What Are The Technical Considerations for A Modern Advanced Traffic Management System (ATMS)?

In a previous blog, we covered the basics of Advanced Traffic Management Systems (ATMS), the core components behind them, and the benefits they deliver for incident management in traffic systems and urban planning. In this post, we will dive deeper into the technical considerations and deployment challenges of an ATMS solution for urban roads. Specifically, we will discuss how traffic management system software and hardware can be architected for maximum efficiency and optimization.

An ATMS Solution for Urban Roads: Key Requirements

A flexible, secure streaming platform is the essential backbone of an ATMS solution for urban roads. It must be capable of handling the vast variety of camera inputs and devices. This platform must ingest diverse video streams, including legacy formats prevalent in public sector deployments such as RTSP, RTMP, and MPEG-TS, while also supporting modern secure standards like SRT and WebRTC.

As a universal protocol bridge, this monitoring and surveillance infrastructure transforms ingested feeds into standardized, low-latency streams suitable for various endpoints, including:

• Centralized ATMS dashboards
• Specialized AI/ML models
• Video management systems (VMS)
• Public traveler information systems (using protocols like HLS and DASH)

This allows departments to preserve legacy investments and avoid costly system rearchitecture. With a protocol-agnostic streaming engine, Departments of Transportation (DoTs) can significantly extend the usable life of older camera hardware. The system’s intelligence is added as a software layer on top of the ingested stream, upgrading the camera’s functionality without costly “rip and replace” hardware upgrades. This maximizes the potential lifespan of existing capital investments.

Technical Requirements & Outcomes of ATMS Solutions

The resilience and reliability of this infrastructure are not optional features. Public sector organizations need solutions they can trust will perform, even under immense load. Video data is often evidentiary, and required for audit logging or chain-of-custody verification during incident review. As such, the streaming backbone must support high-availability and failover patterns. This ensures continuous operations and prevents the loss of real-time visibility during critical incident management in traffic systems scenarios.

The technical requirements, rationales, and outcomes for reliable advanced traffic management systems include:

How Edge Computing Can Add Intelligence and Efficiency in ATMS Deployments

The primary goal of ATMS is the proactive minimization of risk. The integration of AI models into advanced traffic management systems is becoming a more commonplace method of achieving this goal. Strategic decisions regarding where the video data is processed can optimize efficiency, maintain security, and help overcome ATMS deployment challenges.

Adding Intelligence to Legacy Hardware Using Edge Computing

Processing the massive volume of high-resolution video data required by ATMS creates significant latency and bandwidth issues when relying solely on distant cloud resources. Edge computing, which can involve deploying specialized AI models directly at the point of video ingest, resolves these dual challenges. It can also transform passive surveillance feeds into proactive monitoring systems without requiring extensive hardware overhauls.

AI-driven object detection provides immediate situational awareness, enabling the system to identify traffic anomalies, stalled vehicles, or debris significantly faster than human operators or traditional sensors. The speed of detection is directly correlated to the system’s ability to mitigate secondary crashes, a critical safety metric. The streaming platform acts as the core foundation for on-device intelligence. It should offer “Bring Your Own Model” (BYOM) flexibility, which allows agencies to integrate proprietary or specialized capabilities. This could include AI-powered object tracking, scene detection, trend analysis, or predictions.

Building Trust in Smart City Infrastructure with Edge Intelligence

Implementing automated, objective video analytics at the edge also improves public trust in smart city traffic infrastructure. Automated responses based on immediate, locally-processed data provide verifiable records that justify automated intervention. This mitigates public resistance to widespread surveillance technologies and shifts system operation away from manual human monitoring.

Through the integrated ATMS control center, real-time data facilitates the dynamic deployment of incident management in traffic systems strategies, such as Dynamic Rerouting, Queue Warnings, and Variable Speed Limits. These help inform motorists well in advance of a hazard and preserve road safety. This comprehensive system seamlessly integrates Closed Circuit Television (CCTV) surveillance, Advanced Traveler Information Systems (ATIS), and changeable message signs. This helps manage both recurring daily congestion and non-recurring events, such as large-scale or special events.

