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Making American Cities Safer for Pedestrians and Cyclists

Americans are walking or cycling to their destinations with renewed enthusiasm and frequency.

Today, approximately 50% of all trips under one mile and 10% of all trips of any length are made on foot or on bike.

However, with this increase in interest has come corresponding risk: pedestrian and cyclist injuries and fatalities have climbed steadily every year since 2009. In fact, in 2012, bicyclist and pedestrian fatalities were over 16% of all traffic-related fatalities, highly disproportionate to their numbers, and primarily in urban areas.

USDOT Calls for Safer People, Safer Streets

The rise in popularity and challenges in walking and cycling are among the key trends identified by Anthony R. Foxx, Secretary of the US Department of Traffic, in his forward-looking vision of an improved transportation system for. In the DOT’s draft of Beyond Traffic 2045, they predict a significant growth in walking and cycling in the next 30 years.

They note that metropolitan areas will burgeon and be higher density. That, combined with the Millennials’ lifestyle preferences for healthier and more environmentally sound activities, raises both opportunities and alarm.

Accommodating this simple form of transportation, and doing so safely, must become “an increasingly pressing issue for policymakers, particularly in urban areas,” the document urges.

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Towson Roundabout Data Collection by JMT Engineering

Note: This blog has been guest submitted by Clyde Munz of Johnson, Mirmiran & Thompson, Inc. (JMT).

Traffic Count Project Details

JMT was assigned with collecting traffic counts for 36 signalized intersections and one five–legged oblong roundabout – the Towson Roundabout. Of the 37 intersections, 32 of the counts had to be for a 24 hour period.

The Challenge of Roundabout Data Collection at the Towson Roundabout

towson roundabout map

The Towson Roundabout is an oblong five-legged traffic circle that brings five busy roadways together. The roundabout is approximately 200 feet along the East – West orientation and approximately 80 feet in the North – South direction.

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Turning Video into Traffic Data Part Two

In Turning Video into Traffic Data Part One, I wrote about Miovision’s systematic method for processing the large amount of video that is uploaded to our system. I detailed our three step process for video configuration, quality assurance, and data validation, and explained how computer vision is used to detect vehicle movements from video. If you haven’t yet read Part One, I would recommend you start there.

In this second-and-final post, I will be diving into the details of data accuracy, how we account for error, how we develop our best-in-class algorithm, and how that helps our customers rely on the quality of Miovision data for any project of any size.

Additional content credits to Justin Eichel, PhD, Miovision Technical Director and Computer Vision Architect, and James Barr, Miovision Product Manager.

Deconstructing a Frame of Video into Spatial Regions for Counting

When video is uploaded to Miovision, cardinal direction and number of lanes are required inputs. That is because each video is split into video segments to be processed individually.

Each video segment is determined by spatial region, lane and approach. Segments are then  distributed through a number of processes on a cloud computing service and queued for distribution to a computer vision task.

When computer vision tasks are complete, each video segment is queued for human review and verification. Humans manually count a 12% cross-section from each hour of video to ensure that the computer vision algorithm is properly producing counts and the data is accurate.

annotating an intersection

Screenshot: When the customer uploads a video to the Miovision Platform, they are required to annotate each leg of the intersection (or other road facility) and denote the camera position in relation to vehicle movements. This ensures proper configuration, and this metadata is stored with the count data and video for posterity. The annotation provided in this step is then deconstructed one step further at Miovision and made into counting tasks.

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Busy Junction at Night from Above

Turning Video into Traffic Data Part One

As of this spring, Miovision will have turned 1.5 million hours of video into traffic data from multiple video sources, including our own Scout Video Collection Unit. With daily volumes as high as 7,000 hours of video, we rely on a systematic method of combining computer vision algorithms  and human verification to ensure data reports meet our customers’ expectations.

In this two-part blog series, I’ll be writing about how Miovision turns video into traffic data with significant support from Miovision Technical Director and Computer Vision Architect Justin Eichel, PhD.

Video-Based Traffic Data Collection

For those not familiar with Miovision’s traffic data collection solution, here’s a quick overview:

  1. Customer records video: this can be of an intersection, midblock, highway count, roundabout or pedestrian and bicycle location. Video can be provided by any video source, but we recommend our best-in-class Scout video collection unit.
  2. Video is uploaded to Miovision: every customer has a cloud-based account on the Miovision Platform where they can upload video and quickly select the types and amount of data they need.
  3. Data Reports are Downloaded: the video is turned into traffic data on the Miovision Platform. Data reports are stored on the customer account and available for download in a variety of formats, along with the video recording.

three step process

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Pedestrian and Bicycle Safety Prioritized by USDOT

Last September at the Pro Walk Pro Bike Pro Place Conference in Pittsburgh, Secretary of Transportation Anthony Foxx announced that the USDOT is rolling out their “Safer People, Safer Streets” initiative over the next 18 months.

We’re looking forward to the follow-up on this ground-breaking announcement at the National Bike Summit in a couple of weeks. We hear that Secretary Foxx will also be in attendance to hopefully update on the USDOT’s Safer People, Safer Streets initiative.

Miovision is also proud to be an exhibitor at this conference. If you’re in attendance, please come by and visit us where we’ll be talking about our latest EBook, Building a Bike-Friendly Chicago, How Video Data is Moving Chicago Forward.

The USDOT plan prioritizes pedestrian and bicycle safety for all 50 states

bike friendly fatalities

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Miovision’s Traffic Signal Survey Results Infographic

Every year since 2012, Miovision has conducted a peer-driven Traffic Signal Survey. The survey measures the current state of traffic signal maintenance and operations in North America. The question categories include: traffic data collection traffic data reporting and visualization activities software and systems traffic signal connectivity

Add Right-Turn-on-Red Data to Any Intersection Count

In the United States, right-turn-on-red movements are permitted in all 50 states, DC, Puerto Rico, and Guam*. Though seemingly an important part of the operation of an intersection for the last 30-50 years, Right-Turn-On-Red data (RTORs) have not been closely considered in intersection analysis until the release of the 2010 Highway Capacity Manual (HCM). Read more

Introducing Scout 14 – Simplifying Your Data Collection Workflow

At Miovision we value your feedback and actively aim to make Scout the most intuitive data collection tool available.  It is with excitement that we release Scout 14 – our first major firmware upgrade since Scout’s launch.  Scout 14 features a redesigned interface with just three main screens to simplify each step of your workflow, letting you deploy quickly and with confidence. Read more

What Do You Need for Video Traffic Data Collection?

A video system is an effective and efficient method for traffic data collection, but what do you need to ensure data accuracy? This blog article will review the ‘must haves’ of what is important for good video data collection. If these requirements aren’t met, you might be left with poor data quality.


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Miovision Ranks #2 with 6839% Growth in the Deloitte Technology Fast 50™ Program


We are excited to announce that Miovision was named Canada’s second fastest growing technology company on Deloitte’s 2013 Technology Fast 50™, and we’re #38 for the Technology Fast 500™across North America.

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