Advancing Mobility With Data – Part 2: Asset Management

Asset management is becoming an instrumental part of the transportation industry as the success of intelligent transportation systems (ITS) and maintaining roadway infrastructure is dependent on the condition of its assets.  

It’s crucial to have access to detailed and accurate information about the condition of various assets for optimal asset management. Traditionally, obtaining insights about the condition of assets such as bridges, roads, and traffic signs have been through human inspection, often involving manual processes such as paper and pen documentation. However, this method is not only time-consuming but prone to errors and delays. This is where connected autonomous vehicle (CAV) data comes in.

Through a combination of on-vehicle video and sensors, the ability to quickly identify assets in specific corridors and arterials is made possible. A baseline of assets can be quickly established, and with regular feeds of data, it’s possible to identify what has changed. By leveraging this data, transportation agencies can prioritize and plan maintenance and repairs more effectively, ensuring that resources are allocated where they are needed most.

Some of the more prevalent assets that can be monitored through connected autonomous vehicles are:

• Road Signs: A baseline of road signs in a designated corridor can be established. Regular vehicle data feeds will help roadway maintenance teams identify the condition of road signs, especially missing or damaged signs. This data can be utilized to initiate prompt action.
• Road Striping: Clear road striping is essential for both human drivers and autonomous vehicles relying on lane-keeping assistance systems (LKAS). Sensors measure reflectivity levels ensuring visibility under various lighting conditions; this ensures timely repainting when necessary.
• Monitoring Guard Rails: Guard rails are critical safety features that prevent vehicles from veering off the road. CAV sensors can detect damage to guard rails caused by collisions or wear and tear. This data facilitates quicker identification of damage, enabling more timely action.
• Detecting Potholes: Sensors on CAVs can identify potholes and their size based on changes in vehicle dynamics, such as sudden jolts or vibrations. Accurate location data allows maintenance crews to prioritize repairs effectively.

improved Work Order Maintenance

The integration of CAV data with work order maintenance systems also revolutionizes asset management by enabling automated notifications and more proactive maintenance strategies. For instance, using asset data, transportation agencies can develop predictive maintenance schedules to prevent asset failures, reduce long-term maintenance costs, and improve roadway safety.

With the rise of artificial intelligence and machine learning, it’s possible to see a future state where the CAV data collected will lead to:

• Geospatial Analysis: By analyzing the location data of identified issues, the system determines clusters of assets within specific geofenced areas.
• Optimal Routing: The system calculates optimal routes for maintenance crews, minimizing travel time and maximizing productivity.
• Batch Processing: Assets within close proximity are grouped together for simultaneous maintenance activities, reducing operational costs and downtime.
• Resource Allocation: Efficient grouping allows for better allocation of resources such as materials and labor force required at each site.

Data Management Platform

Data is more powerful when aggregated and accessible from a “single pane of glass” platform, like our advanced transportation management platform, iNET^®. It’s one place where users access all the data needed to manage assets, optimize operations, and collaborate with vendors and team members. By integrating data from multiple sources and leveraging artificial intelligence and machine learning, iNET^® helps improve the management, efficiency, effectiveness, and safety of transportation networks big or small. 

Driving Asset Management

The integration of CAV data into asset management marks a significant advancement in the transportation industry. This shift not only enhances the ability to monitor and maintain critical road assets, but also enables proactive and predictive maintenance strategies, delivering smarter, safer, and more cost-effective solutions for maintaining our vital infrastructure.