Vehicle Energy Prediction Using Traffic Light Stop Patterns
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Solution Overview
Problem
Existing techniques for predicting the energy source consumption in vehicles, such as electric vehicles, are not accurate enough, necessitating more precise methods to assist drivers in managing their energy usage.
Innovation Solution
A processing device that includes processors and memories, which acquires traffic light operation patterns on a vehicle's route, predicts the number of stops, and calculates the total energy consumption based on these patterns to determine optimal travel routes and energy usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing prediction techniques are used, then the prediction process is simple, but the prediction accuracy of energy source consumption is insufficient
Solution Approach 1:
The system performs preliminary acquisition of traffic light operation pattern information before the vehicle journey begins. By obtaining the operational patterns (green light duration, red light duration, cycle periods) of traffic lights along the route in advance, the prediction model can calculate energy consumption based on predetermined traffic conditions rather than real-time observations, thereby improving accuracy without proportionally increasing complexity during the actual journey.
Solution Approach 2:
The prediction process is segmented into distinct components: acquiring traffic light pattern information, determining the number of stops based on these patterns, and calculating energy consumption based on the stop count. This segmentation allows each component to be optimized independently while maintaining overall system manageability and improving total prediction accuracy.
2Reliability
If the vehicle stops at traffic lights, then the vehicle follows traffic rules, but the energy source consumption increases
Solution Approach 1:
The system determines the number of stops at traffic lights in advance by analyzing the acquired traffic light operation patterns. By calculating the optimal stopping strategy before the journey begins, the system can provide accurate energy consumption predictions that account for necessary stops due to traffic rules, allowing drivers to plan energy usage while maintaining compliance with traffic regulations.
Data Source
AI summary
A processing device includes one or more processors and one or more memories coupled to the one or more processors. The one or more processors are configured to perform a process including: acquiring pattern information, which is information indicating an operation pattern of at least one traffic light that is present on a traveling route of a vehicle; predicting, based on the pattern information, a number of stops, which is a number of times the vehicle is to stop at the at least one traffic light; and predicting, based on the number of stops, a total consumption amount of an energy source of the vehicle in a case where the vehicle travels on the traveling route.