SmartRail World Exclusive
The transportation industry is undergoing a drastic change, driven by wide-ranging and varied influences. One of these is the evolution of connectability and data gathering, whether through sensors, the Internet of Things (IoT), or Artificial Intelligence (AI). And this data, collected for real-time information, is the driver behind innovations as varied as GPS, mapping technology, Wi-Fi and cellular technologies. These technologies allow the transportation industry to connect in real-time with municipal data systems, offering the opportunity to create a cohesive system of predictive analytics, information and help cities to meet the increased demand of rider expectations.
Our Editor, Luke Upton, wanted to find out more about these changes, the opportunities and the key areas of potential growth, so recently spent some time quizzing William Watkins who leads the Transportation Practice at Fujitsu Network Communications, Inc. As practice leader, William works across the transportation industry including light and heavy rail, public transit, intelligent transportation systems and security systems. With more than 30 years of experience in technology, he is well placed to offer some very useful insights into this exciting and emerging industry…
Luke Upton (LU): Thanks for the time today, as a technology professional with extensive experience, how have you seen passenger demands change in recent years? And what has been causing this change.
Williams Watkins (WW): No problem Luke. Passenger demands are changing dramatically. Millennials are at the forefront of a society that’s always on and always connected through smart phones, tablets and wearables. In conjunction with this shifting workforce dynamic, the modes of preferred travel are also changing. Adding to the matter is the fact that these consumer demands are changing at just as fast, if not faster, a pace than technology can match.
According to a study conducted by the American Public Transportation Association, millennials are happy biking or walking. However, they also view public transit as a way to connect with people and work during their commutes. With smartphones, it's easy to figure out bus and train schedules and stay plugged in while on the move.
The ability to connect with digital resources and accomplish work while traveling is a growing trend and an important benefit. Other trends we’re seeing in the industry include the need for a more reliable system, real-time updates through mobile apps or interactive kiosks, Wi-Fi or 3G/4G connectivity throughout a journey, a user-friendly and intuitive travel experience, and lastly, a safe, comfortable, and easily accessible transport facility.
Shared methods will also continue to grow in significance, and public entities should identify opportunities to engage with these modes to ensure benefits are widely and equitably shared.
LU: With the huge increase in data available to transport agencies, how do you best separate what is important, from what is not?
WW: That is a question I’ve encountered a lot from the industry. We have all this data, but what does it mean and how can it be used? Before you start separating and analyzing data, you have to survey the community on what their needs and desires are for a multimodal transportation system. With the objective data collected through surveying constituents, you can create your initial analysis baseline. Every community is unique, as is the baseline needed to analyze the data. Starting with a survey allows you to identify what’s really needed and wanted in the area.
Partnerships with communities, quasi-governments, businesses, and transportation-oriented development consultants are key to efficiently collecting and sharing data, surveying the public, and creating a baseline for analysis. Ultimately this ensures we can effectively use all this information.To understand the people living within their increasingly connected society, these organizations must take a collaborative, human-centric approach to the entire process. No longer can they take a lone wolf approach to survive and increase ridership.
Sustainable communities must be well-connected, with easily accessible transportation networks that provide attractive, safe, comfortable, and cost-effective service. It’s also important for them to improve mobility, and support economic vitality and environmental quality.
LU: What role do you see for the future of Artificial Intelligence (AI) in relation to transportation?
WW: In the past decade, Artificial intelligence (AI) has led to major breakthroughs in a computer’s ability to understand and interpret tens of thousands of data inputs. This process, often referred to as machine learning, allows computers to recognize and predict patterns based on this collected data. It has been applied to industries ranging from criminology to healthcare to retail.
AI is uniquely suited for traffic management because of its ability to predict traffic flow patterns. It has, and will continue to be, used for city planners trying to understand the expected impact of long-term building projects or event activity, as well as accurate real-time prediction of the time it takes to get across town on any given day. It also helps city planners better understand the impact a traffic accident will have on car, bus, or train commute times. And AI and real-time analytics will continue to influence how cities learn to better serve an increasingly connected community.
LU: The use of Big Data can enhance the passenger experience, what are some of the best examples you’ve seen around the world of this in action?
WW: Big Data is influencing the passenger experience around the globe. It enables city officials to better understand their constituents’ travel needs and expectations. According to a study conducted by Fujitsu with Frost & Sullivan ( @ ), technology is enabling and changing social expectations and causing a dramatic change in the transportation industry.
