Predictive Drawbridge System for Route Rerouting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Cities with drawbridges face traffic congestion and unpredictable delays due to unpredictable drawbridge opening times, as existing systems lack a reliable prediction model for drawbridge operations based on incoming vessel information, leading to inefficient route planning and rerouting.
Innovation Solution
A smart drawbridge system that uses a combination of cameras, marine radio monitoring, and historical data to predict drawbridge opening times, durations, and uncertainties, communicating this information to vehicles for route planning and rerouting through a GPS system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a schedule exists for planned drawbridge opening/closing times, then route planning can be performed, but the actual operation deviates from the schedule causing unpredictable delays
Solution Approach 1:
The system continuously monitors incoming vessel information through cameras and marine radio, comparing actual drawbridge operations with scheduled operations. This feedback loop enables the machine learning model to learn from deviations and improve prediction accuracy, making the system adaptive to real-world variations in drawbridge behavior
Solution Approach 2:
The system performs preliminary prediction of drawbridge opening times and durations before vehicles reach the drawbridge. By using historical data and real-time vessel information to forecast operations in advance, the system enables proactive route planning and rerouting decisions, preventing vehicles from encountering unexpected delays
2Loss of information
If warning signs with lights are used to notify drivers of drawbridge openings, then drivers receive alerts, but drivers cannot reroute in time and the signs may be missed
Solution Approach 1:
The system provides advance notification to drivers about predicted drawbridge openings before they reach the warning sign location. By calculating predicted opening times and comparing them with current time and vehicle position, the system can alert drivers with sufficient lead time for alternative routing decisions
Solution Approach 2:
The system acts as an intermediary between drawbridge control systems and vehicle navigation systems. It receives drawbridge operation data, processes it through prediction models, and delivers actionable information to GPS systems, enabling integrated route planning that accounts for drawbridge operations
3Loss of information
If real-time drawbridge opening data is provided, then vehicles can be notified of openings, but the data does not enable predictive route planning
Solution Approach 1:
The system performs preliminary prediction of drawbridge opening times and durations using historical data and real-time vessel information. This predictive capability enables navigation systems to plan routes in advance, avoiding areas with predicted delays rather than merely reacting to current conditions
Solution Approach 2:
The system replaces simple real-time data display with an intelligent prediction model that processes multiple data sources (historical operations, incoming vessel information, scheduled operations) to forecast future drawbridge behavior. This substitution transforms raw data into actionable predictive information
Data Source
AI summary
Systems and methods are provided for predicting drawbridge operation based on incoming vessel information and historical drawbridge operation data, and transmitting the drawbridge operation prediction to a GPS system such as an autonomous vehicle or a mobile device application for rerouting a planned navigation route. A transceiver may receive vessel information, e.g., incoming vessel size, type, speed, position, or quantity, or estimated incoming vessel arrival time, from one or more cameras and/or a marine radio, and may receive historical drawbridge operation data based on the incoming vessel information from an online database such that the drawbridge operation prediction is based on the historical data.