Shuttle Route Priming for Targeted Drop-Off Advertising
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Solution Overview
Problem
Existing advertising methods for mobile hailing shuttle services lack effectiveness in influencing passenger behavior through targeted route planning and environmental priming to promote local businesses near drop-off locations.
Innovation Solution
A system that uses a controller to select routes based on priming estimates indicating the similarity of points of interest to contracted businesses, combined with environmental atmosphere control, to influence passenger purchasing decisions by creating themed routes and promoting contracted businesses effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the shuttle takes the most direct route to the drop-off location, then travel time is minimized, but advertising effectiveness is reduced
Solution Approach 1:
The system pre-calculates priming estimates for multiple potential routes before the shuttle journey begins. By evaluating points of interest along each route and comparing them to the contracted business characteristics in advance, the system prepares route recommendations that optimize advertising effectiveness before the trip starts, allowing the shuttle to deviate from the most direct route when advertising goals are prioritized.
Solution Approach 2:
The system dynamically changes the routing parameter selection based on the priming estimate values. Instead of always selecting the route with the shortest travel time, the controller adjusts the routing decision by incorporating priming estimates as a variable parameter, selecting routes that pass near points of interest with higher similarity to the contracted business, thus transforming the routing optimization from purely time-based to a composite metric of time and advertising effectiveness.
2Reliability
If the shuttle deviates from the direct route to pass near points of interest, then advertising effectiveness is improved, but travel time increases
Solution Approach 1:
The system applies partial deviation from the direct route by selecting points of interest that are partially aligned with the contracted business characteristics. Rather than requiring complete route deviation to achieve advertising goals, the system identifies points of interest with sufficient priming estimates that provide adequate advertising exposure while minimizing the additional travel time required, thus applying a partial action principle.
Solution Approach 2:
The system uses feedback from passenger preferences and historical data to continuously refine priming estimate calculations. By incorporating passenger feedback about their interests and preferences, the system adjusts which points of interest are selected along the route, optimizing the balance between advertising effectiveness and travel time based on actual passenger responses rather than static assumptions.
3Reliability
If multiple points of interest are included in the route, then advertising coverage is enhanced, but route complexity increases
Solution Approach 1:
The system applies local quality by selecting specific points of interest along the route that have high priming estimates for the contracted business, rather than uniformly including all points of interest. Each point of interest is evaluated individually based on its characteristics and similarity to the contracted business, allowing the route to include only those locations that provide meaningful advertising value, thus enhancing coverage while avoiding unnecessary complexity.
Solution Approach 2:
The system uses copying by creating a simplified representation of the optimal route based on priming estimate calculations. Instead of manually planning complex routes with multiple points of interest, the system generates a copied or replicated route plan that automatically incorporates the necessary deviations and stops based on calculated priming values, reducing the complexity of route planning while maintaining comprehensive advertising coverage.
Data Source
AI summary
An advertising method for a shuttle comprises by a controller, responsive to identifying a drop-off location and a business paying to influence a route travelled by the shuttle, selecting one of a plurality of routes to the drop-off location according to a priming estimate indicating that points of interest along the one share more characteristics with the business relative to others of the plurality; and commanding the shuttle to travel the one.