The Route Optimizer Engine is designed to enhance route planning for logistics and transportation services. By integrating various critical parameters such as fuel capacity, driver hours, and real-time traffic data, this engine aims to optimize routes for efficiency and compliance with legal standards.
- Objective: Manage refueling needs based on vehicle fuel capacity and range.
- Implementation:
- Fuel Capacity Consideration: This parameter does not directly translate into a route parameter for the TomTom API. Instead, potential refueling points are calculated based on the truck's fuel capacity and range.
- Route Calculation: Determines when and where refueling should occur without significantly deviating from the optimal route.
- Objective: Ensure compliance with legal driving hours and provide for mandatory rest periods.
- Implementation:
- Hours of Service Compliance: Segments the route into multiple parts to ensure drivers operate within legal driving limits.
- Rest Period Planning: Plans rest stops based on continuous driving time and remaining hours in the driver's schedule, incorporating these into the route planning.
- Objective: Adjust routes dynamically in response to real-time data and predefined criteria.
- Implementation:
- Real-time Data Integration: Integrates real-time traffic and weather data feeds to adjust routes dynamically, enhancing route accuracy and timeliness.
- Continuous Re-routing: If conditions change (e.g., traffic jams, accidents), the engine recalculates the route in real-time to find the best alternative paths.
- Objective: Utilize a comprehensive database to support dynamic routing with updated real-world data.
- Implementation:
- Data Storage: Integrates with a database that stores up-to-date information on traffic patterns, weather conditions, and available rest areas.
- Data Utilization: Regularly accesses and updates this database to reflect current conditions in route planning.
- Objective: Manage routing parameters that are not directly supported by standard APIs.
- Implementation:
- Custom Logic Implementation: For parameters like axle weight or turn radius that are not directly manageable through the TomTom API, custom logic is implemented to filter and evaluate feasible routes.
- API Extension: Develop extensions or additional API layers to handle complex routing scenarios that involve multiple parameters.
- Objective: Allow for real-time route modifications based on changing conditions and inputs.
- Implementation:
- Driver Inputs: Incorporate feedback or commands from drivers to adjust routes according to real-time needs or preferences.
- Vehicle Status Monitoring: Monitor the status of the vehicle to adjust routes based on factors like unexpected vehicle performance issues or maintenance needs.
graph TD
A[OptimizerRoute]
B[findBestRoutes]
C{Construct URL}
D{Add Parameters}
E{Logic to avoid high-traffic areas}
F{Consider Fuel Stations}
G{Handle refrigeration needs}
H{Add axle weight logic}
I{Handle driver hours}
J{Avoid toll roads if no toll system}
K[Send request to TomTom API]
L[Handle response]
M[findStationsAlongRoute]
N[isStationAlongRoute]
O[calculateDetour]
A --> B
B --> C
B --> D
B --> E
B --> F
B --> G
B --> H
B --> I
B --> J
B --> K
B --> L
F --> M
M --> N
E --> O
classDiagram
class RouteOptimizer {
+OptimizerRoute(tomtom_api_key, from, to, driverHourThreshold, fuelCapacityThreshold, truck) RouteResponse
}
class RouteResponse {
+routes: List<Route>
+warnings: List<String>
}
class Truck {
+Dimensions: Dimensions
+Weight: int
+Hazmat: boolean
+RouteRestrictions: List<String>
+TrafficPatterns: Map<String, String>
+FuelCapacity: int
+FuelStations: List<FuelStation>
+Refrigeration: boolean
+AxleWeight: List<int>
+DriverHours: int
+RestAreas: List<String>
+TollSystem: String
}
class Dimensions {
+Height: int
+Width: int
+Length: int
}
class FuelStation {
+Location: String
+FuelType: String
+Price: float
}
RouteOptimizer --> RouteResponse
RouteOptimizer --> Truck
Truck --> Dimensions
Truck --> FuelStation