Energy-Based Vehicle Route Selection System
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Solution Overview
Problem
Current vehicle route selection methods primarily focus on minimizing distance or time, neglecting energy consumption, which is a significant concern for transportation companies due to rising fuel costs and environmental impact.
Innovation Solution
A system and method that optimize vehicle routes by considering energy usage factors such as terrain, vehicle characteristics, driver behavior, road conditions, traffic, and weather, using a routing module that calculates and prioritizes routes based on energy use costs, and provides real-time feedback to drivers to reduce energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If vehicle routes are selected based on shortest distance or time, then travel efficiency is improved, but energy consumption increases
Solution Approach 1:
The patent changes the optimization parameter from distance or time to energy consumption. The routing module calculates energy costs for multiple candidate routes by integrating factors such as elevation changes, horizontal curvature, vertical curvature, lane gradients, and traffic conditions, then selects the route with minimum energy cost rather than shortest distance or time.
Solution Approach 2:
The patent transitions from two-dimensional route planning (flat map coordinates) to three-dimensional route planning by incorporating elevation data, vertical curves, and lane gradients. This additional dimensional information enables more accurate energy consumption calculations and better route optimization.
2Measurement precision
If multiple route factors are considered for optimization, then route selection accuracy improves, but system complexity increases
Solution Approach 1:
The patent segments the route optimization problem into distinct components: candidate route generation, energy cost calculation for each route segment, and final route selection. The energy cost calculation is further segmented into separate factors (elevation, curvature, gradients, traffic) that can be independently computed and then integrated.
Solution Approach 2:
The routing module serves multiple functions: it generates candidate routes based on geographic data, calculates energy costs by integrating multiple factors (elevation, curvature, traffic, weather), and selects the optimal route. This multi-functional approach consolidates complexity into a single unified system rather than requiring separate systems for each function.
3Measurement precision
If real-time data processing is implemented for route optimization, then energy optimization accuracy improves, but computational requirements increase
Solution Approach 1:
The system performs preliminary calculations by pre-processing geographic data, elevation models, and road network information to generate candidate routes and pre-calculate energy cost factors. This allows real-time route selection to rely on pre-computed data rather than performing full calculations from scratch, reducing computational requirements during actual route determination.
Solution Approach 2:
The routing module autonomously processes route optimization without requiring external intervention. It automatically integrates multiple data sources (geographic information, elevation data, traffic conditions, weather forecasts) and performs the complete energy-based optimization process independently, eliminating the need for complex external computing infrastructure.
Data Source
AI summary
Vehicle management systems and associated processes can consider energy consumption when selecting routes for fleet vehicles. Vehicle management systems and associated processes are described that, in certain embodiments, evaluate vehicle energy usage based on factors such as terrain or elevation, vehicle characteristics, driver characteristics, road conditions, traffic, speed limits, stop time, turn information, traffic information, and weather information, and the like. The features described herein may also be implemented for non-fleet vehicles, such as in personal vehicle navigation systems.