Connected Vehicles Accelerator

Introduction

The Connected Vehicles Accelerator contains components to allow tracking of vehicles and trips based on the GTFS format for transit vehicles. Although based on a transit data model it allows tracking of any kind of vehicle moving to a defined schedule. It includes components for visualization of real-time moving vehicles, rules to detect delays and classify occupancy, and integration components to link all of them together.

This video explains how the Accelerator works.

Download

The Connected Vehicles Accelerator can be downloaded from the Exchange.

Business Scenario

Traditionally, transportation companies relied on routes, schedules, work assignments and other isolated systems to model their business. Much of the data is historical, making it difficult or impossible to predict future state. Plus, with the data in silos there is no overall holistic view of what's going on across the entire network. Stale, batch-oriented feeds mean that the data is in the wrong place at the wrong time, degrading its value. Getting the data to the right people is also a challenge. Backwards-facing data means that exceptions are always surprises and handling them is always a reactive process often resulting in sub-optimal outcomes.
 

In the modern world of Internet of Things (IoT), vehicles have become mobile devices, leading to the Internet of Trains, Boats, or Airplanes. These new information sources provide an opportunity to increase the available operational intelligence, both quantity and quality. Of course the data volume increase can be both a benefit and a hindrance if you can't find the signal in the noise. But the clever use of smart event processing technology and predictive analytics allows you to cut through the clutter to find the events that matter. Now with forward-looking data, exceptions can be proactively handled with the best possible outcome, for the company, and its customers and partners, improving their experience. Plus it opens up new avenues to monetize the value of the data through real-time APIs that can be exposed and marketed to third parties.
 

Concepts

At the heart of the Connected Vehicles Accelerator is the Trip. This is a journey consisting of several stops operating on a schedule. There are three resources that a trip depends on: Vehicle, Crew, and Passengers/Cargo. Plus the Trip also has a dependency on the Processes that make them happen.



 

The Connected Vehicles Accelerator captures data from existing systems, and combines it with real-time feeds from these resources and processes. In addition, it can capture real-time feeds from third party data providers such as weather and traffic. Accelerator rules analyze this data and produce automated actions, advisories to operations staff, and alerts to outside parties. The current state of the network is displayed in true real-time on an operations dashboard, and near real-time using analytics tools.
 

By aggregating all this information in one place, the accelerator gives unique insight into network operations that just is not available in any other single system.
 

Benefits and Business Value

Connected Vehicles platform acts as a single source of truth for all trip and vehicle data. Using an in-memory model exposed using integration services the data is available to any system that needs it, reducing the need for data silos. As a real-time data repository, it is fed directly by data streams from vehicles and systems, so the information is guaranteed to be timely and accurate.
 

The business rules are primarily configuration-driven which allows decision table changes to be deployed in hours rather than weeks. This means a more agile system, able to adapt to business needs quicker and more effectively. By detecting anomalies and sending alerts, the accelerator acts as an efficient and fast first check on network health. It decides when something needs operations input and alerts them quickly and effectively. Using the real-time operation dashboard, operations staff has visual confirmation of network health at a glance, helping them quickly identify critical business moments.
 

Better operational intelligence with predictive capability means a single view of resources, all updated in real-time, with more timely and more accurate data. The net result is a more agile business, able to react on both the micro and macro scale more effectively.
 

The platform deployment is naturally scalable giving better data distribution and the ability to meet growth targets and beyond. The event-based architecture and in-memory network model support large scale deployments both on premise and in the cloud. Exposing this data using APIs empowers employees, customers, and partners.
 

Technical Scenario

Connected Vehicles is organized into contexts, with each representing a particular business or industry scenario. Within each context there will be several different test cases which can be run as demos to show various accelerator features. 
 

The accelerator has the following demo contexts:

• Distribution Logistics -- logistics company providing deliveries to stores in the Bay Area
• Railway -- passenger railway operating in the Netherlands called Virtual Train
• Secure Logistics -- logistics company providing secure delivery services in Madrid

In all cases a simulator is used in place of actual vehicles, publishing data directly into the accelerator environment. This includes information about vehicle speed, direction, distance, and position, as well as occupancy.
 

The accelerator is based around a Network Model which is an in-memory representation of static data. It is based on GTFS (General Transit Feed Specification) for trips and routing, and extended further with Extension data for scheduling, vehicles, and crews. This static reference data is used by the Event Manager to model the transportation network. It combines the static reference data with dynamic data feeds that arrive as Report events. This allows the Event Manager to track the existing state of the network.

Components