Mainstream network models for ITS have traditionally utilized switch/router Ethernet technologies to manage communications between the core and the edge. “Active Optical Networks (AON)”, as the naming indicates, deploy “active” network management devices within the system architecture to facilitate network management capabilities.
Recent years have seen technologies typically utilized by communications providers, proposed for use in support of next-gen ITS. One of those architectures utilizes multiplexing and “passive” fiber optic splitters to maximize the use of fiber optic infrastructure. Passive Optical Networks (PON), deploy the same amount of equipment, in addition to “passive” optical splitters in order to facilitate multiplexing of data at the head-end and distribution of data in the field.
The following provides a comparison of the advantages and disadvantages of “actively switched” and “passively split” fiber optic communications technologies.
ACTIVE OPTICAL NETWORK (AON)
AON’s utilize intelligent switching and routing to direct and manage data flow within a network. The emergence of the Ethernet architecture, protocols and topologies in the transportation and the Intelligent Transportation systems (ITS) arena occurred around 1999, and is rooted in traditional, switched Ethernet networks that date back over 35 years.
Advantages
Active Optical Networks have been successfully utilized for Transportation and ITS networks for more than 10 years, and currently represent the industry standard.
AON’s provide a framework and architecture that enables physical route redundancies, which provides protection against fiber cuts and enables optimized data management strategies.
Adding new devices to AON networks is simple “plug and play”, with little-to-no network reconfiguration required.
AON’s provide the ability to deploy equipment and protocols that are standardized within the telecommunications industry.
AON hardware is ubiquitous, with plenty of hardware vendors available, thus minimizing specific hardware/software/vendor dependencies.
An AON ring architecture allows for simplified network reconfiguration, implementation of additional “head-ends”, or the relocation of head-end by simply connecting to the nearest point on the nearest ring.
AON’s are fully bi-directional with equal upstream and downstream transmission rates.
Disadvantages
Edge switches cost more than PON cabinet devices Optical Network Terminals (ONTs).
Fully redundant core switch with optics cost more than the fully redundant PON’s OLT’s.
Requires the installation of additional conduit and cable runs to achieve physical redundancies.
PASSIVE OPTICAL NETWORK (PON)
PON’s are a relatively new technology that has emerged from the telecoms and cable industry, most notably as a result of the surging demand for consumer-driven, high-bandwidth applications for the residential market. Due to the required data payloads, including voice, video and data, the communications providers realized a need for maximizing the use of each and every single fiber deployed in their network. Gigabit PON or GPON is an asymmetrical, “shared” bandwidth configuration with a maximum downstream bandwidth of 2.4Gbps and an upstream total bandwidth of 1.2Gbps per fiber.
Advantages
Edge devices (cabinet transceivers or ONTs) are less expensive than typical Ethernet edge switches.
PON’s utilize multiplexing (mux) technologies that enable multiple channels (typically 32 or 64) to utilize a single fiber.
Due to the multiplexing architecture, the PON allows for the mux of 32 individual channels per single fiber, enabling communications to 32 different devices over the single mux’d fiber.
Disadvantages
Due to the Point-to-Point architecture of PONs, the technology is unable to feasibly implement physical network redundancies for communications routes.
If a splitter goes offline(splitter failure or cabinet hit), or a break in a cable occurs between the splitter and the head-end OLT (TMC), then all devices downstream from the break and the splitter will go offline until repairs can be rendered. Splitters represent a significant Single Point of Failure (SPOF) – which network design typically tries to minimize.
Due to the multiplexing nature of the data transmission, faults are difficult to identify/isolate/remedy.
The nature of PONs requires that fiber be installed in a manner that does not provide as much flexibility for future network configurations. All fiber backbone radiates from a single point,
The PON architecture does not allow for the implementation of typical Ethernet network management features/protocols associated with layer 3 (OSI) networking protocols.
Passive Optical LAN architecture is not recognized by any of the North American or international standards bodies as being a standards-based architecture for the enterprise environment.
PON’s asymmetrical framework (designed for delivering video/voice to the home) results in an architecture that provides more downstream bandwidth (2.4Gbps) than upstream bandwidth (1.2Gbps) – generally opposite of the needs related to a typical ITS installation, and thus an inefficient use of the technology. The potential downstream bandwidth (2.4 Gbps) will probably never be realized, nor required, where the upstream limitation of 1.2Gbps could potentially yield a constraint in some future installations.
Because a defined group of ONT’s share an upstream path, there is a potential for the collision of data. To correct for this, the OLT allocates specific time slots for each ONT to transmit Its data back to the OLT. This works well with Telecommunications/cable company networks where a majority of the data payload demand is downstream. However, in an ITS environment, the opposite is true as the upstream demand is exponentially greater and more critical.
No Power Over Ethernet (PoE) capabilities via ONT.
