hiedi

About Hiedi Carman

This author has not yet filled in any details.
So far Hiedi Carman has created 7 blog entries.

How to Procure and Use Connected Vehicle Data eBook

By |May 10th, 2022|

Tens of millions of dollars in infrastructure investments are often based on sparse information about how the road network is actually used. This is changing quickly as data from connected vehicles (CVs) provides detailed information on the use of our road networks that was never before available .

Turning billions of CV records into actionable information for transportation engineers, however, can be very challenging. This work requires advanced data processing skills, specialized software, and significant server resources. Many purchased data sets remain unused after agencies and consultants run into data processing roadblocks.

Moonshadow has processed over three trillion CV waypoints from many sources for […]

Corridor of the Month

By |May 2nd, 2022|

Introducing Arterial Insights a product by DKS Associates and Moonshadow Mobile: an online tool to analyze the performance of traffic corridors and signalized intersections, using connected vehicle data from tens of millions of vehicles.  Arterial Insights is available in the US, Canada and Europe.

Please sign up here for the Corridor of the Month. You will receive access to a first hand demonstration of how Arterial Insights can assist you with corridor analysis. Generate travel times, speeds and delays for any segment in the corridor. Check arrivals on green and red for any intersection for any time period of any given day.

Arterial Insights is provided […]

Introducing Arterial Insights

By |May 12th, 2021|

DKS Associates and Moonshadow Mobile are introducing Arterial Insights: an online tool to measure the performance of traffic corridors and signalized intersections using connected vehicle (CV) data from tens of millions of vehicles.

Fig. 1. Segment Travel Times per Hour in Arterial Insights

It can be time consuming and expensive to measure the efficiency of a signal timing plan for a corridor for example.  Up to now travel times, speeds and delays were measured by installing equipment at intersections, or by performing ‘floating car runs’.  Maintaining yet another group of devices in the field can be challenging and expensive whereas floating car […]

DB4IoT with INRIX for transportation emission analysis

By |May 10th, 2021|

The Eastern Research Group (ERG) studied the usefulness of using vehicle telematics data to create vehicle emission inventories. The study has been published by the Coordinated Research Council, Inc (CRC).

ERG surveyed several data sets and analytics platforms and vetted them before embarking on a more detailed study. They selected three sources, these included Moonshadow Mobile’s DB4IoT Platform with INRIX data, StreetLight Data’s Insight platform and Otonomo data.

Data from StreetLight were used to estimate total Vehicle Miles Traveled (VMT) within their study area. The study area was the 10-county Denver metro area. ERG verified StreetLight algorithm for scaling up telematics […]

How Connected Vehicle Data can be used to Save Lives

By |May 10th, 2021|

Charlie Henry at Model shift wrote and excellent blog on how Connected Vehicle Data can be used to Save Lives. He used connected vehicle data in San Antonio as part of a project with the Texas Department of Transportation.

Moonshadow’s DB4IoT Mobility Analytics Platform was used to ingest and visualize the vast amount of data.

Read more on Charlie’s blog: http://modalshift.co/HardBraking/

How Connected Vehicle Data is Changing Transportation Analytics

By |January 28th, 2021|

Watch the presentation

Our CEO, Eimar Boesjes, was invited by Prof. David Hurwitz at Oregon State University to give a guest lecture in Hurwitz’ Masters of Transportation Engineering program.  This 50 minute video gives an overview of the current state of the art in using connected vehicle data for transportation analytics.  In a quick pace Eimar covers how data is collected, the different types of data as well as the transportation analytics supported by each.  High-frequency connected vehicle data, for instance, can be used for safety analytics but Location Based Services (LBS) data from mobile apps does not have a high […]