We are huge believers in the smart city movement. But in order to remain innovative in the face of a changing world, cities need to embrace open architecture and data. That’s because in order to innovate, cities need the power to choose solutions that fit their infrastructure best, and an open smart city strategy allows them to do just that.
For instance, a smart city foundation built on an open architecture is music to a developer’s ears. Open architecture allows the developer ecosystem to access the information they need to create innovative solutions to age-old infrastructure problems. Issues traditionally left to expensive, proprietary vendors can now be solved with the well-trained clicks of a keyboard.
“The more minds dedicated to solving problems, the more likely we are to discover solutions that cater to all citizens, living in cities of all sizes.”
Solve old problems in new ways
Imagine if police had the ability to quickly and easily scan video footage of a specific intersection after a hit-and-run. An app like this could save valuable time in an investigation, increasing public safety. Or, picture an app that tells you what speed to drive to help minimize stops. Cities could cut down on driver frustration, resulting in safer roadways for drivers and pedestrians.
Another solution could help visually-impaired pedestrians safely cross the street. Citizens who download the app would receive audible directions from their smartphone, letting them know when it’s safe to cross an intersection, or hear how many seconds they have left to safely cross the street.
Solutions like these not only increase citizen safety, they also save cities money they would have spent on similar – yet costly – hardware-based solutions.
Ideas within reach
These aren’t just ideas off the top of our heads. We’ve actually developed these apps here at Miovision in just two weeks, using the Miovision Open API and just one ambitious student developer. If a single developer can create three smart city apps in such a short amount of time, imagine what could come out of a team of eager developers, or a city-sponsored hackathon designed to improve your smart city.
The more minds dedicated to solving problems, the more likely we are to discover solutions that cater to all citizens, living in cities of all sizes. We actively encourage cities to embrace the notion of open architecture. Many cities around the world are beginning to see the value in open smart city infrastructure, and are organizing city-wide hackathons to encourage developers to create solutions to help further their smart city visions. Where does your city stand?
This is part 3 of 4 in our blog series on Traffic Insights. This post covers Arterial Performance Measures. Stay tuned for more!
In part one of this series, we covered the evolution of data-driven traffic operations. In part two, we talked about the first set of insights, Signal Performance Measures. Today’s blog covers Arterial Performance Measures (APMs). APMs are traffic insights that allow optimization of traffic corridors.
Part Three: Arterial Performance Measures
As a traffic pro, have you ever been stumped by the following questions:
- Are my intersections in a corridor well coordinated?
- Did that new timing plan adjustment fix my progression problems?
- Is traffic flowing normally in my main corridors right now?
What seems like rudimentary information actually requires planning and systems. But why does it matter, you ask?
Corridor traffic flow is a critical factor in citizen satisfaction. It’s tracked by a discipline called arterial traffic performance, which are a set of metrics that measure travel times across heavy volume arteries in a city. Traditionally, legacy arterial performance systems were only able to measure performance of sequential intersections. Teams had to stitch together this data to get corridor-level views, which wasn’t always easy. But today, new tools make this much easier. At Miovision, we solve for this with APMs.
So What Do These “Insights” Look Like?
Here’s the list of out-of-the-box reports. All are customizable to your city and whatever traffic priorities top your list.
- Point-to-Point Travel Time: A comparison of travel time between two points throughout the day, with ability for comparison to historical averages.
- Corridor Congestion Plot: An analysis of where and when delay is occurring in a corridor.
- Travel Time Index: The median travel time along a corridor expressed as an index relative to the free-flow travel time.
- Planning Index: The 95th percentile travel time presented as an index relative to the free flow travel time. This metric indexes the typical worst-case scenario that a traveler should plan for.
- Buffer Index: The difference between the Planning Index and Travel Time Index. This provides an indication of the perceived extra time that a traveler should plan for above and beyond the average travel time. This metric is a good indicator of Travel Time Variability.
