The connected vehicle (CV) initiative by the United States Department of Transportation (USDOT) is designed to increase the safety, mobility, and the environment of the traveling public. Consequently, Michigan Department of Transportation (MDOT) has begun programs focused on collecting vehicle status and conditions data related to the roadways. Michigan is home to one of the largest CV programs in the United States - Safety Pilot Model Deployment. MDOT has begun investigating ways to utilize this data to manage agency performance, and transportation system operations. The Data Use Analysis and Processing (DUAP) program is an MDOT initiative that investigates how this data, and other mobile and fixed data, can be used to increase the efficiency in the way the agency manages and operates itself. The DUAP program will develop a system that integrates data from CV, mobile, and fixed data sources, and analyzes the data to determine traffic, weather, and asset conditions. 

Key Words: connected vehicles, CV, mobile data, MDOT, DUAP, back office, organizational structure, intelligent transportation systems, ITS

The United States Department of Transportation’s (USDOT) connected vehicle (CV) program is a large-scale initiative aimed at improving the safety, mobility, and environment of the transportation infrastructure for the traveling public. As stated on USDOT’s website, the CV program is described as follows: “As we look ahead to the next stage of roadway safety in America, connected vehicle technology shows great promise in transforming the way Americans travel. Through wireless technology, connected vehicles ranging from cars to trucks and buses to trains could one day be able to communicate important safety and mobility information to one another that helps save lives, prevent injuries, ease traffic congestion, and improve the environment.” (1).  MDOT has initiated efforts to determine how they can utilize this CV data, mobile data, and data from fixed sources in order to better manage and operate its transportation infrastructure. The DUAP program is one of these initiatives.

DUAP PROJECT SUMMARY

The MDOT DUAP program provides a platform and system that supports performance management by enhancing agency-wide usage of CV data, mobile data, and fixed data to increase data sharing, availability, and awareness across the agency. By accomplishing this objective, MDOT decision makers will be equipped with more robust, near-time data from CVs, mobile platforms, and other internal MDOT systems. Receiving this information on a timelier basis will allow for decision making in support of agency objectives at reduced costs and with increased operational efficiency. Towards this objective, the cornerstone of the DUAP program is to integrate CV data, mobile data, and fixed data into a unified system of systems that is accessible by personnel across MDOT. This will provide MDOT system users with a platform to iteratively define, analyze, and refine their need for making decisions.

This iterative process enables them to create automated processes dedicated to streamlining some job functions that allow the users to spend more time meeting their goals. Additionally, the platform and its iterative processes will help identify overlapping needs between functional areas, which will reveal opportunities to refine data needs, and coordinate joint efforts. This provides insight into the “big picture” of how the agency operates, resulting in improvements to data that is collected and used, operational processes within the agency, and reduced agency costs and expenditures. Furthermore, this results in increased data awareness and socialization across the agency, and increases the value of each data collection effort.

ORGANIZATIONAL STRUCTURE

Through an organizational structure viewpoint, MDOT is taking a holistic view of itself, independent functional areas, operations, and assets. An organizational functional analysis has been, and will continue to be, conducted across the entire agency. This analysis covers business units that perform the core business processes within MDOT. Analyzing each business unit includes activities such as obtaining and reading documentation as it becomes available, conducting interviews and workshops with MDOT personnel, and reaching out to the appropriate personnel to obtain information related to MDOT systems of interest.

The outcome of the organizational functional analysis has identified five major functional areas, including planning/asset management, design, construction, maintenance, and operations.  Viewing MDOT as a collection of functional areas enables further analysis of individual assets and the asset life cycle.

From the initial planning and design phases through construction, maintenance, and operations, the entire agency plays a critical role in maximizing the value of the agency’s assets. Each functional area across the agency provides very specific functions at various times throughout the asset life cycle. As each function is executed, data related to the specific functional area is collected by various systems, and is used for accomplishing the related activities. Within each activity, several functional areas will be involved simultaneously, providing separate, but interrelated services and activities.

Often, the data that is collected at these times is used only for a very specific purpose within a single functional area and not easily shared with the other functional areas. While this data may be useful to other functional areas for executing their activities, more often it is stored within the originating functional area, becoming inaccessible despite the overlapping agency functions, thereby becoming “siloed.” This results in unused data, limited data sharing among functional areas, repeated data collection efforts, and increased costs.

Because of this “siloed” result, data sharing efforts proved to be more challenging than anticipated. To combat this major organizational issue, an intelligence gathering process and methodology has been developed for collaborating with the functional areas. This provides a unique perspective of how each functional area views itself, the activities they perform, the information they use, and other functional areas with whom they interact. This also reveals data socialization opportunities by identifying related activities and data used by many other functional areas. The DUAP project is focused on capitalizing on these opportunities by providing the platform to enable development and refinement of the business analytics that allow data socialization to occur and provide useful information across MDOT.

