How to Automate Real World Vehicle Route Generation Using Simulation  

Gamma Technologies’ Solutions for Creating Driving Routes with Simulation 

Ding! your package is eight stops away. Thanks to smartphones and the internet, you can view a live map and watch with excitement as the delivery vehicle arrives at your house. This is quite a transformation from a decade ago when all you’d receive was a tracking number and infrequent updates with nothing more than a location and expected delivery date. 

Example of a package delivery map

Gamma Technologies is looking to transform simulations of real driving routes by offering GT-RealDrive. Gone are the days of having to physically drive a vehicle and record its GPS data in order to re-create a driving route. Instead, this can now all be done virtually using GT-SUITE with GT-RealDrive and an internet connection.  

To get started, simulation engineers, using Gamma Technologies’ GT-SUITE, open GT-RealDrive and simply enter the “Start and End” locations just as you would on a navigation application. The user would then press the “Calculate Route” button and your route is ready to be simulated!  

GT-RealDrive takes care of the rest by generating an optimal route using the “Start and End” locations and estimating local traffic conditions. Users may apply this newly calculated route in an existing GT-SUITE vehicle model simulation. 

Also within GT-SUITE, to further automate and simulate numerous route conditions, users may use GT’s productivity tool, GT-Automation. With GT-Automation, simulaton engineers may instantly create GT-RealDrive route options with the use of Python scripting.  

In the example below, a delivery truck in Midtown Manhattan, New York City going through a last mile delivery route (dropping off packages at customer locations) is simulated. This simulation explores real world vehicle performance using GT-RealDrive and GT-Automation. 

STEP 1

First, we need to start with a list of the warehouse and then all the addresses (manifest) that a package needs to be delivered to (last mile delivery). This data can be in any format that is easily read by Python (e.g. csv, txt, xlsx, py, etc.).  

STEP 2

Next, write a short Python script that will read in these addresses and create a ProfileGPSRoute object for each leg (from one address to the next). The legs are then combined in a ProfilePGSRouteMulti object with stop times at each address to represent the driver stopping the vehicle and getting out to deliver the package. Writing such a script simply requires some basic knowledge of Python and referencing the GT-SUITE Python API documentation.  

STEP 3

Once the script is written, all that is left to do is run the script and sit back as GT-Automation & GT-RealDrive create all the route legs and assemble them all into a single, optimized route (shown below). The delivery route is then ready to be applied and used on any GT-SUITE vehicle model.

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How Simulation Can Be Used Beyond Last Mile Delivery

While we showcased an example using a last mile delivery route, similar challenges are faced with any route that has a lot of stops like buses, garbage trucks, ride shares, and so forth. The same process can easily be applied to any of these situations.  

If you are interested in learning more, please contact us.