The recent increase in new transportation data sources coupled with the enhanced densities of data sources are leading to a number of new analytics tools for transportation professionals. One of the latest analysis resources to recently emerge fuses real-time/near-real time social data with traditional mobility data (speed, location, trajectory). Human sensor networks wield a much more comprehensive ability to not only report on traditional mobility data attributes, but also provides additional resolution for location and time, as well as characteristics with regards to “sentiment”.
Sentiment analysis aggregates and filters real-time data from the web and social media resources and reduces the data for context and transportation value. Sentiment mapping links data sources with location, or future locations with detected sentiment related to each location. For example, data crawlers and filtering for key words (accident, crash, traffic, I-66, I-95) and assessing sentiment tied to messages (slow, clear, backup, bad, good). The resulting sentiment model is then tied to time and location data for a resulting sentiment graph. Sentiment mapping and sentiment analysis can also be utilized for predictive analytics where content is determined to identify future location-based sentiment for future conditions.
The following links provide a primer as well as preliminary information on development and configuration of sentiment data models.
A lot has been written about “big data” lately. The rapid growth of varying data sources coupled with the enhanced density in data sources is establishing a huge resource for transportation operators. The rapid proliferation of data sources from new devices such as smartphones and other newly connected devices, in conjunction with the advancement of technologies for data collection and management have manifested a sizeable inflection point in the availability of data. So what does this mean for ITS operators and the systems they currently manage? What will be required to extract and leverage values associated with “big data”?
At First Glance
Federal regulations for performance measures and real-time monitoring associated with MAP-21 and 23 CFR 511 have implemented a framework for the increased need of new, refined data and information systems. System enhancements will require improvements to existing networks and communications systems in order to optimize data and metadata flows between data sources and central applications. Robust central network equipment, including L3 switches, servers and storage will also be required. Enhanced security measures associated with new data sources and big data values will also need to be reviewed and attended to. New central data warehouse infrastructure will also be required, including new database applications (such as Hadoop), that are capable of managing “big data” and the “Internet of Things” (IoT).
Deeper Dive
A closer look reveals additional layers of change required in order to begin abstracting value from the new data sources. “Big data” will also require somewhat less obvious changes in the way transportation agencies currently do business.
Increased Data Management and Analytics Expertise – The new data paradigm will require new staff skills, most notably, experience in data analytics (Quants). Staff skills will not only require knowledge of the data available now or potentially available in the near term, but also understand transportation systems in order to apply the most beneficial data mining tactics available. The new role must not only be aware of current data and information needs and values, but also be cognizant of what is capable, and potential hidden values currently unrealized or unknown by an operating agency. The new role will also be an integral part of the development of embedded system features and be able to identify nuances in data meaning, as well as establish effective predictive analytics.
Policy and Digital Governance – New data sources are also giving rise to discussion regarding privacy and liability. Data sourced from private entities will always contend with privacy fears and concerns, at least for the near term, although recent analysis is showing a steady lessoning of those fears as “digital natives” begin to represent a greater percentage of the traveling public. Data generated from sources outside of transportation agencies, but utilized by transportation agencies for systems operations, can lead one to question who is responsible should data errors occur that might affect a system.
Networks and Communications – Data sources, formats and general data management practices will need extensive review of existing conditions. What values are attained from real-time, or near real-time collection from subsequent analytics, as well as determining what data is less time dependent. Existing formats and protocols should also be included in the mapping exercise. For example, CV will require a mandatory upgrade of IP protocols from IPv4 to IPv6. General planning regarding the utilization of “the cloud” need to be weighed for benefit-cost. Third-party data brokers and other outsourcing alternatives such as cloud computing need to also be assessed.
Data Management and Analysis Tools – Operating entities also need to look at implementing data management tools (applications) that will assist in extracting value from large data sets. These tools should be integrated with core systems, and provide real-time metrics of collected data. The tools should also provide the ability for “Cloud collaboration”, in order to process data stored by third parties, or general data stored in the cloud.
What to do
Transportation budgets are as tight as ever. How can operating agencies begin to make incremental steps towards the goal of realizing benefits associated with “big data”? The first step is to begin now. Start by mapping existing data sources to existing data management technologies, policies and processes, from end to end. Also, widen your perspective and begin to look at possible benefits from a wide array of new data sources. In addition, “open” it up, and benefit from the wisdom of the crowd. New analytics skill sets should be considered a condition of certain new hires in the transportation and ITS planning departments. A staff member should be designated for leading the way with decisions regarding “big data”, relationships with third party data brokers, cloud management, as well as be responsible for implementing an agile framework for next-gen data systems.
There is no denying “big data” and its importance to next-gen ITS applications. The emergence of a vast, omnipresent data cloud is enabling new knowledge and wisdom to be attained, as well as facilitate new operations models for the mobility manager. Unfortunately, parochial data systems and data management strategies are quickly becoming obsolete with regards to managing this quickly evolving paradigm. As a result, the need for operating institutions and mobility managers to understand “big data” and implement new, comprehensive and overarching data management strategies has never been greater. Next-gen data and information systems will need to be autonomous, contextual, predictive and real-time. The overall impact is cascading in that now a new strategy is not only desired, but will become an essential function, as the proliferation of meaningful data sources accelerates. The time for agencies to plan, prepare, implement and transition is now. The following aggregates a few thoughts into an introductory package for agencies to consider as they get started, in hopes of widening the road to success.