Maintaining Security & Compliance for Low-Latency Traffic Monitoring Systems

Public sector operations demand solutions that conform to stringent security environments. A robust streaming platform must support a full spectrum of deployment models, including cloud-agnostic, private cloud, hybrid, on-prem, and air-gapped networks. This architectural choice enhances data security and privacy. It dramatically reduces the need to transmit sensitive video streams over external, high-traffic networks for analysis. This simplifies compliance, particularly for strict mandates like air-gapped deployments. Only then can they confidently meet and maintain compliance with regulatory mandates.

ATMS, being an interconnected system of IoT devices, is susceptible to digital risks, including software vulnerabilities, malware, and logical attacks. Therefore, the infrastructure must be battle-tested, offering built-in high-availability and failover patterns, coupled with rapid security patch cadences and extensive observability tools. This combination is essential for preemptively identifying and resolving issues quickly, ensuring continuous, secure operation and system integrity. Moreover, the fundamental infrastructure supporting low latency and protocol bridging is strategically positioned to serve as the ingestion and distribution point for the high-volume, real-time data exchange. This is a critical requirement for autonomous fleets and Vehicle-to-Everything (V2X) communication, ensuring the city is prepared for the next generation of mobility infrastructure.

Advanced Traffic Management System (ATMS) Implementation Strategy and Real-World Outcomes

Despite the overwhelming benefits, ATMS deployments can be complex. One of the primary ATMS deployment challenges is the integration of proprietary, outdated, or legacy hardware (such as older cameras and controllers) with modern software. Successful implementation requires partnering with platforms that offer open architecture and specialized capabilities. This foundational backbone will seamlessly bridge protocols and ensure interoperability.

The system’s reliance on low-latency data makes data reliability paramount. A single failing sensor or glitch in the data processing software can lead to incorrect, potentially chaotic, traffic management decisions. Therefore, deployment strategies must incorporate sophisticated observability solutions to ensure data integrity and preemptively prevent the system from acting on faulty sensor readings. This includes webhooks and other confidence monitoring tools. The system’s tangible benefits can be quantified by improvements in safety and travel time rather than purely on surveillance capabilities.

Case In Point: Mississippi Department of Transportation (MDOT)

The Mississippi Department of Transportation (MDOT) built an in-house, automated system utilizing a resilient streaming platform to manage its extensive network of over 1,500 traffic and signals management cameras. This investment yielded substantial, verifiable returns.

By automating monitoring and troubleshooting, MDOT saw massive efficiency gains. They also dramatically reduced the team’s burden. Time spent on manual camera management plummeted from approximately 50% to less than 1%. This allowed engineering resources to be redirected toward higher-value projects.

From a capital planning perspective, the optimized traffic flow achieved through intelligent signal management provided significant cost savings by helping the department avoid the need for building additional road lanes. What would have been a major, multi-million dollar capital expenditure was avoided entirely.

Finally, the automated system delivered essential operational resilience. MDOT maintained centralized control and continuous, effective operation even if they faced significant staff reductions.

MDOT saw the following outcomes from this strategy:

• Massive Efficiency Gains: Cut manual camera management time from 50% to less than 1%
• Significant Cost Savings: Avoided costly road expansions by shifting from a reactive road design based on observed congestion to a proactive optimization approach using automated signal testing
• Operational Control: Centralized management and control of over 1,500 cameras via a highly-configurable API

Building ATMS and Smart City Traffic Infrastructure with Wowza Streaming Engine

The transition to Smart City mobility is not merely a software update; it is an infrastructure modernization project. True urban intelligence relies on a foundational media platform capable of addressing the immense volume, protocol diversity, and ultra-low latency demands of video-as-a-sensor data.

Agencies must prioritize solutions that offer three critical capabilities:

1. Unparalleled deployment flexibility (supporting hybrid, on-prem, and air-gapped environments)
2. Mission-critical reliability (with failover and high availability)
3. Integrated on-device intelligence (with BYOM flexibility)

Wowza Streaming Engine can transform existing surveillance assets into intelligent, proactive monitoring systems built on a secure, resilient streaming backbone. Urban Planners and Departments of Transportation can ensure they have an extensible, compliant, and future-proof path to integrating the next wave of ITS innovations. If you are interested in learning how Wowza Streaming Engine can power your advanced traffic management system, get in touch with us today.