- Progression SPM: Use of various Signal Performance Measures for the collection of intersection data along a corridor. It’s presented in ways that help evaluate the quality of progression along the corridor.
How Are These APMs Generated?
The process is called “wireless vehicle re-identification,” which counts vehicles by tracking MAC addresses from mobile phones. Here’s how it works within Spectrum.
Collect: Included with the Spectrum hardware at each traffic cabinet is the antenna used to transmit data back to the traffic management center using cellular LTE. This antenna supports Wi-Fi signal discovery, and is used to monitor the presence of Wi-Fi devices passing thru the intersection, such as mobile phones or even “smart” vehicles. The Spectrum antenna scans the intersection for Wi-Fi devices in its vicinity, and reads and records addresses within the active range.
Sort: By scanning continuously at all intersections, Spectrum can recognize or “re-identify” a MAC address as it enters and then exits the readable range. Comparing the multiple identifications of the same device, Spectrum can calculate how long it takes for vehicles to travel between two intersections, otherwise known as the “travel time”. Spectrum is able to calculate travel times for 5% to 10% of all vehicles travelling along a route, which produces a statistically accurate model of the true traffic conditions.
Analyze: Spectrum then performs sophisticated data analyses and filtering to combine the individual records to produce a total Travel Time Analysis for an arterial. This analysis indicates how the commute time, delay and congestion varied throughout the day, as well as easy comparison between different time periods.
An important note on privacy. (We’ve highlighted it in red because this is important.)
MAC addresses don’t contain personally identifiable information, but they could be used to “track” a specific vehicle in ways that violate citizen privacy. As soon as Spectrum detects a Wi-Fi MAC address, it is hashed or scrambled, using an algorithm that does not allow the original MAC address to be reverse engineered. The hash key changes every 24 hours to ensure that a single driver’s commutes cannot be correlated over time.
What do APM Dashboards and Reports Look Like?
Here are the two most popular.
Travel Time: This graph shows the selected single day’s travel time (orange) vs. the 12-week historical trend (blue). The 24-hour data is presented as individual vehicle captures (dots) and the associated median travel time (orange line). The trend is presented as median (blue dotted line) and variability bands of 80th, 90th and 95th percentile travel times are shown for the selected comparison window.
Congestion Scan: This index graph shows the travel time for different segments of the corridor and for various times during the day. This can highlight not only when, but also where congestion is building.
Part four of this blog series will appear in a few weeks. It will cover the final category of Miovision Traffic Insights: Maintenance and Performance.
This is part 2 of 4 in our blog series on Traffic Insights. This post covers Signal Performance Metrics. Stay tuned for more!
In part one of this series, we covered the evolution of data-driven traffic operations. We looked at the obstacles many cities face in implementing modern systems. And we didn’t forget to cover the benefits:
1. Better payback from infrastructure investments and 2. Better served citizens.
Both are driven mainly by the traffic insights available from Spectrum.
These insights fall into three main categories: Signal Performance Metrics (the subject of this blog post), Arterial Performance Metrics, and Maintenance and Infrastructure (which we will cover in future posts).
Design, Tune and Troubleshoot with SPMs
Signal Performance Metrics (SPMs) are a set of measurements and visualizations that help traffic teams design, tune, and troubleshoot traffic intersections. They are part of Miovision Spectrum, a turnkey solution for remote traffic signal optimization.
Spectrum provides the entire range of solutions needed to collect, monitor, and understand traffic signals. This includes a managed cellular connection and tools for signal monitoring, video streaming, maintenance alerts, and traffic data insights.
Spectrum’s analytical tools and reports generate actionable information from the raw traffic intersection data. SPMs provide intersection-level reporting of key metrics like:
- Vehicle volumes
- Wait times
- Problem detection
Do These Questions Ring True?
If you recognize the questions below, your team is a good candidate to test these solutions.
SPMs help traffic agencies answer the most basic questions like:
- Are my traffic signals working?