DUAP SYSTEM

The DUAP system itself is a large-scale data collection system designed to ingest data from multiple data sources to be processed, stored and made accessible to users of the system. It is also designed to be flexible, scalable, and maintainable, while providing the following capabilities:

• Operate as a collection point for large amounts of data from many sources

• Allow new data sources to be integrated as they become available

• Sustain existing data sources that are still viable

• Minimize costs by creating processes that are configurable

• Act as a collection of processing methods for:

  • Parsing data from its original format

  • Transforming data into more useful formats

  • Storing data in a database

  • Securing data

  • Ensuring data integrity

• Provide the means for accessing data from the database

• Provide a collection of web services that process the stored data to provide information

• Provide a collection of developed applications that share and disseminate information to the users of the system

• Act as a data source for other MDOT systems and applications

Due to the size and complexity of the project, the physical DUAP system consists of three major components: data collection/ingestion, data management, and consumption. Below, figures 1, 2, and 3 illustrate the components of the overall DUAP system architecture.

The data collection/ingestion component is responsible for detecting data that has been collected by an external intelligent transportation system (ITS) and submitted to the DUAP system. It is designed with special methods and processing routines that are capable of analyzing the data and storing it in the appropriate databases. It also houses the first round of data quality checks to ensure the data is of the correct type, is in a valid format and is within a logical and predetermined range.

Figure 1 – Data Collection/Ingestion

Once the data has been stored in the initial databases, the data management component performs additional verification, validation and quality checking routines, and integration processes. The data management component is responsible for storing the data so that it can be accessed and used by the consumption component.

Figure 2 – Data Management

Figure 3 – Data Consumption

DATA SOURCES

MDOT currently maintains and operates hundreds of information systems, which collect and provide an abundance of CV, mobile and fixed data. A critical part of the organizational functional analysis focused on identifying existing MDOT systems that could be used as data sources for the DUAP system. As the functional areas were evaluated, the systems used to collect and store data were, and continue to be, evaluated against user and data needs, while being mindful of the influence they can have on the applications that are selected for development. Additionally, existing CV and other mobile data sources are continually evaluated for integration into the DUAP system. These sources will be explored to determine the types of data they provide and how they can be used to support, augment, or replace existing data systems. A few of the data sources that are currently being ingested (or are in the ingestion development phase) into DUAP are described below:

• MDOT Road Weather Information System (RWIS) - MDOT has a sizeable Environmental Sensor Stations (ESS) network in place to monitor atmospheric and road surface conditions. DUAP is ingesting information such as surface and air temperatures, wind speeds, relative humidity, and precipitation rates. Depending on specific locations, other data is available such as traffic conditions, camera images of current conditions, etc.

• Weather Responsive Traveler Information System (Wx-TINFO) – An MDOT project team (supported by the Federal Highway Administration - FHWA), is currently developing a system to bring together near-time environmental/weather data from both mobile and fixed data sources. Data from this source include items such as radar images, RWIS station readings, Integrated Mobile Observations (IMO), National Weather Service (NWS) warnings, watches and advisories, and weather event conditions and locations.

• Integrated Mobile Operations (IMO) – IMO is another MDOT initiative (supported by the FHWA) to gather road condition data from snowplows and light- and medium-duty vehicles. The vehicles are equipped with smartphone technology and monitoring sensors to collect data such as accelerometer readings, vehicle location, vehicle speeds, antilock braking system (ABS), electronic stability control (ESC), and traction control system (TCS) events, and weather-related information.

• The Safety Pilot Model Deployment project is a joint effort between the United States Department of Transportation (USDOT), the University of Michigan Transportation Research Institute (UMTRI), and other public and private entities. The data being collected is providing the opportunity to understand the potential benefits in the areas of safety, mobility and environment. Data examples from this source includes basic safety messages (BSM), traveler information messages (TIM), signal phase and timing (SPaT) messages, and anonymous vehicle paths information.

• Microwave Vehicle Detection System (MVDS) – These MDOT sensors collect data on traffic counts, occupancy/lane information, and vehicle speed.

• MDOT Automated Vehicle Locator/Global Positioning System (AVL/GPS) Program – Snowplows and light/medium/heavy duty trucks are equipped with sensors to provide data on vehicle location (GPS), speed, blade position, and spreader information such as material type, rate and amount used. Sensors also record weather data such as humidity, and air and surface temperature.

• Transportation Management System (TMS) is MDOT’s version of the Highway Performance Monitoring System (HPMS) – HPMS is the national program that includes condition, performance, use, and operating characteristics of the nation's highways.

• Advanced Traffic Management System (ATMS) – This system provides traffic data, messages for the dynamic message signs (DMS), incident information, etc.

