V2I Infrastructure Placement via Digital Twin Simulation
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Solution Overview
Problem
Current V2I systems lack the ability to proactively predict and recommend the optimal placement of infrastructure devices on roadways to support vehicle driving decisions, relying solely on alerting drivers about traffic accidents without addressing infrastructure placement.
Innovation Solution
The system engages with an electronic map to receive real-time and historical data from IoT devices, identifies roadway characteristics and driving conditions, executes a digital twin simulation of vehicles driving on these roadways, and recommends the relative location of infrastructure devices based on vehicle capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If V2I systems only alert drivers about traffic accidents, then the system is simple to implement, but the system cannot proactively predict and recommend optimal placement of infrastructure devices
Solution Approach 1:
The system performs preliminary actions by using digital twin simulations to predict and recommend optimal infrastructure device placements before actual deployment. The simulation environment allows the system to test different scenarios and identify the most effective locations for infrastructure devices, enabling proactive planning rather than reactive responses.
Solution Approach 2:
The patent creates a digital twin (a virtual copy) of the roadway and vehicle systems to simulate and analyze driving conditions. This copying approach allows the system to evaluate infrastructure placement recommendations in a virtual environment without affecting real-world operations, thereby increasing adaptability while managing complexity through simulation rather than direct implementation.
2Reliability
If the system executes digital twin simulations for all vehicles, then driving decision support is improved, but computational resources and time are consumed
Solution Approach 1:
The system applies partial action by executing digital twin simulations selectively rather than for all vehicles simultaneously. The simulation focuses on specific scenarios, roadways, or vehicle types where infrastructure placement recommendations are most needed, thereby maintaining high reliability for critical decisions while reducing overall computational time and resource consumption.
3Productivity
If infrastructure devices are placed without simulation analysis, then deployment is fast and simple, but the placement may not optimize vehicle-to-infrastructure communication effectiveness
Solution Approach 1:
The system performs preliminary simulation analysis to determine optimal infrastructure device placements before actual deployment. By using digital twin simulations to evaluate different placement scenarios in advance, the system ensures that infrastructure devices are positioned to maximize vehicle-to-infrastructure communication effectiveness, avoiding the need for trial-and-error deployments.
Data Source
AI summary
An embodiment for engaging with an electronic map for an effective vehicle-to-infrastructure (V2I) network is provided. The embodiment may include receiving real-time and historical data from one or more IoT devices and an electronic map of one or more roadways. The embodiment may also include identifying one or more characteristics associated with the one or more roadways. The embodiment may further include identifying one or more driving conditions of each roadway in the electronic map and capabilities of one or more vehicles. The embodiment may also include executing a digital twin simulation of a digital twin model of each vehicle driving along the one or more roadways. The embodiment may further include in response to determining at least one vehicle is unable to make a driving decision, recommending a relative location of one or more infrastructure devices on the one or more roadways.