THE NEED
Although all of the values of new “big data” resources are not yet fully understood, the danger of getting bogged down in the data deluge is already being felt. Before these new values can be leveraged, we must first review, research and retool, predicated on a sound understanding of existing conditions and extensive research and evaluation of likely future conditions and future capabilities. In addition, programmatic and industry changes such as MAP-21 and the Connected Vehicle are changing the operational fabric and are mandating new requirements for mobility managers, and thus, also need to be considered when developing a new data and information management strategy.
WHAT / HOW MODEL
So where to start? – The following insights are framed within the “What/How” solutions model, or “What do we want/need?”, and then,”How do we do it?” As is the case with all sound planning efforts, an accurate understanding of existing conditions is an essential first-step prior to commencing with future planning efforts.
What
Stakeholders and Champions – The first step is to identify all possible stakeholders (including champions and arbiters), both internal and external to an operating entity. It’s key to remember that the data paradigm shift will cover all departments, agencies, programs and offices within a city and/or region, therefore coordination with an overarching perspective is essential for success. Typically non-traditional stakeholders will now play important roles and become key teammates. The identification of the initial list of stakeholders should include a first draft of a new steering committee or “Data Management Team” (DMT), which should encompass all pertinent agencies and institutions.
What do we have?
Following the formation of DMT, the team should begin to assess existing conditions. Some key questions to get started include:
What are our existing data generators?
What systems are required to support these data generators?
How do we currently source, transmit and aggregate data from existing data sources?
What data and information-based goals and objectives are currently in place?
What are our existing processes for measuring and monitoring the path towards prescribed goals?
What values are we realizing/not realizing?
What standards and formats do we utilize?
What policies and regulations currently exist?
What quality control processes and procedures are in place?
What licensing, warranty and policy factors impact our data and information systems?
These questions will likely uncover significant new understanding as to how an agency currently handles data, and identify opportunities lost or new opportunities for functional improvements. The baseline assessment needs to include identification and mapping of existing supporting systems and infrastructure, including networking and software applications. The exploration should also begin to drill down and refine existing information such as data attributes. A list of attributes might include:
Data
Source
Owner
Use rights
Format
Polling rates
Current uses (realized)
Potential uses (unrealized)
Quality
Cleansing/conditioning
Data Support Systems and Applications
Infrastructure requirements
Software dependencies
Other OSI reference model considerations
Policies, Guidelines and Contracts
Use policies
Cost per byte/poll
Licensing and Warranties
Existing vendor contracts, limitations
Storage and Retrieval
Performance metrics and monitoring
Existing staff requirements
Interim Review – Immediately following initial exploration of existing conditions, the Data Management Team should conduct an interim review of its findings. In addition, the DMT should review any and all existing goals and objectives related to data and information systems. What are we truly trying to accomplish and what are we achieving? What are we not achieving? What are the perceived initial gaps? The initial review of existing conditions will likely trigger additional exploration needs with regards to existing data and information systems. The interim review will also likely uncover additional stakeholders, both internal and external to the mobility management ecosystem.
Mapping – Map your findings. As with all good wayfinding processes, a “you are here” marker is essential. The goal is to map all exploration activities and contextualize the existing data and information system landscape. In addition to narrative and graphical mapping, a spreadsheet or database is also helpful for tracking results such as data and information attributes.
Projections and Forecasts
The next step will be to begin exploration and research of existing trends and to conduct forecasting of future trends and forecasted conditions. Predicting the future is always challenging at best. However, with a sound, comprehensive strategy in place, an organization can best plan and implement strategies that prepare an agency for potential future conditions. Trends analysis and future conditions forecasting will assist in establishing a pragmatic orientation for the foreseeable future. These assessments should be conducted in parallel, yet separate paths from the existing conditions exploration and mapping tasks. (The simultaneous work efforts will assist in finalizing the existing conditions survey task by uncovering additional gaps in the initial existing conditions survey and identify additional existing conditions research required).
Current Trends – Current trends such as cloud-computing, smartphones, mobile apps, private data sourcing, crowdsourcing, and integrated corridor management (ICM) need to be identified and included in new data management strategies. MAP-21 and other Federal requirements will mandate a new minimum acceptance level for the operating entities and also need to be immediately included in planning efforts. It’s important to look past today’s sheen of certain applications and technologies to truly understand where industries and agencies are headed.
Future Trends – Connected Vehicle, including V2X, or V2I components will directly impact operating agencies and the way they do business in the coming years. Other likely future trends such as the autonomous vehicles, City as a Platform and integration of transportation networks will directly impact the data and information framework. Additional trends such as system automation and data driven systems will amplify the need for pertinent real-time data.
