Today’s Traffic Management Challenge
Cities, Counties, and States across the US have dated traffic management processes, limited traffic data, and fragmented technology solutions to effectively monitor traffic flow and adjust signal timing to relieve congestion.
on a Hunch
Traffic controllers review limited traffic data and manually eye-ball cameras to monitor flow across the network.
Congestion is manually detected via data feeds. Root cause and network ramifications is largely unknown.
An outdated paper-based traffic “playbook” is used to identify and deploy a course of action to relieve congestion
Analysts go through traffic camera footage and deficient performance data to determine the impact of applied action
Now, IMAGINE a traffic management center
using Mobi’s system and unlocking the grid
Traffic controllers review real-time full-spectrum traffic performance indexes across the entire network
Mobi’s system predicts congestion build-up and root cause, then alerts traffic controllers accordingly
Mobi's system issues an optimized-plan recommendation to alleviate congestion and preempt gridlock emergence
Traffic controllers receive dynamic control report, and ML algorithms continue to improve prediction & direction
From City To State Networks
Israeli Ministry of Transport (MOT) Use Case
In 2016 Mobi won a tender for a city-scale deployment of its system from Yefe Nof company, which serves as the transportation planning entity and executing arm of the MOT, Haifa municipality and the cities in Israel's northern metropolitan area. The system harnessed Mobi's IoT network to provide 24/7 mobility situational awareness, including full traffic indicator spectrum monitoring and performance index analytics at network, zone, corridor and link levels.
In Late 2018 following the successful deployment in Haifa, Mobi won a two-year, multimillion-dollar tender from the MoT to design and implement a nationwide system for data gathering, fusion and analytics utilizing its proprietary platform. Mobi, together with its telecom partners, provide the basis for all strategic transportation decisions, with the system's full spectrum of multi-modal mobility indicators being used in developing master plans and ongoing mobility performance monitoring.
Events Area Network
Atlanta Use Case
Mobi's system has been operational 24/7 in Renew Atlanta's traffic control center since late August 2017. After a rapid deployment of Mobi's IoT network in the downtown and midtown areas, and fusion of additional data sources, the system started to provide real-time actionable insights for traffic control and comprehensive analytics for action planning.
Mobi's live dashboard presents AI-powered network metrics, predictive alerts and prescriptive recommendations.
Mobi's BI system enables in-depth trend and irregularity analysis, as well as plan optimization development, with advanced statistics, machine learning and simulation tools.
Mobi's automated control reports provide event scorecards, comparative studies and lessons learned after-action review.
Since its launch, Mobi's system has been facilitating the downtown area traffic operations in over 100 events, including during Super Bowl LIII week, weekend and game day.
Port Area V2X Network
Harbor and Border Use Cases
The city of tomorrow is expected (1) to deliver on-demand flexible mobility options for individuals and for the delivery of goods; (2) to provide efficient dynamic routing guidance for all vehicle types; and (3) to employ highly dynamic optimal traffic control strategies in real time. One of the biggest obstacles cities face in this regard is the movement of trucks in the city in general, and specifically with relation to land and sea port destinations.
Preparing for the city of tomorrow, Mobi integrated V2X technology into its system, enabling 2-way communication between traffic control centers and truck fleets - enhancing traffic management capabilities by enabling discrete truck direction in terms of route and departure/arrival time, in the context of overall traffic network optimization.
Mobi's system was successfully piloted in Canada for the purpose of integrating Intelligent Border Crossing, Smart City traffic management and V2X infrastructure, with the aim of reducing wait times at border crossings and improving emergency response times.
Mobi's system was successfully piloted in Israel for the purpose of network traffic optimization - reducing both congestion and air pollution generated from truck traffic in Haifa bay, using network-based I2V management and control.
Collecting and fusing valuable data from multiple information feeds – from Mobi's IoT and V2X sensor network as well as external sources, such as anonymous and aggregated cellular signaling, GPS and App data, as well as data from cities' legacy systems.
Utilizing AI analytics on complex data structures with actionable insights – providing real-time mobility situational awareness, including performance indices, trend notifications and congestion buildup alerts.
Real-time simulation of possible solutions for emerging congestion, helping to plan preventive measures – complementing a hybrid simulation with machine learning in optimizing preemptive traffic control measures.
Turnkey solution for traffic control automation and policy implementation – Mobi's AI engine brings actionable insights to fruition in various applications, from optimizing operationalization of existing traffic control tools, to introducing novel approaches maximizing policy-oriented impact on network performance.