By Theresa Wells, Executive Advisor – Digital, GHD

Across Aotearoa New Zealand, road-controlling authorities face mounting pressure to deliver safer, more efficient transport networks with limited budgets. From urban congestion to freight bottlenecks and safety hotspots, the challenges are complex and interconnected. At GHD, we’re pioneering the use of connected vehicle data (CVD) to help authorities make evidence-based decisions that address these challenges head-on.

Beyond traditional data: A new era of evidence

Since 2019, most new vehicles have been equipped with embedded sensors capturing speed, braking patterns, acceleration and g-forces. In New Zealand, this data is provided through our partnership with Compass IoT, which integrates ERoad fleet information, significantly improving coverage of commercial vehicles – critical for understanding freight movements and overall safety risks.

This represents a fundamental shift from traditional data collection. Where authorities previously relied on intermittent manual counts or temporary sensors providing snapshots of activity, CVD offers continuous, year-round visibility across the entire network. With New Zealand’s average vehicle age declining and connectivity increasing, this data source will soon represent more of the vehicles on our roads.

Four priority applications for road controlling authorities

1. Transforming road safety through proactive intelligence: Traditional crash analysis is reactive. We learn about problems after people are injured or killed. CVD enables proactive safety management by identifying near-miss events through harsh braking, swerving and speed pattern analysis. We’re helping authorities develop monthly safety reporting that supplements crash statistics with near-miss heat maps, pinpointing emerging danger zones before crashes occur. For out‑of‑context curves, where approach speeds exceed safe levels, CVD provides precise measurements rather than conservative estimates, enabling targeted interventions without unnecessary network‑wide restrictions.
2. Optimising freight movement for economic productivity: Freight efficiency underpins New Zealand’s economic competitiveness, yet authorities have historically lacked visibility into actual movement patterns. CVD enhanced with ERoad data provides comprehensive origin–destination matrices that show where and when freight travels, and via which routes. We can analyse weighbridge avoidance patterns, revealing alternative routes used by heavy vehicles – helping authorities understand compliance issues. This intelligence enables strategic infrastructure investment in corridors that genuinely support economic activity, while addressing unexpected heavy vehicle loading on alternative routes.
3. Evidence-based infrastructure investment – balancing safety and efficiency: Road controlling authorities invest millions annually in safety treatments and traffic management solutions; yet, measuring effectiveness has been challenging. CVD enables objective before‑and‑after analysis of interventions such as speed humps, rumble strips and safety cameras. CVD enables surgical precision in targeting interventions where they’re genuinely needed, maintaining network efficiency elsewhere. For example, for the city of Geelong, in Australia, we compared driver behaviour before and after speed humps were introduced, measuring speed and g-force changes on approaches. This evidence directly informed efficacy of the interventions and whether additional or alternative safety investments were required. This data-driven approach helps to build public and industry support, while also achieving both safety and economic objectives.
4. Smart urban planning through movement intelligence: Urban planning requires understanding who uses road space and why. Traditional methods couldn’t distinguish between through‑traffic and local trips, limiting decision‑making effectiveness. CVD provides comprehensive origin–destination analysis, revealing what percentage of vehicles pass through urban areas versus those serving local needs. This intelligence is transformative for bypass planning, pedestrianisation schemes, and freight access policies. By understanding actual movement patterns rather than making assumptions, authorities can design interventions that enhance livability without unnecessarily impacting essential access.

Technical robustness and data quality

Road-controlling authorities rightly demand confidence in data quality before making significant decisions. Connected vehicle data offers a number of technical advantages:

• Sample sizes: Current penetration rates provide statistically significant samples for major corridors, with coverage improving rapidly.
• Temporal consistency: Continuous monitoring eliminates the seasonal or event-specific biases inherent in manual counting.
• Behavioural authenticity: Anonymous aggregated data captures genuine driving behaviour, not the modified behaviour seen when drivers know they’re being observed.
• Commercial vehicle coverage: ERoad integration provides exceptional heavy vehicle representation – often the most critical for planning and economic analysis.
• Privacy protection is paramount: All data is fully anonymised with identifiable information removed before analysis, ensuring regulatory compliance while maintaining analytical value.

Regional applications and national coverage

While urban areas benefit from higher data density, the integration of ERoad data enables comprehensive national freight analysis. We’ve successfully mapped freight movements across rural corridors, identifying bottlenecks affecting agricultural and forestry products. This capability is particularly valuable for regional authorities with limited traditional data‑collection resources.

For smaller centres, CVD offers cost‑effective network monitoring, enabling evidence‑based investment decisions rather than assumption‑driven planning. This democratisation of transport intelligence ensures all communities benefit from data-driven transport planning.

The path forward

CVD represents the most significant advancement in transport intelligence since the introduction of traffic signals. For road-controlling authorities, it offers an opportunity to move beyond reactive management to predictive, evidence‑based planning that optimises both safety and productivity outcomes.

As New Zealand’s connected vehicle fleet expands, authorities that embrace this technology now will establish competitive advantages in network performance, safety outcomes, and economic productivity.

At GHD, we combine deep transport planning expertise with advanced CVD analytics capabilities – translating insights into actionable recommendations.

For more information, visit ghd.com.