- What kind of traffic volumes are we seeing?
But also deeper-level questions like:
- Do we have an appropriate allocation of green time between movements?
- Are we meeting our goals on vehicle wait times at rush hour?
How Are SPMs Generated?
Spectrum captures event data from the traffic controller, detectors, and other cabinet devices. This data includes signal state, pre-emption, and detector actuations. This is generated from stop-bar and upstream count detectors and pedestrian call button actuations.
Spectrum’s cabinet hardware is able to generate this data even from cabinets housing older traffic controllers. These typically do not produce high resolution reporting. The raw data is securely stored in Spectrum’s cloud where analysis is performed to extract meaningful information and actionable insights.
What are the Infrastructure Requirements for Signal Performance Measures?
Although Spectrum Traffic Insights can be useful in an intersection with no detection, the set of available analytics expands with additional detector infrastructure.
With no detectors, Spectrum SPMs include:
- Red/Green Allocation: The proportion of green time allocated to each approach and movement.
- Pre-emption Summary: Reports of pre-emption events, durations, and triggers, including railroad crossings or emergency vehicle pre-empts.
With stop-bar detection data, Spectrum SPMs include:
- Red and Green Occupancy Ratio: Gauges the demand for the various phases based on the ratio of time that vehicles are present in the associated movements. This allows for tuning of split times between phases.
- Purdue Split Failure: Industry-standard metric that charts the frequency of split failure occurrences, an incident where green signal time fails to meet the vehicle volume demand.
- Simple Delay: Simplified approach delay measures the time between detector activation during red singals and movement service at start of green signals. Simple delay approximates the overall delay experienced by intersection users.
With advanced upstream detection, Spectrum SPMs include:
- Arrival Volumes: Counts of total vehicle traffic through an intersection from each approach.
- Arrivals-on-Red vs. Arrival-on-Green: Counts of total vehicle volume arriving during red or green, giving a rough sign of progression quality for the given movement.
- Purdue Coordination Diagram: A graphical representation of individual vehicle arrivals relative to cycle time (red, yellow and green), highlighting arrival characteristics, and platoon progression quality.
- Average Delay: The length of time vehicles are delayed at a congested intersection.
What do SPM Dashboards and Reports Look Like?
We’ve included three screen grabs for dashboards that are generated by Spectrum.
The UX is designed to 1. Be as simple as possible for a big data set and 2. Show performance patterns over time.
Check these out!
Approach Volume: chart showing the volumes for the chosen day compared to the previous 12-week weekday average and variability bands.
Arrivals on Red/Green over a 12-week period showing the average volume of traffic arriving at the intersection during the red or green phases at different times of the day.
Occupancy Ratio chart showing the stop bar occupancy ratio during red, green, and the first 5 seconds of subsequent red (ROR5) for each cycle of a selected movement.
Feeling informed? Part three of this blog series will appear in two weeks. It will cover Miovision Traffic Insights for Arterial Performance Metrics.
This is part 1 of 4 in our blog series on Traffic Insights. Stay tuned for more!
How do you operate a modern traffic system? It requires more than the ability to manage the asphalt, concrete, steel, and electronics that make up road infrastructure. It’s also about understanding the data being produced by this infrastructure.
As a provider of intelligent traffic signal management solutions, Miovision knows first-hand how traffic teams can leverage the power of traffic data to improve congestion, safety, and operating efficiency.
In this blog series, we’ll describe the current state of city-deployed traffic operations. We’ll also forecast on a future state using traffic insights, made possible by Miovision’s Spectrum solution.
A transformational change is now happening in public sector traffic agencies. Cities are awakening to the power of traffic data as a foundational element of how they plan, build, and operate their road networks. Enabling technologies – remote connectivity, vehicle detection, and software tools – are at the heart of this change. But another key driver is public pressure—taxpayers demand accountability in how public dollars are spent.
