Autonomous Vehicle Mission Control for Muddy Terrain Load Adaptation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous vehicles face challenges in maintaining energy efficiency, productivity, and vehicle longevity when operating in confined geographical areas with varying and unpredictable environments, particularly in hilly and muddy terrains, which affect traction control and increase energy consumption and wear.
Innovation Solution
A computer system that processes travel mission data and real-time road conditions to adjust driving modes and load capacities, determining drivability impacts and adapting traction control levels and load capacities to optimize vehicle performance and reduce wear.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous vehicles operate in hilly and muddy terrains with heavy loads, then transport productivity is maintained, but energy consumption increases and vehicle wear increases
Solution Approach 1:
The system dynamically adjusts driving modes and load capacities based on real-time road condition data and drivability impact assessments. The computer system modifies vehicle operation parameters adaptively to match actual terrain conditions, enabling the vehicle to maintain productivity while optimizing energy usage in varying environmental conditions
Solution Approach 2:
The system changes operational parameters such as driving mode and load capacity based on determined drivability impact. By adjusting these parameters in response to road condition data, the system resolves the contradiction between maintaining transport productivity and reducing energy consumption in challenging terrains
2Productivity
If autonomous vehicles operate in hilly and muddy terrains with heavy loads, then transport productivity is maintained, but vehicle wear increases
Solution Approach 1:
The system dynamically adjusts driving modes and load capacities based on real-time road condition data and drivability impact assessments. By continuously adapting operation parameters to match actual terrain conditions, the system maintains productivity while reducing unnecessary component wear and extending vehicle service life
Solution Approach 2:
The system changes operational parameters such as driving mode and load capacity based on determined drivability impact. These parameter adjustments protect the vehicle from excessive wear in challenging terrains while maintaining transport productivity
3Productivity
If real-time road condition data and drivability impact assessment are implemented, then vehicle efficiency and productivity are optimized, but system complexity increases
Solution Approach 1:
The computer system performs multiple functions including receiving travel mission data, obtaining real-time road condition data, determining drivability impact, and adapting driving modes within a single integrated platform. This multi-functional approach optimizes vehicle efficiency while managing system complexity through consolidation
Solution Approach 2:
The system implements a feedback loop where real-time road condition data is continuously obtained, drivability impact is assessed, and driving modes are adapted accordingly. This closed-loop control optimizes vehicle efficiency by responding to actual conditions while managing complexity through systematic feedback processing
Data Source
AI summary
A computer system controls one or more vehicles operating in a confined geographical area. The computer system has processing circuitry to receive travel mission data for at least one vehicle of a plurality of vehicles within the confined geographical area, the travel mission data comprising at least data about an intended route for completing a transport mission; obtain real-time road condition data for the intended route; based on the obtained real-time road condition data, determine a drivability impact for the at least one vehicle intended to perform the travel mission along the intended route, the drivability impact being indicative of an estimated decrease in any one of a vehicle traction control level and an energy efficiency level; in response to the determined drivability impact, adapt any one of a driving mode and load capacity for the travel mission for the at least one vehicle; and control the at least one vehicle based on any one of the adapted driving mode and adapted load capacity for the travel mission.