Redefining private sector investment in transportation

Traffic management is evolving, and the public sector is working hard to adapt. Advanced technologies like artificial intelligence (AI) are changing the game, and success requires a thoughtful implementation strategy. 

To that end, the private sector should be investing to meet agency needs. At a recent workshop hosted by Google and transportation professional services firm WSP,  industry experts and government leaders from the Department of Transportation, Federal Highway Administration, rail agencies and various state departments of transportation, gathered to discuss the opportunities and challenges in this space. 

The roundtable brought together the minds of Google's Public Sector, Research and Geo arms to discuss public sector safety and resiliency challenges, in collaboration with WSP.

Key challenges: Innovation without sacrificing agency goals 

Representatives from the public sector highlighted the current challenges that private sector investment can help them to overcome:

• Security vs. innovation: There is a significant tension between centralized IT departments, who are focused on preventing risk and ensuring security, and operational teams who want to develop mission-critical use cases. Strict compliance can lead to paralysis for operational teams trying to innovate.

• Fear-driven policy: Concerns over cybersecurity and a lack of transparency in industry solutions often lead to restrictive policies.

• Hallucination and risk: There is a concern that over-reliance on AI could lead to a loss of engineering judgment — accepting a result just because a prompt said so. AI can hallucinate, making prompt engineering and training is so critical to insight review. 

Proactive traffic management

WSP offered an overview of current traffic management systems since they manage some of the largest in the country, and overviewed their predictions of the future. In this vision, agencies will leverage AI to be more proactive, shifting from reacting to crashes, to predicting and preventing them.

What would proactive management look like? Pat McGowan, WSP’s senior vice president and mobility operations director in the U.S., pointed to some likely use cases that would leverage Google’s data to move from incident response to prevention:

• Predictive alerting and preventing crashes: By analyzing Google’s data from two minutes before a crash, WSP seeks to understand if there could be specific “signatures” or triggers of an incident, enabling preventative alerts to vehicles or roadway signs.

• Optimized work zone construction: Using advanced analytics, agencies can determine whether extending a lane closure by just 30 minutes could finish a construction project months earlier.

• Dynamic special event planning: While local sports events have predictable traffic patterns, global events like FIFA or the Olympics involve drastic shifts. WSP is investigating how using Google’s demographic and zip code data can better predict these unique traffic origins and patterns.

How Google and big tech can underpin the mission

Eric Peissel, WSP’s global director for transport and infrastructure,  Kristin White, Google Public Sector’s transportation industry executive, and Andrew Stober, head of public sector partnerships for Google Geo, described how Google is actively sharing geospatial data with transportation agencies to drive impact. Examples include Road Management Insights (RMI), which provides travel time and speed data between user-defined origins and destinations, ranging from a few hundred feet to many miles.

Unlike anonymous cell phone data, Google’s insights come from 2 billion monthly active users and 250 million Android Auto users who are actively navigating, ensuring high certainty that the data reflects actual driving behavior. It’s the lowest-latency, highest-speed data on the market to hep public agencies meet their goals.

Speakers also detailed a range of capabilities set to come online in 2026.

These include vehicle counts: Google will provide hourly traffic counts for non-residential segments with a two- to three-day lag. There’s also hard braking data, derived from actual vehicle sensors via Android Auto. This high-certainty dataset identifies safety “signatures” and near-misses, avoiding the “noise” associated with older accelerometer-based phone data.

A free traffic signal optimization program, Project Greenlight, models cycle times and phases to suggest improvements in signal coordination, aiming to reduce emissions. And later in the year, Google plans to commercialize intersection data, allowing agencies to query specific locations for accurate operational statistics.

The path forward: Strategies for advancing innovation

How can agencies best move ahead? Participants shared successful approaches.

For public agencies, an understanding of technical considerations can help show how this vision comes to life. For example, data can be delivered via BigQuery tables, with the computational power of Google Cloud and the domain expertise of firms like WSP helping to transform raw data into actionable transportation solutions.

Agencies need a high-level champion to sponsor technology innovation and make bold decisions that allow for innovation. And they should be building technical literacy within senior leadership and staff, including governors, secretaries, and business managers.

Data governance plans are key: Data needs to be kept in one spot and not siloed. And a “sandbox” approach can help to create safe environments for experimentation, allowing staff to gain hands-on experience and proving the value of new tools before full-scale deployment.

Moreover, participants pointed to key ambitions for the next five to 10 years, including:

• Parking and curb space management: It’s important to know parking space availability to avoid tickets.

• Infrastructure optimization: Maximizing coverage with AI and software solutions while limiting new physical infrastructure development.

• Safety applications: Reducing the time for crash data to reach nearby vehicles from minutes to seconds.

• Data standardization: Developing global standards similar to General Transit Feed Specification (GTFS) for broader transportation data sets.

As agencies look to advance transportation, collaboration between public agencies and industry experts like WSP and Google can lead to tools that ensure data security. With private sector investments in support of public sector operational outcomes, the ultimate goal is to achieve “safe mobility” and maximize the efficiency of transportation systems, without sacrificing safety.

Learn more about how Google for Transportation is optimizing the citizen journey.