V2V Reward Allocation for Drafting and Autonomous Droning
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Solution Overview
Problem
Current vehicle-to-vehicle communication systems lack effective methods to incentivize and reward beneficial driving behaviors such as drafting and autonomous droning, which can improve fuel efficiency and safety, while also affecting insurance policies and driver interactions.
Innovation Solution
A system that analyzes vehicle operational data to determine drafting and autonomous droning relationships, allocating rewards such as cash payments, carbon credits, or insurance policy adjustments based on identified characteristics, using vehicle-to-vehicle communication and data analysis algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If vehicle-to-vehicle communication systems are implemented to enable drafting and autonomous droning, then fuel efficiency is improved, but the system complexity and cost increase
Solution Approach 1:
The communication system is designed to perform multiple functions: enabling drafting coordination, autonomous droning operations, safety warnings, collision alerts, and data transmission for insurance purposes. By making the V2V communication system multi-functional, the patent reduces the need for separate dedicated systems for each function, thereby improving fuel efficiency through drafting and autonomous droning without proportionally increasing system complexity
Solution Approach 2:
The patent combines drafting coordination, autonomous droning control, safety communication, and insurance data collection into a unified V2V communication framework. This merging of functions allows the system to achieve multiple benefits (fuel savings, safety improvements, insurance optimizations) through a single integrated system rather than multiple separate systems, addressing the contradiction between fuel efficiency improvement and system complexity
2Use of energy by moving object
If drafting relationships are established between vehicles to improve fuel efficiency, then energy consumption is reduced, but safety risks may increase due to reduced vehicle spacing
Solution Approach 1:
The system continuously monitors vehicle spacing, speed, and operational parameters between vehicles in drafting relationships, and uses this feedback to dynamically adjust communication and control signals. This real-time feedback mechanism ensures that vehicles maintain safe distances while maximizing fuel efficiency benefits from drafting, and enables immediate response to any safety concerns that arise
Solution Approach 2:
The system establishes predetermined safety protocols, communication protocols, and control algorithms before vehicles engage in drafting relationships. By pre-configuring safety parameters, communication channels, and emergency procedures, the system ensures that safety measures are in place before vehicles reduce spacing to improve fuel efficiency, preventing safety issues before they can occur
3Use of energy by moving object
If autonomous droning is implemented where vehicles follow lead vehicles, then fuel efficiency and safety are improved, but the complexity of coordination and communication increases
Solution Approach 1:
The system uses standardized communication protocols and message formats as intermediaries between lead and following vehicles in autonomous droning operations. These communication intermediaries simplify the coordination complexity by providing predefined interaction patterns, reducing the need for complex direct coordination algorithms while enabling fuel efficiency improvements through autonomous droning
4Productivity
If vehicle operational data is collected and analyzed for reward allocation and insurance adjustments, then beneficial driving behaviors are incentivized, but data processing requirements and system complexity increase
Solution Approach 1:
The system extracts only the specific operational parameters needed for reward calculation and insurance adjustment (such as vehicle spacing, drafting duration, fuel consumption data) from the overall vehicle operational data stream. By extracting only the necessary data elements rather than processing all available data, the system effectively incentivizes beneficial driving behaviors while minimizing data processing complexity and requirements
Data Source
AI summary
System and methods are disclosed for determining, through vehicle-to-vehicle communication, whether vehicles are involved in autonomous droning. Vehicle driving data and other information may be used to calculate an autonomous droning reward amount. In addition, vehicle involved in a drafting relationship in addition to, or apart from, an autonomous droning relationship may be financially rewarded. Moreover, aspects of the disclosure related to determining ruminative rewards and/or aspects of vehicle insurance procurement/underwriting.