maintains traffic condition detection accuracy while significantly reducing data transmission volume and network bandwidth consumption.
Data Source
AI summary
In one embodiment, a system monitors states of an autonomous driving vehicle (ADV) using a number of sensors mounted on the ADV. The system perceives a driving environment surrounding the ADV using at least a portion of the sensors. The system analyzes the states in view of the driving environment to determine a real-time traffic condition at a point in time. The system determines whether the real-time traffic condition of the driving environment matches at least a predetermined traffic condition. The system transmits data concerning the real-time traffic condition to a remote server over a network to allow the remote server to generate an updated map having real-time traffic information, in response to determining the real-time traffic condition is unknown. In response to receiving the updated map, the system plans and controls the ADV based on the updated map.