Autonomous Vehicle Speed Control for Driver-Preferred Traffic Response
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Solution Overview
Problem
Autonomous vehicles lack the ability to dynamically adjust speed based on driver preferences in various traffic scenarios, relying solely on predefined speed limits or adaptive cruise control systems that do not account for individual driving styles or specific traffic conditions.
Innovation Solution
An autonomous vehicle system that receives input from the driver for multiple speed preferences corresponding to different triggering situations, uses sensor data to identify relevant objects, and adjusts speed accordingly based on processor calculations to maintain preferred speeds in relation to surrounding traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the autonomous vehicle uses predefined speed limits or adaptive cruise control systems, then the basic speed control function is provided, but the system cannot dynamically adjust speed based on driver preferences in various traffic scenarios
Solution Approach 1:
The system dynamically adjusts the autonomous vehicle's speed by switching between multiple speed preferences (first, second, and third speed preferences) based on detected traffic conditions. The processor selects different speed profiles depending on whether traffic is heavy, moderate, or light, enabling the vehicle to adapt its speed control behavior to varying driving scenarios rather than using a fixed speed control mechanism.
Solution Approach 2:
The system changes the speed parameter by selecting from multiple predefined speed preferences corresponding to different traffic conditions. Each speed preference represents a different set of speed parameters (maximum speed, acceleration rate, following distance), and the processor dynamically switches between these parameter sets based on sensor input, allowing the vehicle to optimize its speed behavior for current traffic conditions.
2Adaptability or versatility
If the autonomous vehicle uses multiple speed preferences for different traffic scenarios, then the adaptability to traffic conditions is improved, but the system complexity increases
Solution Approach 1:
The speed control system is segmented into multiple discrete speed preferences (first, second, and third speed preferences), each optimized for specific traffic conditions. The processor evaluates traffic conditions and selects the appropriate segmented speed preference, breaking down the complex task of continuous speed optimization into manageable discrete choices based on traffic density and flow patterns.
Solution Approach 2:
The system implements feedback control by continuously monitoring traffic conditions through sensors and adjusting the selected speed preference accordingly. The processor receives feedback about current traffic state (heavy, moderate, or light traffic) and dynamically switches between speed preferences to maintain optimal speed behavior, creating a closed-loop control system that adapts to changing conditions.
3Reliability
If the autonomous vehicle continuously monitors traffic conditions and adjusts speed dynamically, then the safety and comfort are enhanced, but the computational requirements and system complexity increase
Solution Approach 1:
The system uses partial monitoring by focusing on key traffic condition parameters (traffic density, flow speed, distance to other vehicles) rather than comprehensively analyzing all possible environmental factors. The processor evaluates only the necessary conditions to determine which speed preference to apply, implementing sufficient rather than exhaustive monitoring to achieve safe and comfortable speed control.
Solution Approach 2:
The system prepares multiple speed preferences in advance, each pre-configured for specific traffic scenarios. Rather than calculating optimal speed in real-time from scratch, the processor selects from pre-computed speed preferences based on current conditions, reducing computational burden while maintaining safety and comfort through proactive preparation of speed strategies.
Data Source
AI summary
Aspects of the disclosure relate generally to speed control in an autonomous vehicle. For example, an autonomous vehicle may include a user interface which allows the driver to input speed preferences. These preferences may include the maximum speed above the speed limit the user would like the autonomous vehicle to drive when other vehicles are present and driving above or below certain speeds. The other vehicles may be in adjacent or the same lane the vehicle, and need not be in front of the vehicle.