Vehicle Parameter Simulation for Multi-Vehicle Driver Training
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Solution Overview
Problem
The availability of drivers capable of operating various types of delivery vehicles is limited due to the time-consuming and expensive process of obtaining specialized training and certification, leading to a severe strain on delivery service providers, with a projected shortage of over 1 million new drivers by 2030.
Innovation Solution
A vehicle system that allows drivers to simulate and train for different types of vehicles without physically driving them, by modifying vehicle parameters and monitoring driving behavior to generate a performance report, using sensors, braking systems, and environmental adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If drivers undergo specialized training and certification for different vehicle types, then driving capability and safety are improved, but training time and cost increase significantly
Solution Approach 1:
The system creates a virtual copy of the training experience by using sensor data and environmental information to simulate driving different vehicle types. Drivers interact with a virtual representation of the training environment, allowing them to practice operating various vehicle types without physical training sessions, thus reducing training time while maintaining learning effectiveness
Solution Approach 2:
The patent replaces the mechanical physical training process with a digital simulation system. Instead of requiring drivers to physically sit in different vehicles and receive hands-on instruction, the system uses software-based virtual reality or augmented reality environments to substitute the physical training experience, significantly reducing the time and resources required
2Reliability
If drivers undergo specialized training and certification for different vehicle types, then driving capability and safety are improved, but training cost increases significantly
Solution Approach 1:
The system creates a virtual copy of the training experience by using sensor data and environmental information to simulate driving different vehicle types. Drivers interact with a virtual representation of the training environment, allowing them to practice operating various vehicle types without physical training sessions, thus reducing training time while maintaining learning effectiveness
Solution Approach 2:
The patent replaces the mechanical physical training process with a digital simulation system. Instead of requiring drivers to physically sit in different vehicles and receive hands-on instruction, the system uses software-based virtual reality or augmented reality environments to substitute the physical training experience, significantly reducing the time and resources required
3Quantity of substance
If more drivers are hired to replace retiring drivers, then workforce availability is improved, but the shortage problem worsens due to training time requirements
Solution Approach 1:
The system creates a virtual copy of the training experience by using sensor data and environmental information to simulate driving different vehicle types. Drivers interact with a virtual representation of the training environment, allowing them to practice operating various vehicle types without physical training sessions, thus reducing training time while maintaining learning effectiveness
Solution Approach 2:
The system enables preliminary virtual practice before actual driving duties begin. Drivers can complete virtual training modules and assessments beforehand, so that when they transition to actual vehicle operation, they are already prepared, reducing the overall time needed to bring new drivers up to speed
Data Source
AI summary
Systems and method for driver training are provided. Drivers can be trained to drive different types of vehicles using a single vehicle without having to actually get behind the wheel of the different types of vehicle. A first type of vehicle can be equipped with a training/simulation application that can modify certain vehicle parameters to mimic other types of vehicle. For instance, a small box truck can be made to operate like a semi-trailer by adjust certain parameters of the small box truck to cause it to drive like a semi-trailer. A driver can drive the box truck as if he were driving a semi-trailer and the vehicle will monitor the driver performance based on criteria for deriving a semi-trailer. Any driving infractions caused by the driver while he is driving the small box truck in the “semi-trailer” mode may be recorded and used for training and evaluation.


