Page 832 - AI for Good Innovate for Impact
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AI for Good Innovate for Impact
Sub-Scenario 2: In-Journey Feedback for Driving Style
• Monitors real-time driving behavior (e.g., harsh acceleration or frequent braking).
• Recommends smoother driving patterns using reinforcement learning, which improves
range by 8–12%.
Sub-Scenario 3: Smart Journey Planning
• Suggests charging stops based on real-time SoC, terrain, and slot availability.
• Dynamically adjusts the plan if unexpected traffic or battery drain is detected.
Actions Taken (Driving Style Recommendations)
• The system continuously monitors driver input and battery output. Based on this, it
suggests:
Table I – Driving Style Suggestions�
Situation Suggested Action
High energy usage at an incline “Reduce speed to 45 km/h”
Frequent braking in city driving “Maintain more distance to avoid stops.”
Inefficient regen usage “Lift foot earlier before stop”
High temperature impact “Pre-cool vehicle while plugged in”
These are communicated via audio (if supported) and visual cues on the HUD.
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