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Autonomous City Information Exchange

Leverage your investment in video & IoT to make your streets safer for pedestrians, less congested causing less emissions via accurate data.

Photo of Christian Kotscher
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Written by

Mobility Data from MetroTech


Problem Statement

Lack of accurate, timely data feeds congestion. Most signal-timing systems are not driven by real-time traffic measurements. Precise data is unavailable and predictive data based on historical averages, not accurate trends.

Yes, state and local governments are investing in fiber networks and deploying more sensors and cameras. But even if a single metro entity did deploy a cloud-based Internet of Things (IoT) exchange to store and analyze the data, the system would not include data from surrounding jurisdictions. The problem, then, is both lack of data and siloed data.


Connected/Autonomous Vehicles (CAVs) will require better information to increase safety and efficiency. Sensors will need to be synchronized to coordinate with mobile devices in both time and location. The type of coordination required will encompass whole ecosystems. The solution MetroTech suggests is about organizational innovation as much as technological application. The theory that unites the following solutions, some of which MetroTech already deploys, is that many sensors will need to be integrated across multiple systems. Wireless, cloud computing, IoT, Big Data, etc., will all have to be incorporated into the infrastructure to keep up with the hyper-evolving CAV industry.

1) Leverage Existing Infrastructure for Better Signal Timing

To date roadside video is used to see what happened, not help predict what will happen. Santa Clara County (CA) has over 500 cameras producing more than 700 Terabytes of video daily. The MetroTech RTT server analyzes the video, producing real-time traffic counts and speeds to change signal-timing patterns.

2) Traffic Safety Alerts

The start of congestion after an accident, or a hazard like a wrong-way driver, is best captured and measured by sensors in the infrastructure. MetroTech has deployed pilots where existing cameras were used for identifying suspected wrong-way drivers. The data were processed to avoid false alarms, confirmed wrong-way drivers tracked by other nearby cameras, and safety alerts sent to connected vehicles and apps to warn drivers or autonomous vehicles. Following the example of Amber Alert, MetroTech’s solution could broadcast wrong-way driver alerts, road closures, evacuation instructions, and other information to mobile devices or connected vehicles in an affected area.

3) The Digital Streets Platform (DSP)

MetroTech’s DSP, functioning regionally, will ingest IoT data from multiple infrastructure owners through a transparent information exchange. The sensor data will be normalized and analyzed before being broadcast over various networks to both drivers and autonomous vehicles as maps or as dashboards that can depict lane-level volume, speed, and headway. The network types include V2X, CV2X, and Satellite.

4) The Autonomous City Safety Network (ACSN)

The ACSN is the suggested name for a nationwide network that would take information from exchanges, such as the Digital Streets Platform, and put it into a standard that all CAVs could access, allowing vehicle makers and app developers to share data.

5) CAV Data Subscriptions

CAVs, smart fleets, and apps will be enhanced by subscribing to infrastructure data. Audi already has a type of subscription service that allows their connected cars to communicate with infrastructure.[1]


6) Pedestrian Safety


CAVs have blind spots that infrastructure could illuminate. Let CAVs navigate with assistance from infrastructure. MetroTech’s pedestrian safety solution uses LiDAR (Light Detection and Ranging) sensors to pinpoint pedestrians to a 10-centimeter accuracy 10 times per second. A pedestrian’s path is followed as an object and their predicted path is then converted into exact GPS coordinates. The information is then sent to devices on vehicles five times per second, using the US DOT’s V2X standard on a 5.9GHz local network.






The emerging era of connected and autonomous driving will demand accurate, real-time information that cannot be estimated from GPS probes. Life-saving applications and greater harmonized driving will require that the “Autonomous City” can communicate with pedestrians and vehicles moving around its streets.








Describe who will use your solution (1,000 characters)

Safety around modal junctions will be greatly enhanced when pedestrians can be measured by the infrastructure and their location sent to buses and cars to prevent accidents. The enhanced safety will give the public a greater comfort with the adoption of Autonomous Vehicles which will reduce the price of transportation and increase the access for many undeserved and physically challenged. Drivers will also benefit due to the real-time and accurate nature of Smarter City data that will be fed directly to their vehicles via V2X, Satellite, and 5G. Cities and local governments will be able to organize this information in the cloud at a region level to make the sum of their data useful for investment by Connected / Autonomous / Sharing / Fleet mobility customers. More accurate and real-time data will lead to less congestion, less pollution, and will lead to the reduction of transportation costs for all modes that us our roads and sidewalks.

Describe your solution's stage of development

  • Ready to Scale - you have completed and expanded your pilot and are seeing adoption of your solution by your intended user

Insights from previous testing (500 characters)

Location technology and IoT via various wireless networks will be in important part of the Autonomous City. This is where Smarter City investments meet the information demands of the mobility world. Smarter Cars will need smarter data from Smarter Cities. The eventual goal being Autonomous Vehicles speaking in real-time with Autonomous Cities to enhance safety and mobility. After the first pilot with LiDAR we discover that many Video and IoT sensors could be used to enhance safety.

Tell us about your team or organization (500 characters)

MetroTech has been in startup mode for a few years performing first of a kind projects around Machine Vision, Machine Learning, LiDAR, Wireless, Cloud, & Big Data. Our team is virtual and has created and deployed innovative solutions from Miami to Silicon Valley. The technical team develops and supports pilots from around the US and Europe ranging from developer to delivery. The CEO has worked in Smarter City since he owned the solution for IBM Globally in its early days.

Size of your team or organization

  • 2-10

Funding Request

  • $100,000

Rough Budget (500 characters)

For $100K MetroTech will deploy our Digital Streets Platform that ingests video and IoT to create a better information network for signal timing, commuter information, safety alerts, and pedestrian protection. This would include the temporary deployment of LiDAR system in a single intersection, and up to 100 cameras and 200 sensors into the cloud based system for sharing with V2X and 5G pilot vehicles.

Describe how you would pilot your idea (1000 characters)

The system has already been deployed or piloted for advanced signal timing and pedestrian safety. Next phase is integrating to Ford and other mobility companies' vehicles for safety and mobility applications such as navigation, wrong way driver alerts, traffic jam alerts, and pedestrian safety.

Describe how you would measure the success of your pilot (1000 characters)

Silicon Valley saw a $42M ROI over 5 years when utilizing their existing video cameras to create real-time traffic information for adaptive signal timing. THEA in Tampa used the LiDAR to V2X solution to prove out the technology for national usage in the US DOT Connected Vehicle Test-bed. The pilot would be successful if we could prevent the first accident between a vehicle and a pedestrian via fixed Smarter City sensors. The pilot would also show promise if real-time and accurate traffic and safety information for Fleets, Sharing, Connected and Autonomous Vehicles.

Sustainability Plan (500 characters)

As Safety becomes a larger topic for the public adoption of Autonomous Vehicles, these types of additional "eyes" will help make a safer drive for vehicles and pedestrians. Many types of information from Smarter City will be valuable to the mobility world, but many public transportation agencies do not have the resources to organize analyze, host, and broadcast to OEMs, Tier1s, Telcos, and other mobility players. This information will create a revenue stream to enhance safety & mobility.


Join the conversation:

Photo of Madhan K

Hi Christian, does your solution work on computer vision?

Photo of Christian Kotscher

yes, and Machine Learning, Radar, and LiDAR.