One example from aforementioned study examined how big data came into play when a major European city was looking to improve its rail, bus, and other transport systems. It was concerned that it took too long for citizens to get across town and was hurting the city’s productivity, costing the local carriers excess money, causing ongoing complaints from the citizens, and creating a bad image of the city for tourists. To solve this program, Fujitsu’s team worked with the city, bank, and transport providers to create a card for seamless transport across train and bus, with future options for bike-share and car-share applications. Fujitsu ( @ ) then created a user-friendly app that will tell users the fastest route across town based on real-time inputs. In the future, the company plans to implement a predictive algorithm that will show the best route a few hours or weeks in advance.
LU: One of the key Fujitsu developments in this area has been your Traffic Optimization Methodology, how does this work to bring data streams together to help build smarter cities?
At its core, Fujitsu’s Traffic Optimization Methodology is a layered approach to a smart cities framework. It captures location data from diverse sources, aggregates it, and uses analytics to generate the best real-time transport, as well as short and long-term planning decisions.
There are four main areas of execution: data collection and aggregation, data management and analysis, optimization, novel service creation.
Data Collection and Aggregation where we collect spatial and temporal data about moving objects such as automobiles and pedestrians. Collection and aggregation is via multiple inputs, from roadside sensors to GPS probes, and may be sourced from cities, transport companies, or Fujitsu’s own sensors. At the same time, information on weather conditions, holidays, local events, and the like are gathered for use in analysis.
And Data Management and Analysis which arranges data into layers for easy visualization by traffic planners, transport operators, or researchers. Use of location-based management that stores data with key values of latitude, longitude, and time stamps. This is more effective in tracking moving objects and utilizes the multi-layering capabilities to sort and provide information to the user. For some of its analyses, Artificial Intelligence can be used to improve algorithms and modeling.
Then there's Optimization where real-time data processing capabilities such as real-time visualization of moving objects, as well as analytic capabilities including statistical analysis, predictive analysis, modeling and simulation. The Fujitsu team utilizes its proprietary algorithm to provide insights, optimize routing for individual rides in real time, and to provide the best routing plan for an area for long-term planning.
And finally we have Novel Service Creation based on data processing capabilities, we’re able to develop innovative navigation services for passengers, transport operators, and road congestion managers. These may be as simple as smartphone interfaces or may include new optimization schemes and revenue-generating business models for the operator.
LU: Thanks, that's very useful. The past few years have seen extensive changes in transportation, if you had to pick just one, what would you say will be the biggest change between now and in ten years’ time?
WW: In my opinion, the most extensive change in transportation is multimodal. There is a resurgence in the central parts of cities. Simultaneously, there is an increased availability of travel options in non-central areas. Traveling is no longer as simple as choosing what bus or train to take.
It’s about people considering how they can get from point A to point B economically, quickly, securely, and with real-time updates to their smartphone. For example, personal vehicles are not as important to millennials as they were for baby boomers. Economics has also played a role as well, such as current gas prices, urban form, changes in socio-demographic traits and generational effects, and the expanding availability of travel options.
There are a variety of hypotheses on the reason behind why transportation is changing. The next 10 years of transportation depend on factors and technology yet to be uncovered. Autonomous vehicles and other technological modes will continue to evolve. Policies will change, traffic congestion will ebb and flow in large metropolitan areas, and there will be changes in household composition and demography. As we’ve seen the past 10 years, personal preferences and lifestyles will continue to change. Our society will become increasingly connected, and our transportation system will advance to meet the “new” customer demand.
LU: And finally… as we ask all our interviewees, what’s your favourite rail journey?
WW: I would have to say my favorite rail journey is riding New York City’s transit system. It’s like no other system in the world. One step on the train platform and you’re exposed to the city’s diverse cultures, demographics, arts and entertainment. The experience inside the train and at the station are so unique. As someone that’s been in the transportation field for quite some time, I can honestly say it’s unlike anything else I’ve seen. Where else can you see famous actor or a talented street performer all in one place? I’m an observer and often wonder where people have been, where are they going, and how technology has impacted their journey along the way. For me, these observations have been the inspiration throughout my career to find a way to continuously improve transportation systems for all riders.
LU: Great, thanks for the time today William all at SmartRail World look forward to trakcking the progress of Fujitsu Network Communications as we move into 2017.
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