Mobile network strategy helps public agencies and private operators plan for a transportation future that is increasingly multimodal, connected, and automated. Rather than focusing on a single mode, it looks at how rail, bus, micromobility, shared vehicles, autonomous vehicles, and emerging services fit together to move people efficiently and safely across a region. Engagements often include scenario planning, policy development, safety framework design for new technologies, and operational readiness assessments. 

The goal isn’t to predict exactly which technologies will win, it’s to help clients build flexible plans, governance structures, and safety cases that can adapt as the mobility landscape changes over the next five to fifteen years.

Autonomous vehicle safety spans vehicle-level engineering, system-level validation, and operational deployment. On the vehicle side, standards like UL 4600 address safety cases for fully autonomous systems, while NHTSA provides federal guidance on testing and deployment. 

At the operational level, agencies must consider interactions with pedestrians, cyclists, transit vehicles, and emergency responders, as well as how AVs behave in work zones, inclement weather, and complex urban environments. 

Data sharing, incident reporting, and cybersecurity are equally important. Agencies piloting autonomous shuttles or partnering with AV operators should define clear safety performance metrics, incident thresholds, and ongoing oversight, treating AVs as evolving systems rather than finished products.

An operating hazard assessment systematically identifies what could go wrong during the normal operation of a transportation system, a new rail line, a bus rapid transit corridor, an autonomous shuttle pilot, and evaluates how likely and severe each hazard would be. 

Assessors look at vehicle-infrastructure interfaces, maintenance activities, emergency response, and interactions with other system users. These assessments are typically required during safety certification of new projects, after major service changes, or when introducing new technology onto existing infrastructure. The output is a prioritized hazard log with recommended mitigations, supporting the broader SMS process and giving operators confidence that known risks have been identified and controlled before service begins.

Effective CAV planning combines policy, infrastructure, data, and workforce considerations. On policy, agencies update procurement, permitting, and liability frameworks so they can engage with AV operators without inadvertently locking in outdated assumptions. On infrastructure, they assess whether lane markings, signage, signal timing, and communications networks are ready to support connected vehicles. 

Data strategy matters because CAVs generate, and depend on, enormous volumes of operational and safety data that must be shared responsibly. Workforce planning is often overlooked: agencies need staff who can evaluate safety cases, interpret AV data, and oversee hybrid fleets. The best plans are modular so they can evolve as technology, regulation, and public expectations mature.