NEXCO HIGHWAY SOLUTIONS OF AMERICA INC.
- A Subsidiary of NEXCO-Central
UPDATES
NHSA Newsletter
Current Edition: Volume 24
SPM Story | How We Identified the Values of SPM
In the initial meeting with clients, we highlight our experience as a roadway operator in Japan for over 60 years. NEXCO started the construction of the major highway system in 1956 and has tackled the challenges that Public Works faces every day. One of the most critical areas as a roadway operator is ensuring the budget to maintain the service level and meet public expectations.
Our marketing research in the development phase illustrated that Public Works departments in the United States face the same challenges as we do.
As roadway operators, we know ongoing issues and problems at the sites very well. However, it is sometimes not easy to present the facts to decision-makers.
Therefore, we developed our Smart Pavement Management (SPM) to provide the following critical points.
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Easy to Understand - Intuitive Output through the Colored Map
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Whole Picture - Quality Data Collecting as a Snapshot
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Supporting Facts - Assessment Results on Every 33-foot with Pictures
SPM provides a balanced output between simplicity and detailed data. Engineering insights will be limited if the output is too simple, and vice versa. Again, we know the balance should be depending on our experiences.
In conclusion, we are on the same page and here to help you make your job easier.
Please allow us 15 minutes to explain more details. We will offer a 5-mile free trial run during the meeting.
Just email our sales manager, Cate Hansen, to schedule your meeting!
Other Articles
Volume 1: Optimizing Pavement Management Costs
Volume 2: Ranking Pavement Condition
Volume 3: Keeping Everyone Informed
Volume 5: Beat The Heat! GIS Map Modes
Volume 6: GIS Predictive Slider Tool
Volume 7: Addressing Individual Resident Concerns
Volume 8: SPM-IRI
Volume 9: Measuring Repair Output
Volume 10: Ratings and Repair Methods
Volume 11: Winter Storm Impacts Pavement Deterioration
Volume 12: Smoothness Starts With A Survey
Volume 14: Enhancing Efficiency with Budget Simulation
Volume 15: Capture the Consequences of Extreme Weather
Volume 16: 4A Values with AI-based Pavement Assessment
Volume 17: GIS Tips - Get to the Point with Point Mode
Volume 20: GIS Tips: Power of the Visual Data Analysis
Volume 21: SPM Tips | Data Integration with Custom GIS
Volume 22: SPM Tips | Find and Showcase the Data Trend
Volume 23: SPM Tips | A Snapshot of the Roadway System
Commercial Projects
Updated November 2024
Texas
City of Anna
City of Bridgeport
City of Plano
City of Roanoke
City of Carrollton
City of Hamilton
City of Hutchins
City of Irving
City of Sachse
City of Terrell
City of The Colony
City of Whitesboro
City of Wilmer
City of Crowley
City of Commerce
City of Huntington
City of Lucas
City of Wichita Falls
City of McLendon-Chisholm
City of Joshua
City of Merkel
City of Heath
Oklahoma
City of Ardmore
City of Piedmont
And more...
Free Trial Run Project
Since SPM is a cutting-edge solution powered by the latest AI technology, a free trial run project would be necessary to better understand the benefits and values.
At the moment, more than 40 cities in North Texas and Oklahoma have commenced pilot projects.
Please contact us right now, to enjoy the opportunity.
What's New
SPM-PCI
SPM-PCI is NEXCO’s proprietary index system. Like Pavement Condition Index (PCI) using the ASTM 6433 standard, it is a numerical index between 0 and 100, which indicates the general condition of the surveyed pavement. SPM-PCI has a statistically significant correlation with PCI.
SPM-IRI
SPM-IRI is a simplified readability index leveraged by machine-learning technology. Based on the bump data recorded while data collection, NEXCO's provides a roughness index.
Deterioration Prediction
Using a standard deterioration curve, SPM provides a prediction of future pavement conditions as an add-on feature of SPM-PCI.
Budget Simulation and Repair Planning
Based on SPM-PCI and the predictive feature, our algorithm automatically offers a simulation of different budget scenarios over the years. The algorithm suggests the optimal combination of repair segments based on our mathematical model. Also, the segments located in an area where many others require the same maintenance category gain higher weights in the calculation to make the suggested work plan efficient and realistic. This entire process is designed to mimic the considerations of the engineers who conduct maintenance planning manually.