Event-Based Traffic Routing Avoidance Zones
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Solution Overview
Problem
Current route planning systems struggle to accurately forecast and mitigate traffic congestion caused by local events such as concerts, sporting events, and conferences, as they do not adequately consider the impact of these events on road segments, leading to delayed travel times and inefficient routes.
Innovation Solution
A system and method that forecast traffic congestion on road segments due to events by using a model incorporating event type, attendance information, weather, and other factors to identify congested areas, generating an avoidance zone, and providing this information to route planners to suggest alternative routes and update travel times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If route planners use traditional forecasting methods to estimate travel times, then the routing system operates with simple models, but the accuracy of traffic congestion forecasting deteriorates due to the fluid nature of traffic and unaccounted local events
Solution Approach 1:
The system segments the forecasting model into multiple specialized components: an event detection module that identifies local events, an event impact assessment module that evaluates potential traffic effects, and a route planning module that integrates these insights. This segmentation allows each component to specialize in specific tasks, improving overall forecasting accuracy without overwhelming system complexity
Solution Approach 2:
The system performs preliminary actions by proactively detecting local events and assessing their potential traffic impacts before routing decisions are made. The event detection and impact assessment occur in advance, allowing the route planner to pre-calculate alternative routes that avoid anticipated congestion zones, thereby improving forecasting accuracy through early intervention
2Measurement precision
If the system incorporates comprehensive event data and complex modeling to accurately forecast congestion, then forecasting accuracy improves, but the computational time and processing resources increase
Solution Approach 1:
The system applies partial action by focusing computational resources on assessing only the most significant event impacts rather than analyzing every possible variable. The event impact assessment module prioritizes events with higher predicted congestion effects, performing detailed analysis only where necessary. This selective approach maintains high prediction accuracy for critical congestion scenarios while reducing overall computational time and resource consumption
3Productivity
If the system generates detailed avoidance zones based on event impacts, then route efficiency improves by avoiding congestion, but the complexity of route planning increases
Solution Approach 1:
The system performs preliminary action by pre-generating avoidance zones based on detected events and their predicted impacts before the user requests a route. These avoidance zones are prepared in advance and stored as spatial constraints. When a user requests routing, the planner simply integrates these pre-computed zones into the routing algorithm, improving route efficiency by avoiding congestion while minimizing the complexity added to the real-time planning process
Data Source
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AI summary
One or more techniques and/or systems are provided for to creating an avoidance zone spatially proximate a venue, where the avoidance zone is created based upon identifying road segments where increased traffic congestion is expected due to an event at the venue. Information pertaining to the avoidance zone, such as a description of road segments to avoid and/or expected travel delays, may be provided to a route planner configured to develop vehicle routes. In this way, the route planner can take into consideration the impact of events on one or more road segments when planning a route.