Context-Sensitive Route Planning for Dynamic Travel Time Estimation
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Solution Overview
Problem
Conventional route planning applications assume constant travel times regardless of time of day, day of week, and other contextual factors, failing to provide optimal routes that account for varying conditions such as rush hour or weather.
Innovation Solution
A system that uses a context-sensitive traffic system representation, including weighted graphs and probabilistic forecasting models, to estimate travel times based on time of day, day of week, and other contextual observations, allowing for real-time updates and optimization of routes to minimize travel time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional route planning applications use constant travel time assumptions, then the system complexity is reduced and ease of operation is improved, but the accuracy and reliability of route planning deteriorates
Solution Approach 1:
The patent applies dynamics by transforming the static travel time assumption into a dynamic model that adapts to varying contexts. The system now considers time of day, day of week, and other contextual factors to dynamically adjust travel time estimates, making the route planning system both more reliable and still easy to operate through automated context detection.
Solution Approach 2:
The patent changes the parameter of travel time from a constant value to a variable that depends on multiple contextual parameters. By incorporating time of day, day of week, and other contextual observations, the system accurately estimates travel times without requiring user input, thus maintaining ease of operation while improving reliability.
2Reliability
If route planning applications incorporate context-sensitive travel time estimation, then the accuracy and reliability of route planning is improved, but the device complexity and computational requirements increase
Solution Approach 1:
The patent applies preliminary action by pre-establishing the context-sensitive travel time estimation model and its parameters before actual route planning occurs. The system pre-defines how contextual factors affect travel times, so that during operation, it only needs to observe current context and apply the pre-established model, reducing real-time computational complexity while maintaining high reliability.
3Ease of operation
If conventional route planning applications provide static routes, then the ease of operation is maintained, but the adaptability to changing traffic conditions deteriorates
Solution Approach 1:
The patent applies feedback by continuously monitoring contextual changes (time of day, day of week, traffic conditions) and using this feedback to dynamically adjust route recommendations. The system provides static route structures but dynamically adapts them based on observed contextual changes, maintaining ease of operation while achieving high adaptability to changing conditions.
Data Source
AI summary
A route planning system comprises a receiver component that receives a request for directions between a beginning point and a destination point. An analysis component analyzes a traffic system representation that varies as context varies and outputs expected amounts of travel time between the beginning point and the destination point for multiple contexts based at least in part upon the analysis. A method is described herein that includes techniques for searching over routes and trip start times simultaneously so as to identity start times and routes associated with maximal expected value, or equivalently minimum expected cost, given preferences encoded about one or more of the leaving time, the travel time, and the arrival time.