Research
The “Future-Casting” task should also assign segments of industry to in-house champions (domain expertise), in order to monitor federal regulations, funding streams, the information technology and automobile sectors, university, state and federal research tracks, consumer technology markets, as well as tangential markets and adjacent internal agencies and divisions.
What do we want/need?
Immediately following the initial existing conditions survey and research and forecasting of future trends and conditions, the DMT should revisit original goals and objectives regarding data and information systems, and modify/append accordingly. At this point, a traditional “User Needs and Preferences” assessment can be conducted, and should follow a traditional Systems Engineering framework. Some of the basic questions to address include:
Have we properly identified and defined all of our goals and objectives
How do you plan to leverage enriched data environments?
How will this foster enhanced wisdom and adaptive genius within our mobility ecosystem?
How will me monitor our progress towards achieving our goals and objectives (performance measures)
Have we instituted agency changes appropriate and sufficient to meet our goals and objectives?
To this point, you should have a pretty sound understanding of all of the existing data and information systems within the agency/region. However, it may require additional iterations of the exploration, mapping and wants and needs assessments to truly understand where you are, and where you want to be (goals).
How
Once goals and objectives have been set, we can begin to assess “How” do we get there? As with most planning efforts, an alternatives analysis and a Long Range Plan and Implementation Plan need to be developed. A scale vs. value and ROI assessment is conducted at this point as well. As is always the case with future-proofing, the key is not to plan to design for specific (undefined, and in some cases unknown) technologies, methodologies and strategies, but to identify and anticipate likely future conditions and implement a framework that is agile, flexible and capable of embracing future technologies, strategies and methodologies.
The next step is to establish a requirements-based blueprint and roadmap to transition from today to tomorrow. It’s also important to set measurable goals and identify necessary performance metrics in order to track progress towards goals and objectives, and to be able to conduct evaluatory assessments. This step should also include a traditional gap analysis as well. The Long Range Plan should also include a Concept of Operations. This step will also begin to define “rewiring” necessary for executing the new data and information management program, which should also include business rules. In addition, new data management schema needs to be integrated with the overall (typical) planning processes, including budgeting, long-range plans and regional plans.
Staffing resources and annual operations should also be assessed at this point. Domain expertise, staffing and skills requirements will need to be addressed. This should be included in the initial existing conditions exploration. A new Data Manager position is likely the most appropriate first hire. This individual may be an MPO, DOT or local agency staff person in charge of overseeing all harmonization of data and information systems across all platforms, jurisdictional and agency boundaries. A Data Scientists/Analysts will also likely be required.
Additional Challenges and Potential Impediments to Consider
Initial Buy-in and Engagement – As with most new initiatives, getting up from the “comfy couch” can be the biggest challenge to implementing new or improved strategies. Generating the initial inertia and momentum will require champions at the administrative, technical and arbiter levels, within all stakeholders, departments, agencies and regional staff (MPO).
Data use and retention policies – some data may be approved for certain uses, however, additional uses may raise privacy, licensing or ownership issues. This challenge also gives rise to additional hurdles including operational governance and regulation of the new data and information system. For example, can private data be sourced to operate public systems (signal systems, etc.) were safety is critical?
Integration and Standardization – what level of data and system integration is optimal, or will achieve the greatest Benefit/Cost ratio for an operating entity? What granularity and resolution (data density) is required for each component of the goals? Automated monitoring and performance reporting will be a key to success with regards to overall integration and standardization.
Sustainability – A new funding stream (outgoing) is likely required. However, the potential for additional revenue streams (incoming) is also likely. Funding needs to be identified for the initial capital outlay, as well as annual operations and maintenance cost for the life-cycle of the system and subsystems.
Security – As the data reservoir expands, and the network to support and manage the data and information systems expands, so will the security concerns. New policies and data management applications will be essential. Data storage, encryption, access rights, use rights as well as infrastructure and support applications should all be included in the initial security assessment and security planning efforts.
Webopedia defines the Digital Divide as “A term used to describe the discrepancy between people who have access to and the resources to use new information and communication tools, such as the Internet, and people who do not have the resources and access to the technology. The term also describes the discrepancy between those who have the skills, knowledge and abilities to use the technologies and those who do not. The digital divide can exist between those living in rural areas and those living in urban areas, between the educated and uneducated, between economic classes, and on a global scale between more and less industrially developed nations“.
The so-called “digital divide” is a complex multifaceted issue, which includes social, economical, physical, geographical and educational barriers to the deployment and scaling of innovative transportation solutions. Although not new to the transportation industry, the digital divide is gaining in importance, as innovation is increasingly reliant on digital technologies. So the primary question at this point: Is the divide closing or widening in the era of next generation transportation solutions? And what can be done to facilitate improved accessibility for all demographics across all platforms.
