Centralized Arrival-Time Index Calculation for Rental Fleet Management
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Solution Overview
Problem
Current technologies for assisting in the return of rental cars are costly due to the need for navigation devices and map data per vehicle, and high usage fees for external map services, leading to increased processing volume as the number of rental cars increases.
Innovation Solution
An arrival-time-index calculation system that sets representative points for a zone of destinations and calculates an estimated arrival time for multiple vehicles using a single route search, allowing for the determination of returning delay risks with reduced processing volume and costs by using an external map service less frequently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a navigation device and map data are installed in each rental car to calculate estimated arrival time, then the accuracy of arrival time calculation is improved, but the device complexity and cost increase with the number of rental cars
Solution Approach 1:
The patent extracts the route search and arrival time calculation function from individual navigation devices in each rental car and centralizes it in a server. The server collects current location data from rental cars and performs route search using map data, then returns estimated arrival times. This eliminates the need for each rental car to have its own navigation device while maintaining calculation accuracy.
Solution Approach 2:
The server performs multiple functions: it manages rental car locations, searches routes using map data, calculates estimated arrival times, and provides this service to multiple rental cars simultaneously. This universal server replaces the need for individual navigation devices in each rental car, reducing overall system complexity and cost.
2Measurement precision
If map data license fee is paid for each rental car to enable route search, then the route search accuracy is improved, but the cost increases with the number of rental cars
Solution Approach 1:
The patent merges the map data resource usage across all rental cars into a single centralized instance on the server. Instead of each rental car requiring its own map data license, the server holds one map data license and serves all rental cars. This consolidation significantly reduces the total map data license cost while maintaining route search accuracy for all vehicles.
3Measurement precision
If external map service is used to acquire required driving time for each rental car, then the arrival time calculation is improved, but the usage fee increases with the number of requests
Solution Approach 1:
The patent segments the rental cars into groups based on their current locations and destinations. Instead of performing individual route searches for each rental car, the system performs route searches for representative vehicles from each location group. The estimated arrival times from these representative searches are then applied to all vehicles in the same group, significantly reducing the number of external map service requests and associated costs.
Solution Approach 2:
The patent performs route searches only for a subset of rental cars (representative samples from each location group) rather than for all rental cars. This partial action is sufficient to provide accurate arrival time estimates for all vehicles in the system, as vehicles in the same location group have similar route characteristics. This approach reduces map service usage fees while maintaining adequate accuracy.
4Measurement precision
If route search and required driving time calculation is performed for each rental car, then the returning deadline determination accuracy is improved, but the processing volume increases with the number of rental cars
Solution Approach 1:
The patent segments rental cars into location-based groups and performs route search and driving time calculation only for representative vehicles from each segment. The results are then applied to all vehicles in the same segment. This segmentation approach maintains returning deadline determination accuracy for all vehicles while significantly reducing the total processing volume compared to individual processing.
Solution Approach 2:
The patent performs complete route search and driving time calculation for only a partial set of rental cars (representative samples). This partial processing is sufficient to determine returning deadlines for all rental cars in the system, as vehicles in the same location group have similar travel characteristics. This approach reduces processing volume while maintaining adequate accuracy for return deadline management.
Data Source
AI summary
An arrival-time-index calculation system includes a representative-point setting part configured to set a target-location representative point in a first zone and a mobile-body representative point in a second zone, and an index-value calculator configured to calculate an estimated arrival time to a destination of a traveling route as an index value of an arrival time of each of the plurality of mobile bodies, which are in the second zone and whose destinations are set in the first zone, to the destination. The first zone includes at least one destination, and the second zone is a zone in which a plurality of mobile bodies whose destinations are set in the first zone are located. The traveling route is searched by setting a current time as a departure time, setting the mobile-body representative point as a departure point, and setting the target-location representative point as the destination.