Traffic teams are already realizing significant benefits from being more data-driven in their operations and decision-making. Teams are now empowered by data to respond more quickly to public safety issues, optimize existing infrastructure to reduce congestion, and more effectively deploy limited budget dollars. However, this transformation is by no means complete, as agencies continue to face challenges in making the shift.
Despite the recognized benefits of agencies moving to a more data-driven framework, three main obstacles are hindering the transition.
- Supporting Infrastructure: Historically, two pieces of supporting infrastructure are needed to generate signal performance measures: a controller capable of producing high-resolution data and remote connectivity. Traffic controllers yielding hi-res data are limited to only the latest generation of devices, and remote connectivity is lacking in 55% of North America’s traffic cabinets. The lack of this pre-requisite technology and connectivity has limited the rollout of data-driven practices in many agencies.
- Data Analysis Tools: Generating actionable insights from large volumes of traffic data requires analytical software tools. The ATMS or central software systems in place in most agencies today aren’t equipped to perform sophisticated analysis of traffic data. The software systems that do support advanced data analysis are typically limited to modeling signal performance data, without the ability to analyze network-level trends, arterial performance, or maintenance metrics.
- Technical Expertise: Leveraging data-driven tools for traffic operations has historically been complex, and required expertise in two areas: the technical IT skills to maintain sophisticated server systems for data processing, and the engineering skills to interpret and understand the resulting data metrics. Many small and medium sized traffic agencies have continued to struggle to deploy traffic data analysis systems due to a lack of expertise in these areas.
Spectrum’s Traffic Insights tools are helping agencies solve these obstacles by utilizing performance measures and data analysis to enhance traffic operations. Agencies that can effectively collect, understand, and utilize data, have shown the ability to enhance traffic operations in four main ways.
- Network Monitoring: Agencies are able to leverage real-time data to understand when congestion is occurring, and if these events are normal or indicate an issue in the traffic network. This is helping operations teams develop traffic plans using accurate and timely traffic data, as opposed to approximate models based on sporadic and potentially out-dated engineering studies.
- Optimizing Intersection Performance: Agencies are able to leverage signal performance metrics that quantify and analyze intersection flow from a number of perspectives. These tools are helping engineers to not only identify coordination or configuration issues but also significantly reduce the time that it takes to diagnose and solve traffic issues.
- Measuring Impact and ROI: Assessing the impact of a change to road design, a timing plan or a traffic policy has historically been challenging, time-consuming, and expensive. Data-driven traffic agencies are able to leverage the power of “before/after” analysis immediately after making a change so that the true impact and return-on-investment of an initiative can be determined.
- Data-Driven Decision Making: Agencies are not only using data to optimize traffic flow; they are using data to optimize strategic decision-making. Capital and operating investment decisions are areas of traffic strategy becoming increasingly justified by data-driven objectives. Agencies can report on their fiduciary responsibility to a council and the public with assurance that tax dollars and resources are being optimally allocated.
Ask Yourself the Following Questions
Are you struggling to answer the questions below? If so, your traffic agency is likely a good candidate for increasing the use of data-driven operations.
- Based on complaints we’ve re-timed and coordinated a major corridor – is it working?
- I know my signals need to be re-timed, but how can I prove the need with hard data?
- How can I make a stronger argument for support in my funding applications, backed up by real performance data?
- Is my signal green-time being optimally allocated?
- Our staff and budget are decreasing, so how can we maintain our service level with fewer resources?
- I’m not sure that our maintenance contractor is meeting our agreed on service standards – how can I know for certain?
Part Two of this blog series appears in two weeks. It will cover Miovision Traffic Insights for Signal Performance Metrics. Parts three and four of this series will cover Arterial Performance Metrics and Maintenance and Infrastructure.
Until recently, the Internet of Things (IoT) for cities was a lot of hype. As recently as 2015, Gartner listed IoT at the top of the hype curve. Real results were hard to come by, and cities were struggling to understand how IoT fit into their plans.