Technological Barriers
The recent megatrend of “consumerization” is shifting ownership of critical components of transportation systems from the traditional public control to the private end-user (traveler). This paradigm shift is a relatively new phenomena in the ITS industry, and one that now places a significant reliance on the use of privately-owned technologies. Although the affects of this new technology delivery model are not fully understood at this point, it is clear that market penetration will be a key factor to their overall success.
Consider that it took approximately 15 years for the cell phone to achieve 92% market penetration among all people in the United States, and that the smartphone is tracking to reach that level of penetration in one-half to one-third the time. However, transportation solutions will need to contend with a technology and service divide for the near term.
Vehicle-based technologies have also created a divide, as newer platforms have facilitated improved safety and efficiency. However, the full value of these technologies cannot be fully realized by all automobile owners for the better part of the next decade, if not longer.
Other technological barriers are outside of the end-users control. For example, geographic barriers, such as those associated with wireless communications availability, demonstrate the divide based on accessibility outside the reach of an end-user.
Economic Barriers
In many cases, economic barriers to next-gen ITS go hand-in-hand with the aforementioned technological barriers. However, in many cases the divide is solely based on the ability of the end-user to afford the purchase and on-going costs to operate technologies necessary to participate and support certain next-generation ITS solutions. The credit barrier is another barrier that is not unique to the ITS industry, but one that must be continuously dealt with as the digital age evolves, and the mainstreaming of next-gen ITS continues.
Social Barriers
Education is a multifaceted barrier in its own right. Simply making technology accessible to all consumers is not enough to ensure successful use. End-users must not only know how to operate technologies, but must be informed and understand how to realize the potential values of the devices. Language barrier, whether to discern DMS messages, utilize mobile applications, or simply understand static street signs has been mostly unaddressed. The Digital Divide also includes accessibility as it relates to age and disabilities, and subsequent inabilities to access Information and Communications Technologies, or ICT.
Conclusion
Recent trend analysis and conservative projections are showing a narrowing of the digital divide with regards to many of the demographic components of the digital divide. However, in some ways, transportation industry professionals will always have to contend with some form of the digital divide.
The digital divide is taking on new characteristics, now becoming a two way street. What was once a void of opportunity on the users end, is now limiting potential for systems to capitalize on potential user data. We, as ITS practitioners, planners and designers should be continuously cognizant of the digital divide, the barriers presented, and strive for development and deployment of next-generation ITS solutions with the aforementioned barriers in mind. It is my position, that ITS should always consider non-technological solutions and methodologies as an integral component of all ITS deployments, and continuously focus on narrowing the digital divide as much as possible.
Another International Consumer Electronics Show (CES) is in the books, and once again, Next-Gen ITS was a key contributor to the news of the week. One of the interesting aspects to this year’s CES was the fact that it was held the same week as the Detroit Auto Show, a key event on the automakers calendar. However, even with the overlap in event scheduling, automakers including Ford, GM, BMW, Mercedes and Toyota were all in attendance at CES, further amplifying the importance of the recent shift in consumer transportation technologies.
Some of the key ITS-related trends from CES this week included:
The emergence of open APIs from automakers for crowdsourced app development,
The continued rapid growth of in-vehicle connectivity/telematics systems,
Deeper, enhanced integration of consumer devices with vehicle-based information systems,
Continued proliferation of context-aware, geofencing-based applications,
Continued integration of wireless providers with vehicle information systems,
Continued migration to cloud-based vehicle networking, and
Continued convergence of mobile software and application platforms.
The following provides a listing of some of the ITS-related news that surfaced at CES this week.
2011 was another excellent year for ITS innovation, with significant advancements along multiple market segments, and most indicators point to similar advancements for 2012. The following provides a 12-month overview for Next-Gen ITS in 2012. The summary is a result of multiple assessments, including analysis of market patterns, technology relationships and dependencies, adoptability and overall market timing with regards to emerging solutions and technologies. As always, your thoughts are welcomed and encouraged.
NEW ENTRIES FOR 2012
2012 will see a number of new entries for Next-Gen ITS technologies and solutions. Some of the following may have been born in 2011, or were initially planned and/or identified for continued development 2011, yet 2012 will mark the first real significant showing of these technologies or represent the point at which these technologies and solutions become pervasive.
New Data and Information API’s from the Automotive Industry – The rapidly expanding telematics and vehicle “infotainment” industry, coupled with continued explosive growth of the commercial connected vehicle will see the emergence of new data streams, provided by the auto industry, and openly accessible to the developer community. The open data streams will facilitate the development of additional applications and services, and represent the industry’s first extensive, real-time, anonymized data set sourced from traditional passenger vehicles. We will also continue to see enhanced partnering between the automotive industry and the big software and computing companies such as Microsoft’s partnerships with Ford and Toyota, as Detroit moves to the cloud.