• Vehicle-Based Information and Data Acquisition System (VIDAS) – this MDOT initiative involves creating a flexible, scalable and maintainable mobile data acquisition platform. The vehicles in the program are equipped with a base set of sensors such as GPS locators, accelerometers, etc. The system’s flexibility enables the agency to determine the need for data and the appropriate sensors to be developed and deployed.

   

The following images show some of the numerous MDOT CV data sources and systems that potentially contain valuable data available for integration into the DUAP system. They are both prospective providers to and consumers of DUAP and its associated applications. Figure 4 is a sampling of systems and sources with interactive paths that currently exist, and figure 5 illustrates additional potential interactive paths.

Figure 4 – MDOT Systems and Data Sources with Current Interactive Paths

Figure 5 – MDOT Systems and Data Sources with Existing & Potential Interactive Paths

CV technology enables MDOT to equip existing MDOT fleets with CV data collection sensors that can communicate with the DUAP system. They can utilize existing infrastructure to transmit the data to the back office, where it is processed, quality checked, and analyzed. This provides information related to the current state of the transportation system. The intent is to provide a platform for the MDOT users to iteratively access this data, analyze it, and refine it to satisfy their needs.

DATA USES

Once the data from the various data sources is transmitted to the central DUAP system, intelligent business analytics can be applied to analyze it for providing information about current conditions (e.g., pavement or other assets, traffic, weather, etc.). Time constraints associated with the data will dictate which types of business analytics are applied. The time considerations include the time of collection, the time of upload, and the time of consumption by each user. The time of collection usually occurs in near-time. The time to upload considers when the data will be uploaded to the DUAP back office system. The time to consumption considers when the MDOT personnel will access the data from the DUAP system. This may occur at varying times depending on the functional area, and the job functions requiring the data. In some cases, such as traffic and weather updates for operations and maintenance, the time to collection, upload, and consumption must all be executed in near-time. In other cases, such as long-term transportation infrastructure planning, historical trend analysis based on snapshots of traffic, weather, and asset condition will be used to generate the plans. In this case, the collection may be in the near-time, the upload may be as needed, and the consumption is as needed.

The method of presentation of the information will vary by application, and the business analytics that are used/requested by the system users. Typical methods include text message and email alerts, daily/weekly/monthly/yearly reports, map displays, historical trends and charts, etc. The operations and maintenance functional areas will typically require more near-time data, while the other functional areas may subscribe to data over a longer timeframe, and in a different format. This will follow an iterative process that draws on feedback from the system users to refine the data they need, the information they will use, the necessary business analytics, and the method of consumption they desire.

Since the DUAP system design is multi-faceted, it acts as a data collection point, quality checking mechanism, data analysis tool, and a provider of data. All of these functions, among others, provide a rich foundation from which to build applications that meet the needs of MDOT personnel. The stakeholder meetings and workshops conducted throughout the functional areas, provided important information about user needs and requirements.

The user needs and requirements were recorded, shared among other functional areas, and prioritized for application development. Applications must satisfy the following requirements:

• Support MDOT’s performance management and data sharing efforts

• Provide benefit to a broad set of functional areas within MDOT

• Be available for use by MDOT within project time constraints

• Be expandable and scalable to include capabilities that are not yet defined

   

  The applications developed as part of DUAP are envisioned to consist of web, desktop/laptop and mobile applications.  From the rich set of data available, applications can be built with the ability to perform these, and many other activities:

   

• Track pavement conditions and degradation (both in near-time on a map, and historically through reports)

• Use mobile devices as a data collection tool to record and upload asset conditions in the field (utilizing form submission and image capture)

• View weather conditions affecting winter maintenance or traveling activities

• View reports of conditions (weather, traffic counts, etc.) that may have affected pavement lifecycle in a certain location

• View and/or receive maintenance work orders

THE FUTURE OF DUAP

Currently, the DUAP project is collecting and analyzing data from many sources. As the project continues, other existing, as well as newly created data sources can be integrated into the DUAP system. As technology advances, new opportunities for CV and other mobile data collection will be created, thereby generating additional data available for integration. The flexible and scalable design of DUAP will allow these data sources to be added without negatively affecting the operation of the system.

Continued data sharing among the agency’s functional areas will provide a rich source of information that will continue to grow in volume and value. By continuing to involve agency personnel to identify and discuss evolving requirements, applications can be created which will assist users to perform their job functions more effectively. Ongoing communication ensures that the concept of data sharing will continue.

At present, the DUAP project is in the application refinement phase. The system will be continuously refined and enhanced until ITS World Congress 2014, in Detroit. The project itself continues through 2015. The first iteration of the system will address a working pavement application, traffic application, and weather application.

REFERENCES

1. ITS JPO, “http://www.its.dot.gov/connected_vehicle/connected_vehicle.htm,” USDOT RITA, January, 2014, p. 1