Cloud Platoon Acceleration Control for Mode Switching and Delay Handling
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Solution Overview
Problem
Conventional vehicle platoon following systems face challenges such as delayed response times, irrational acceleration decisions, and inadequate handling of multiple obstacles, particularly when switching between manual and autonomous modes.
Innovation Solution
A vehicle platoon following system based on cloud computing that includes a leading vehicle processing unit, following vehicle processing units, and a cloud processing unit, which generates and adjusts acceleration ranges, performs mode judgment, parameter uniformization, and acceleration estimation to calculate optimal platoon accelerations, while also diagnosing signal delays and handling obstacle scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional vehicle platoon following deciding technologies are used, then the system structure is simple, but the response time is delayed and the acceleration decisions are irrational
Solution Approach 1:
The patent introduces a cloud processing unit as an intermediary between vehicles to perform centralized decision-making. The cloud processing unit receives data from multiple vehicles, performs comprehensive analysis including acceleration estimation and mode judgment, then returns optimized control decisions. This mediator architecture enables complex computations that improve response speed and decision quality without requiring each vehicle to have high-complexity onboard systems.
Solution Approach 2:
The patent transitions from distributed onboard processing to centralized cloud-based processing, adding a new dimensional layer to the system architecture. By moving the decision-making function to the cloud dimension, the system achieves faster and more rational acceleration decisions while keeping individual vehicle units relatively simple.
2Productivity
If autonomous vehicle platoon following is implemented, then operation efficiency is improved, but the cost of hardware and manpower increases
Solution Approach 1:
The patent merges the computing resources of multiple vehicles into a centralized cloud processing unit. Instead of each vehicle requiring independent high-performance autonomous driving hardware, the system combines processing power in the cloud, reducing hardware requirements at the vehicle level. This sharing approach maintains high operation efficiency while reducing overall hardware and manpower costs.
Solution Approach 2:
The cloud processing unit serves multiple vehicles simultaneously, performing universal decision-making functions for the entire platoon. This multi-functional approach allows a single centralized system to handle what would otherwise require multiple independent autonomous driving systems, reducing redundant hardware and manpower resources.
3Reliability
If conventional platoon following control is used, then the control system is simple, but the handling of multiple obstacles and delay diagnosis is inadequate
Solution Approach 1:
The patent implements comprehensive feedback mechanisms where the cloud processing unit continuously receives data from vehicles, analyzes obstacle situations, and adjusts control decisions in real-time. The system performs delay diagnosis by monitoring communication timestamps and adjusts for signal delays. This feedback loop enables reliable obstacle handling and delay compensation without requiring overly complex local systems at each vehicle.
Solution Approach 2:
The cloud processing unit performs preliminary analysis of potential obstacle scenarios and prepares decision strategies in advance. By pre-processing data and anticipating obstacle situations, the system can respond more reliably when obstacles appear, while maintaining a relatively simple structure through proactive rather than reactive complexity.
4Adaptability or versatility
If manual mode switching is implemented, then driving flexibility is improved, but the rationality of acceleration during mode switching deteriorates
Solution Approach 1:
The cloud processing unit acts as an intermediary that manages mode switching between manual and autonomous driving. When mode switching occurs, the cloud receives notifications, performs comprehensive analysis of the situation, and returns optimized acceleration commands. This mediator ensures rational acceleration control during transitions while preserving driving mode flexibility.
Solution Approach 2:
The system dynamically changes control parameters based on driving mode. The cloud processing unit adjusts acceleration ranges, response thresholds, and control strategies according to whether the vehicle is in manual or autonomous mode. This parameter adaptation enables flexible mode switching while maintaining precise and rational acceleration control through cloud-based parameter optimization.
Data Source
AI summary
A vehicle platoon following deciding system based on cloud computing is configured to decide a plurality of vehicle platoon accelerations of a leading vehicle and at least one following vehicle. A cloud processing unit receives a leading vehicle parameter group and at least one following vehicle parameter group. The cloud processing unit is configured to implement a cloud deciding step. The cloud deciding step includes judging whether the leading vehicle is manually driven according to the leading vehicle parameter group to generate a driving mode judging result, calculating a driving acceleration range according to a leading vehicle acceleration range and at least one following vehicle acceleration range, estimating a compensated acceleration according to the leading vehicle parameter group, and calculating the vehicle platoon accelerations according to the driving mode judging result and at least one of the driving acceleration range and the compensated acceleration.