Smartphone Data Integration for System Operations – To date, mobile data sources such as smartphone GPS and Bluetooth data have been primarily utilized for “passive” system use, such as traveler information systems like DMS travel times. 2012 will see the expanded use of public and private data sources for “active” systems operations, where public safety is involved (legal issues). The new data sources will see the first integration with signal systems and freeway management systems for “active” support of systems such as variable speed limits, ramp metering and traffic signal operations. This new use of sourced data will require significant regulatory and policy assessments, however, for private data to make the next step, it will need to be approved for more critical uses.
Transportation Data and Information Management – A relatively new staffing position within operating entities will begin to take shape in 2012. This new position will be responsible for the aggregation, processing, storage and management of all transportation data and information. As data availability and data-reliant services explode, agencies will be faced with increasing internal needs with regards to architecting and managing their transportation data and information systems. Agencies will need to begin considering outsourcing, or staffing this role internally. 2012 will show the initial signs of this trend starting to emerge, as “big data” hits both transportation as well as the enterprise.
Private Data Tools and Services – 2012 will also see new market segment growth in response to the growing need for tools and applications that utilize private data sources. Agencies purchasing private data will be looking to maximize the functional value of the costs associated with the procurement of the private data. This will include stand-alone planning and analytical tools, as well as operational support applications.
CONTINUED GROWTH FOR 2012
A number of next-gen ITS technologies and solutions that emerged in 2011 will see further incubation and in some cases, explosive growth in 2012. The following provides a brief overview of what is expected for the coming year.
DATA Next-Gen Data – Next-Gen Data, including Bluetooth and GPS-based (smartphone) data will continue to take root and expand within the ITS community, as well as provide data and information for the development of Next-Gen ITS. Both public agencies and private vendors will continue to aggregate and integrate mobile, real-time data with current and next-gen ITS. The next 12 months will see increased focus on the big data “piñata”, as both public and private entities come to the realization that the big data “grab” is on, with ownership, usage rights and data openness hanging in the balance. Data coverage and densities will continue to expand at rapid pace, facilitating the emergence of higher-resolution Next-Gen ITS services such as arterial travel-time information systems. Privately sourced data will also see increased use for transportation planning purposes. “Big Data” applications and algorithms will also gain in importance of the next 12 months.
Data Liberation Front – The “Open Data” movement will continue to expand, facilitating continued citizen engagement and establishing fertile ground for the development of applications and solutions generated from the “hive-mind”. “Open Data” initiatives will continue to expand world-wide as we will see continued democratization of many transportation-related data resources. However, some new challenges will also confront the data liberation movement, including Next-Gen issues such as maintenance of crowdsourced applications and resistance from traditional vendors to openly release data that was traditionally private (controlled) under existing contractual agreements.
TRAVELER INFORMATION Next-Gen ATIS – Next-gen traveler information systems will also continue to emerge and mature in 2012. The FHWA’s EnableATIS program, coupled with private industry advancements based on location and mobile technologies, will make 2012 a pivotal year for Next-Gen AITS applications and solutions. As previously noted, Context-Aware, location based applications will begin to firmly take root, and fortify earlier versions of GPS-based traveler information applications. Peer-to-Peer (P2P) data and information exchange, coupled with social analytics and integration data and information from other related ecosystems will continue to enhance the resolution of data collected and information disseminated.
Context-aware, Location-based Services – Next-gen ITS will continue to pivot from earlier technologies and methodologies, and continue migration to mobile, user-based data and information systems, tailored to each individual users (traveler) unique requirements. Traveler information based on individual user-preferences, sentiment analysis, user-history and hyper-local environmental conditions will continue to mature. Geo-tagged, location-based traveler information will also emerge, allowing the provision of traveler information to be pinned (virtually reside) at specific coordinates, and be ingested by those passing through/near those coordinates.
Predictive Analytics and Forecasting – Predictive analytics and forecasting will move to center stage in 2012. Coupled with context-aware solutions, predictive analytics and forecasting will enable further development of user-unique traffic and traveler information systems. Predictive analytics will be enhanced with the addition of social engineering and behavioral management principles, in addition to the arrival of continuously enriched real-time data sets, robust data histograms and advanced modeling and analytics. Embedded predictive analytics will also be implemented in conjunction with gaming mechanics to generate user recommendations that are best suited holistically for the overall efficiency of the transportation network, thus optimizing operational efficiencies.
CONNECTED VEHICLE Connected Vehicle Research and Testing – 2012 will see significant development of the Connected Vehicle program, from the Government’s perspective, including the official launch of the Safety Model Deployment project in Ann Arbor, Michigan. Next-gen ITS initiatives including AERIS and EnableATIS will continue to create the foundation for the pending decisions to be rendered by NHTSA in 2013/2014, as well as continue to frame the technological environment for numerous Next-gen ITS solutions. 2012 will also include further research and advanced development of Dynamic Mobility Applications, which will closely integrate with Context-aware, location-based applications and the Connected Vehicle program. Networking protocols and standards (architectures), both in-vehicle and interfacing with vehicles, will also begin to take shape in 2012.
