Cloud Control Architecture for Vehicle Speed Trajectory Optimization

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Solution Overview

Problem

Existing vehicle control systems for autonomous and platooning operations face inefficiencies in optimizing fuel consumption and operational costs, particularly in managing vehicle spacing and speed trajectories, which limits their effectiveness in reducing fuel costs and improving operation efficiency.

Innovation Solution

A cloud computing control system that communicates with vehicle controllers to determine optimal speed trajectories and neutral coasting commands based on various driving factors, including static and dynamic conditions, to manage vehicle spacing and formation, enabling efficient platooning and autonomous vehicle operations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Use of energy by moving object

If existing vehicle control systems are used for autonomous and platooning operations, then basic vehicle control functions are maintained, but fuel consumption optimization and operational efficiency are insufficient

Engineering Contradiction:

Improvefuel consumptionVSAvoidoperational efficiency

Core Design Contradiction:

Use of energy by moving objectVSProductivity

Solution Approach 1:

The system performs preliminary actions by determining optimal speed trajectories and neutral coasting commands in advance based on static and dynamic driving factors. The cloud computing control system calculates and communicates these optimal parameters to vehicle controllers before execution, enabling proactive fuel consumption optimization rather than reactive control adjustments.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts speed trajectories and coasting commands based on real-time driving factors including traffic conditions, road grade, and vehicle spacing. The cloud computing control system continuously receives updated information and recalculates optimal parameters, allowing the vehicle operations to adapt dynamically to changing conditions for improved fuel efficiency and operational effectiveness.

Inventive Principle:

Principle #15Dynamics

2Use of energy by moving object

If vehicle spacing and speed trajectories are not optimized, then control simplicity is maintained, but fuel costs and operational costs increase

Engineering Contradiction:

Improvefuel costsVSAvoidcontrol system complexity

Core Design Contradiction:

Use of energy by moving objectVSDevice complexity

Solution Approach 1:

The cloud computing control system serves as an intermediary between environmental sensing and vehicle control execution. It receives driving factors from various sources, processes this information to determine optimal speed trajectories and coasting commands, then communicates these parameters to vehicle controllers. This intermediary architecture centralizes the computational complexity while keeping individual vehicle control units relatively simple.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system optimizes fuel costs by dynamically changing key operational parameters including speed trajectories, coasting timing, and vehicle spacing distances. The cloud computing control system calculates optimal values for these parameters based on driving factors and communicates them to vehicle controllers, enabling parameter-based optimization without requiring fundamental changes to vehicle hardware or control architecture.

Inventive Principle:

Principle #35Parameter changes

3Productivity

If cloud computing control system is implemented to determine optimal speed trajectories, then fuel consumption is optimized, but system complexity and communication requirements increase

Engineering Contradiction:

Improveoperational efficiencyVSAvoidcontrol system architecture

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The cloud computing control system performs multiple functions including receiving and processing various driving factors (traffic conditions, road grade, weather), calculating optimal speed trajectories, determining neutral coasting commands, and managing platooning coordination. This multi-functional centralized system replaces what would otherwise require complex distributed intelligence in each vehicle, achieving operational efficiency improvements while consolidating system complexity in a dedicated cloud platform.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS11022981B2Control architecture for predictive and optimal vehicle operations in a single vehicle environment

Publication Date: 2021.06.01 CUMMINS INC

AI summary

There is disclosed a cloud computing control system for vehicle speed control and also for control of a vehicle in a platoon. The cloud computing control system determines a speed trajectory and neutral coasting command for a first vehicle of the platoon and a vehicle controller determines a reference speed for the first vehicle in response to the speed trajectory and the neutral coasting command, and is response to one or more vehicle specific factors associated with the first vehicle.