Dynamic Vehicle Scheduling for Anomaly Resolution
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Solution Overview
Problem
Existing transportation network scheduling systems fail to adapt to unforeseen events such as mechanical failures, route damage, and increased traffic, leading to inefficient fuel consumption and disrupted travel schedules.
Innovation Solution
A system comprising a scheduling module and a resolution module that determines initial schedules for vehicles in a transportation network and modifies them in real-time based on detected anomalies, such as mechanical failures or increased traffic, to optimize travel routes and arrival times, communicating these changes to energy management systems for implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If predetermined schedules are used to arrange vehicle travel, then vehicles can arrive at desired locations at scheduled times, but the system cannot adapt to unforeseen events such as mechanical failures or route damage
Solution Approach 1:
The scheduling system transitions from static predetermined schedules to dynamic schedules that are continuously updated based on real-time anomaly detection. When anomalies such as mechanical failures or route damage are detected, the system automatically modifies vehicle schedules and routing decisions, enabling the network to adapt while maintaining reliable service delivery.
Solution Approach 2:
The system implements a feedback mechanism where anomaly detection information flows back to the scheduling module. This feedback loop enables the system to detect anomalies in real-time and adjust schedules accordingly, resolving the contradiction between maintaining scheduled arrivals and adapting to unexpected events.
2Reliability
If vehicles abruptly slow down or stop to avoid collisions when congestion increases, then safety is maintained, but fuel consumption increases significantly
Solution Approach 1:
The scheduling system proactively adjusts vehicle schedules and routing before congestion leads to abrupt stopping. By detecting anomalies early and pre-modifying schedules to route vehicles around problematic areas or adjust timing, the system maintains safety while avoiding the fuel waste associated with sudden deceleration and idling.
Solution Approach 2:
The system dynamically optimizes vehicle speed and routing decisions based on real-time network conditions. Instead of abrupt stopping, vehicles receive continuously updated scheduling instructions that guide them through efficient paths, maintaining safety margins while minimizing fuel consumption through smooth, planned adjustments.
3Productivity
If real-time schedule modification is implemented to adapt to anomalies, then network efficiency improves, but system complexity increases
Solution Approach 1:
The scheduling system performs self-service by automatically detecting anomalies and generating modified schedules without requiring complex external intervention. The anomaly detection module feeds directly into the scheduling module, which autonomously recalculates and distributes updated schedules, maintaining high network throughput while managing complexity through automated self-regulation.
Solution Approach 2:
The system merges the anomaly detection function with the schedule modification function into an integrated scheduling module. This consolidation reduces overall system complexity by eliminating the need for separate complex coordination systems, while still achieving real-time adaptability and maintaining high network productivity through unified decision-making.
Data Source
AI summary
A system includes a scheduling module and a resolution module. The scheduling module determines plural initial schedules for plural different vehicles to concurrently travel in a transportation network. The initial schedules include locations and times for the vehicles to travel. The resolution module modifies at least one of the initial schedules to one or more modified schedules based on an anomaly in at least one of the vehicles or the routes that prevents one or more of the vehicles from traveling in the transportation network according to the initial schedules. The scheduling module communicates the modified schedules to the vehicles so that energy management systems disposed on the vehicles modify travel of the vehicles according to the modified schedules.