Smartphone Integration with the Vehicle – 2012 will see enhanced refinement and resolution with regards to the integration of the vehicle and smartphone, continuing migration towards a seamless user (traveler) experience. The OBD-II and the Smartphone’s wireless (Bluetooth) and hardwired ports will be better defined and optimized. The automotive industry will continue to rapidly deploy the commercial infotainment market sector, which will include traveler information and other overlapping ITS-related services via deeper integration with smartphone applications and enhanced embedded vehicle data and information systems. 2012 will also continue to identify, define and refine data and information architecture for the automobile. Ethernet and HTML5 will likely lead the way in the automobile protocol stack.
TRAFFIC MANAGEMENT Systems Integration – 2012 will continue the push towards the integration of ITS. The Integrated Corridor Management (ICM) Systems Initiative will continue to develop and disseminate guidance to assist local agencies with implementing integrated corridors. Demonstration and evaluation of the Pioneer Sites will continue through 2012 (and into 2013). Next-Gen ITS will also continue a slow but assured march towards the integration of existing “stove-piped” transportation systems. Cloud-based applications will facilitate the transition from siloed, stand-alone transportation systems, to fully-fused and homogenous operating systems (further down the road). A key facilitator will reside in the development of applications that interface and integrate with existing instrumented stand-alone systems. The new applications will eventually include multimodal predictive analytics and multimodal management and decision support systems. We will also begin to see the emergence of complex adaptive systems begin to emerge during the initial fusion of systems.
Next-Gen Parking Systems – 2011 saw the continued testing and development of a number of next-gen parking systems throughout the Country. 2012 will see the mainstreaming of new technologies and applications for next-gen parking management. This will include refinement of congestion-pricing schema, further integration with personal mobile devices, as well as integration of parking management systems with adjacent traffic management systems.
LEGISLATIVE Reauthorization – The next transportation bill is expected to pass before the summer of 2012. We’ve heard this a few times before, and there are no guarantees that existing legislation gets extended once again, but most key indicators point to something getting done in Q2 or Q3 of 2012. Of course, the final version of the Bill will greatly impact ITS program development and subsequently steer the direction of many Next-Gen ITS solutions for the coming years. Reauthorization will build around the four Surface Transportation Safety Bills, including S.1953, the Research and Innovative Technology Administration Reauthorization Act of 2011, which extends funding for RITA, that were introduced in December of 2011.
Distracted Driving – 2012 will be a critical year for the continued discussion, definition and legislating of the distracted driving issue. NTSB’s call to ban the use of all electronic devices, although greatly impactful, will ultimately get down to decisions made at the state level. The initial call by the NTSB is already receiving a great deal of push back from the scientific and technology communities, as well as the safety community with regards to actual data supporting the NTSB claims.
COMMUNICATIONS AND INFORMATION TECHNOLOGY Web-based (Cloud) Solutions – Probably the largest IT-related influencer in 2012 will be the continued movement of central networking and systems to the cloud, as agencies and businesses discover the tremendous cost savings and benefits associated with cloud-based services. Maturing consumer and enterprise services such as Amazon’s EC2 and Microsoft Azure are making it painless and attractive, both fiscally and technically. Current lean economic conditions, coupled with vendor-based goals for developing cloud-based applications will facilitate the initial transitions. Cloud-streaming and cloud-processing will also enrich functional (processing) capabilities at the mobile-user level.
Wireless – 2012 will continue with the wide-scale deployment of so called “4G” cellular services. Naming and specification criteria aside, the bottom line will be increased commercial wireless bandwidths. Also, Wi-Fi will begin initial migration to newer 802.11 protocols, including 802.11ac and 802.11ad. Near Field Communications (NFC) will continue to be demonstrated for next-gen ITS solutions in 2012.
BEST OF THE REST FOR 2012 Next-Gen Policy – 2012 will increase dependencies on policy makers with regards to implementing, operating and maintaining the aforementioned next-gen ITS solutions. In addition to new data management policies, substantial regulatory modeling and framework will be required to address new connected vehicle technologies as well as utilization of private data sources for systems where public safety is concerned.
Social Tools – As previously noted, 2012 will see continued implementation of commercial peer-to-peer (traveler) solutions and applications. These user-based data and information systems (social) will mature in 2012 to include advanced behavioral management strategies, as well as potentially integrating with more formal traffic management systems.
KEY QUESTIONS FOR NEXT-GEN ITS IN 2012
Some of the key variables for 2012 will include:
• How will Reauthorization and continued budget shortfalls in all transportation arenas affect the innovation, realization and growth of next-gen ITS?
• Will mileage-based/usage-based (infrastructure-less) payment and tolling systems get a shot at a large scale deployment? The technology is in place, already being deployed by multiple insurance companies in numerous configurations. Test beds conducted by Oregon, Nevada, Minnesota, Colorado and the I-95 Corridor Coalition, will provide insights to potential deployments and overall viability.
