Using Transportation Data for Operations and Safety

By improved communication and information sharing, security and transportation can both gain. An operations command center (OCC) for safety and security and a traffic management center (TMC) for transportation both operate in very similar ways. While reacting to incidents, they follow a similar pattern:

The cornerstone of any operation is gathering crucial data to use in deploying the right response and countermeasures, which is at the heart of a sophisticated and inventive solution. It’s critical to comprehend how, in a smart city, we might use transportation data sets or a trip calculator cost to assist our colleagues in safety and security.
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The data sets from a TMC, which are accessible to most cities, can be gathered and shared in the ways shown below to assist the operations of the city as a whole as well as its safety and security. It will be assumed that every city, town, and incorporated or unincorporated region has worries about safety and security and wants to boost mobility to ease traffic and enhance the environment.

assisting with operations and safety
With the introduction of fully functional edge devices with artificial intelligence (AI) and machine learning (ML) capabilities, cities will become even more of a data treasure trove.
Any operation starts with gathering crucial information so that the right response and defenses can be put in place.

Since operations have an ethernet or passive optical network (PON) through fiber connecting cloud services and/or local server-based data, TMCs are essential to a city’s data interchange. Traffic lights, work zones, smart lighting, closed-circuit television (CCTV) and license plate reader (LPR) cameras with AI/ML capabilities, mobile devices, transit, fleet, and freight systems, and autonomous/connected cars are just a few of the sources of data that they ingest (CAVs). Original Equipment Manufacturers (OEMs) and Morgan Stanley predict that CAVs will produce up to 40 terabytes of data every hour.

The number of vehicles on the roadway network, their efficiency in moving (or not moving), basic safety messages from the CAVs (such as braking, acceleration, and windshield wiper activation), the type, make, and model of the vehicles, and their license plate, the number and type of pedestrians on sidewalks and in crosswalks, the concentration of people and their activities, and the location of transit, fleet, freight, and transportation can all be determined from these fundamental sources. We regularly come across these data sets, which are a resource for a city.

When used effectively, this information can give communities a variety of advantages in terms of operations, safety, and security.

The biggest ability of TMCs and OCCs in a reactive model is the capacity to identify and minimize a delay or identify and address an event. Getting precise data as soon as possible can help investigations be completed more swiftly, such as those into car accidents. Being able to foresee incidents or recognize circumstances that have a high propensity to cause an incident is fundamental to the proactive model of a smart city.

Take the example of tourists visiting a city for a holiday or a special event as we start to see more people returning to cities as the COVID-19 pandemic enters a new phase. According to transportation data, more automobiles are entering and being seen in the city’s central business district (CBD). This is indicated by sensor data and data from third parties (such as Google, Waze, Tom-Tom, HERE) showing an increase in vehicle traffic, and it is corroborated by CCTV cameras on approaches to the CBD that do not use analytics.

In this illustration, analytics from pedestrian CCTV cameras in the CBD indicate a simultaneous 50% increase in foot activity on sidewalks and crosswalks. Smart traffic signals confirm that throughput is lower as a result of the higher traffic loads from both vehicles and pedestrians. This combination is a leading predictor of three potential occurrences: vehicle accidents (rear-end collisions), which may result in road rage; petty theft as a result of closer encounters between pedestrians; and disturbances of large gatherings, which may result in violence, robbery, and damage to public property.

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A proactive model enables two events. Secondly, by influencing traffic through phase changes in traffic signals to promote greater traffic flow and platooning, the TMC may make efficient use of municipal streets. Congestion information from TMC operators can be shared with third-party applications, enabling more and safer pedestrian crossings. Second, the TMC may notify law enforcement of increased traffic and pedestrian activity, allowing them to dispatch extra officers and security guards to both prevent criminal conduct and respond quickly to any events that do occur.

With a reactive model, strong cooperation between the TMC and law enforcement can aid in tracking the vehicles or people involved in events, giving investigators real-time data information, descriptions, and proof. Investigations will be more effective by giving actual evidence if law enforcement is given access to CCTV and LPR cameras as well as toll tags to track vehicle type, color, and movement.

A few American cities, such as Las Vegas, Nevada; Salt Lake City, Utah; and Detroit, Michigan, are beginning to push advanced analytics and predictive modeling. Several of these implement and refine these capabilities using specialized software and algorithms as well as operating experience.

TMCs and transportation data can offer both historical and real-time support for investigations and preventive monitoring. TMCs and OCCs can proactively collaborate to prevent and discourage crime as well as offer access to information to enable more effective criminal investigations by integrating seamless Smart City technology, as stated above, with suitable broadband communications.

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