Cloud Delivery Routing With Energy-Based Driver Remuneration
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Solution Overview
Problem
Existing package delivery systems face challenges in route optimization, leading to higher operational costs, environmental impact, and inadequate integration of driver well-being and incentive structures, affecting driver performance and overall service effectiveness.
Innovation Solution
A cloud-based system that utilizes a network of vehicles equipped with Telematics Control Units (TCUs) for dynamic routing, considering package and vehicle characteristics, and provides remuneration based on energy consumption to incentivize efficient driving.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional route optimization is used, then delivery operations can be maintained, but operational costs increase and environmental impact worsens
Solution Approach 1:
The system dynamically determines delivery routes based on real-time vehicle information (fuel efficiency, location, speed) and package characteristics, rather than using static pre-planned routes. This allows continuous optimization of fuel consumption while maintaining delivery efficiency through adaptive route adjustment.
Solution Approach 2:
The system collects feedback from vehicles regarding fuel efficiency, location, and speed, then uses this information to optimize route determination. The remuneration system also provides feedback by incentivizing fuel-efficient driving behaviors, creating a closed-loop system that continuously improves fuel consumption without sacrificing productivity.
2Productivity
If driver incentive structures are not integrated, then system complexity is reduced, but driver performance and service effectiveness deteriorate
Solution Approach 1:
The existing route optimization system is extended to serve multiple functions: it not only determines optimal routes for delivery efficiency but also calculates fuel consumption for remuneration purposes and tracks driver performance. This multi-functionality integrates driver incentives without requiring a completely separate system, thereby managing complexity while improving productivity.
Solution Approach 2:
The system automatically determines remuneration based on collected vehicle and route data, eliminating the need for manual intervention in incentive distribution. This automated self-service approach integrates driver performance tracking and incentive management into the existing operational framework, improving driver performance without proportionally increasing system complexity.
3Use of energy by moving object
If dynamic routing based on vehicle information is implemented, then fuel efficiency improves, but system complexity increases
Solution Approach 1:
The routing system is designed to simultaneously optimize for multiple objectives: delivery efficiency, fuel consumption minimization, and driver remuneration calculation. By integrating these functions into a single system rather than separate systems, the patent manages complexity while achieving improved vehicle fuel efficiency through dynamic route adjustment based on real-time vehicle information.
Data Source
AI summary
A first electronic device and a method for cloud-based package delivery and vehicle energy consumption based rider remuneration are provided. The first electronic device comprises a circuitry. The circuitry receives first information indicative of first delivery request of first package from a source location to a target location. The circuitry selects one or more vehicles from a set of vehicles, based on vehicle information of each vehicle, and further based on a first package profile. The circuitry determines one or more delivery routes for the first delivery request, based on driver information and the first information. The circuitry transmits the one or more delivery routes to one or more second electronic devices. The circuitry receives energy consumption information for each vehicle, based on the one or more delivery routes. The circuitry determines remuneration information for the driver, based on the energy consumption information.