IoT is Here
Sensor proliferation is taking off. Chicago is deploying hundreds of sensors with it’s Array of Things initiative. It doesn’t stop there. This year Chattanooga, Atlanta, Seattle and Bristol and Newcastle in the United Kingdom will begin installing identical sensors in their cities. Next year, Boston, Austin, Delhi and Singapore will be building their own arrays. And late last year, DOT announced up to $40 million to a mid-size city with the best blueprint depicting a fully integrated forward-looking urban transportation network.
Big IT Challenges
While all of these IoT devices will provide valuable information, they’ll also present major security and data management challenges. Internal IT departments will be stretched to store, manage and analyze this data. Cities will need to manage thousands of data points and store millions of gigabytes of data. IT demands could skyrocket in a short period of time.
But big data requirements don’t mean big problems. Cities can overcome these challenges in a few ways.
#1: Consider Managed Services
If the CIA trusts the cloud, your city can too. Consider partnering with an IoT vendor that will provide managed services. At Miovision, we employ smart engineers and data scientists but we outsource some of our data storage functions to Amazon Web Services . They can do it better. Your traffic operations department is built around traffic engineering skills, not IT skills. Focus on what you do well and leave the rest to the experts.
So, how do you vet an IoT vendor? Here are few quick ways to get a read on whether you should consider a partnership:
- They Are Experts in IoT Solutions for Cities: Vendors with a focus on solutions for cities will understand your unique needs. Cities are different than companies. You require a specialized offering.
- They Have a Demonstrated Ability to Evolve With Your Needs: Your solution should evolve with your city. Partner with a vendor that has demonstrated a capacity to innovate on a regular basis. Chances are you’ll start with a particular need, but as you build your IoT platform, you’ll want more.
- They Take Security Seriously: Security should be a top priority. Your vendor should have clear documentation on security protocol, secure backups and disaster recovery. Furthermore, a reputable cloud partner should provide a detailed security response process.
- They Do More Than Store Data. They Can Provide Actionable Intelligence: You might not need data analysis right away, but as you collect and store data, you’ll want a vendor with a solution that can provide actionable intelligence for your city.
#2 Start with Small Pilot Projects
No need to dive into a full IoT implementation. Start with a small pilot project. It will allow you to slowly develop your IT infrastructure, whether it be externally or internally.
Don’t Avoid the Future
Cities are changing, and the Internet of Things is here to stay. Tackle the future head on. Start talking IT requirements. Start planning small pilot projects. Take the MyCitySmarts survey to help assess and plan the path forward. It will make your transition to a smart city that much easier.
You can’t be a provider of advanced Intelligent Transportation Systems (ITS) solutions without being a forecaster. The world of transportation is experiencing major upheaval. From autonomous vehicles to ubiquitous traffic sensors, 2017 is shaping up to be a year of rapid change. Here’s an overview of the top seven ITS trends we expect to see in 2017.
1. States Will Invest in V2V and V2I Infrastructure
Vehicle-to-vehicle (V2V) communications is a network where automobiles send messages to each other with information about what they’re doing. Vehicle-To-Infrastructure (V2I) is the same concept, but between cars and infrastructure. States are beginning to invest in infrastructure to support the rise of autonomous vehicles. The Federal Highway Administration released its V2I Guidance in 2016. It included five basic steps for State DOTs and Owners/Operators considering V2I deployments. These steps included updating Regional ITS architecture to better integrate with connected vehicles.
Why invest in V2I? When combined with V2V, V2I deployment will help to improve safety and mobility, and reduce environmental impact. These are all important to transportation agencies.
Also, in 2015 Transportation Secretary Anthony Foxx announced legislation that would make vehicle-to-vehicle a mandatory feature of new cars. The US Department of Transportation is planning on providing up to $100 million over the next 5 years, through its Connected Vehicle pilot program, for projects that will deploy V2I technologies in real-world settings.
Connected, autonomous vehicles are coming. States and provinces need to be ready for them.