• Will the “Open Data” movement energize existing “Open Source” platforms – will Android and/or the Arduino platform (Open Source) make significant inroads into transportation, and provide a valued resource for Next-Gen ITS?
• What will be the lasting impacts on Next-Gen ITS with regards to the continued “flattening” of organizational hierarchy’s, the “consumerization” of the enterprise, and the “fragmentation” of the internet with regards to proliferation of mobile computing platforms?
• How will Next-Gen ITS begin to address the digital divide that exists technically, socially and economically? As consumerization continues to provide the foundation for next-gen ITS solutions, how will the non-technoliterate adapt and be provided for?
• Will there be a need for an update to the National ITS Architecture, as a result of the recent emergence of aforementioned technologies and solutions?
The recent emergence of new web and mobile computing technologies, coupled with the explosion of high-resolution, context-sensitive data sources has provided a set of powerful tools and resources for ITS practitioners. However, as a result, the implementation of these technologies are generating an expansive array of new policy demands associated with the selection, procurement, installation, operations and overall governance of new systems utilizing these new technologies. The Connected Vehicle, Big Data, Government 2.0 and Private Data are just a few of the next-gen solutions that will require significant policy development.
Big Data and Data Management
The explosion of viable data viable for ITS solutions has given rise to numerous policy challenges. So called “Big Data” represents the exponential growth of data available for ITS via new data sources such as smartphones, connected vehicles and other connected devices (infrastructure). The management of this data will initially present significant policy challenges for public agencies responsible for the entire vertical integration of data management strategies, from the collection (origin), aggregation and processing, to development and dissemination of actionable content (destination). Policy and governing guidelines will be required for basic configuration issues, such as data formatting, to the more complex issue regarding rights and ownership of the new data, throughout the entire “life cycle” of the data. The cloud computing model has also generated issues concerning data management policies.
Private Data
Private data is also generating substantial policy debate. Private data has proven successful for certain “passive” ITS solutions such as providing the data for travel time information. However, the continued integration and “active” use of private data, whether obtained from private citizens or third party data vendors, will pose challenges to those who curate and manage public policy. Can private data be used to supply data to feed traffic management systems where safety is involved? Can private data vendors assume the risk associated with signal systems, freeway management systems or other traffic management systems that require data to fuel operational applications (algorithms)? Traffic management systems are traditionally reliant on publicly owned and operated data sources, such as point detection devices (Microwave, Inductive loop, video, etc.). Legal issues associated with potential tort, negligence and liability will need to be addressed for all systems that “actively” utilize privately sourced data, particularly where human safety is involved.
Open Data
Opening data to the public for crowdsourcing new applications and solutions has yielded valuable transportation tools and applications, but who is responsible for problems associated with the publicly-generated application? Who owns the data that feeds the system? Is the data open and rights-free to anyone in the general public? What about private technology vendors that generate data through their proprietary applications, technologies and/or solutions? Many vendors claim sole rights to the data, which precludes the data from being “open”, even though the data was generated from public infrastructure or the public itself, thus “locking down” the data and precluding it from other, free uses.
Connected Vehicle
The utilization of connected vehicles is possibly the most complex technology that will require significant public policy and governance. Successful implementation of the connected vehicle ecosystem will require addressing substantial policy issues on a number of fronts, including privacy, driver-distraction, data ownership and usage rights, and probably most important, liability. Decisions regarding overarching governance will be required for data ownership and usage-rights for all data transmitted to and from a vehicle (V2V, V2I, etc.), to the cloud, and between public infrastructure and private devices. Who will be liable for accidents related to connected-vehicle data or technology errors?
Government 2.0
The emergence of “Government 2.0” strategies has also posed significant public policy debate. The engagement of the general public for the support of operating and managing public agencies, including transportation systems, has been highly successful in many respects, yet generated a new “breed” of policy issues. In addition, the use of social media tools to implement two-way engagement with the citizens has significantly challenged document management requirements, such as those associated with open records requests, or information management requirements associated with Sarbanes-Oxley.
Others
As always, privacy concerns will be a primary concern for all of the aforementioned policies that are developed. In addition, the “consumerization” of information technologies, where the citizen is taking on the rights and responsibilities of owning and operating their own computer devices, has shifted some of the enterprise strain to the consumer, and facilitated a “flattening” of organizational structures, yet what are the legal responsibilities for the overarching agency where data is generated, or operational efforts are conducted and issues arise? It’s clear that a strong policy framework and organizational governance will be essential in successfully implementing and managing next-gen ITS.
the enhanced density in data sources is establishing a huge resource for transportation operators. The rapid proliferation of data sources from new devices such as smartphones and other newly connected devices, in conjunction with the advancement of technologies for data collection and management have manifested a sizeable inflection point in the availability of data. So what does this mean for ITS operators and the systems they currently manage? What will be required to extract and leverage values associated with “big data”?
Terranautix 