2. “Standard Production” Autonomous Vehicles Will Hit the Streets
Up until now autonomous vehicles tested on roads were concept cars. Nevada has been licensing autonomous vehicles since 2011, and in 2012 Google received the first license for an autonomous vehicle. All of those cars have been prototypes. Next year, the 2017 Mercedes-Benz E-Class will become the first “standard-production” vehicle to receive a testing license in Nevada. Other models required extra sensors or other modifications. Not the E-Class. It’s ready to go. From prototype to standard production. Driverless cars are going mainstream in 2017.
3. Sensors, Sensors Everywhere
Expect a new wave of technology to enter the market in late 2017 that significantly lowers the cost of deploying traffic sensors. It’s already happening in Chicago. They’ve just launched Array of Things, a groundbreaking urban sensing project. The plan is to install 500 nodes on city streets that can measure air quality, climate, traffic and other urban features. This technology will collect data that will help the municipality understand environmental, traffic or pedestrian trends so it can make better and safer municipal planning decisions.
We expect 2017 to be a big year for sensor deployment as lower-cost technology to track and manage traffic and other city services become available. Everything and anything can, and will be measured in cities.
4. Cities Will Get Smart About ITS Security
Many cities will tackle ITS security. As public works infrastructure begins to rely on sensor integration and data gathering as part of its operations, data security will emerge as a key concern for cities. This issue will move from a theoretical “what if” in 2016, to a practical “must have” for cities in the year ahead.
A thorough data security policy which covers how data is transmitted to and from infrastructure, where data is stored, and who has access to use it will become a critical management questions for traffic agencies. Many cities will rely on guidance from sources like Smart City IoT best-practices.
5. The Rise of Smart City Testbeds & Municipal Innovation Zones
Expect a flurry of new initiatives in 2017 related to helping cities explore ITS innovation in a faster and more effective way. While standard procurement models will still exist, we expect more smart city testbeds and municipal innovation zones in the year ahead to spur the adoption of new technologies.
Jakarta is leading the way in 2017, by allocating two pockets of its city to testbed sensors and apps to improve public services. The testbed will be used to improve street lights, parking, electricity generation and water treatment.
Luxembourg is trying to position itself as a national testbed for smart city technologies. Luxinnovation, the national agency for innovation and research, recently released a video highlighting its Smart Day initiative.
We’re developing a smart city testbed in our own backyard. Our future headquarters will be located at Catalyst137. Catalyst137 represents a Canadian testbed where local makers can gather to innovate in the Internet-of-Things (IoT) space. It will include testing facilities, commercialization services, and a hackable streetscape.
6. City Infrastructure as a Service
In the same way that many technology companies have moved to hosted “software-as-a-service” (SaaS) platforms to run their businesses, cities will start embracing “infrastructure-as-a-service” (IaaS) to help run traffic operations. For many cities, this will be driven by the desire to move away from the mindset of needing to own, host, and operate all ITS technology, which can place excessive burden on IT and transportation departments, especially for smaller traffic agencies.
Leveraging IaaS introduces agencies to fully managed and hosted services for everything from traffic signal communications to video storage and data analysis. IaaS has the potential to not only save traffic agencies money, but also empowers their traffic engineers to focus on using data to fix traffic challenges instead of coping with IT challenges of simply acquiring the data.
7. ITS, Coming to a Rural Area Near You
Historically most ITS deployments were focused on large cities with high congestion and complex traffic problems. But if the interest in the 2016 National Rural ITS Conference is any indicator, we’ll see more sophisticated ITS deployments in rural and small towns.
Smaller agencies recognize the benefit of data-driven traffic management, and want to generate better efficiencies in their maintenance and traffic operations. A new generation of ITS solutions that are both affordable and accessible to various levels of technical expertise will bring value to cities of any size in 2017.
Other ITS Trends?
Do any other intelligent transportation trends come to mind? Leave a comment below and we’ll expand our list!
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