New Data and How to Use it to your Benefit

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New Data and How to Use it to your Benefit Bill Griffiths Division Chief, Fleet Management Services Montgomery County, Maryland bill.griffiths@montgomerycountymd.gov

Topics Telematics Challenges with On-Board Technology Policies Data & GIS Making Better Decisions Integrating DTC

Montgomery County Fleet 500 Sq. Miles 1 Million + Residents Over 40 Departments 24/7/365 Operations 4,000+ Fleet Vehicles 65 Million Miles Driven 6.2M Gallons of Fuel $100M Budget

Telematics Utilization Vehicle Maint. Take Home Vehicles Driver Education Telematics Fuel & Idle Mgmt. Risk Mgmt. County Services

Our History & Challenges Enforcement of Policy Multiple Pilots Retrieving Data Integrating with Motor Pool

Utilization Policy = Change County Policy Utilization criteria is measured or expressed in vehicle mileage, hours in service, user to vehicle ratios, trips per vehicle, utilization (daily and monthly percentage), or passengers carried. Once that standard has been created, a baseline will be created for future benchmarking; this will be considered the fleet profile. Departments will be provided an annual report of all vehicles and equipment not meeting the standard. They will be given 30 days to review the report, provide justification as to why the vehicle/equipment is not meeting the standard and request an exception. All vehicles that are granted an exemption will have a telematics device installed and be monitored quarterly. Vehicles that do not meet the standard will be reassigned / rotated within the department, County fleet, or sold.

County Policy Drive Green Reduce Vehicle Miles Traveled (VMT) Take Home Vehicles Idling Centralized Pooling Maintenance Practices Replacement Planning

Telematics As DFMS implements innovative solutions to create a more sustainable and efficient fleet, vehicle telematics can play an integral role. Vehicle telematics devices provide real time vehicle data on items such as fuel consumption, idle time, emissions, and vehicle diagnostics. Telematics can also be used to improve the safety and security of fleet assets. Similar to commercial GPS devices found in newer cars, these devices can provide essential data to make fact based decisions about improved routing, preventive maintenance intervals, and fleet utilization. Data provided from vehicle telematics could help optimize the fleet by reducing petroleum consumption, identifying and validating utilization criteria, reduce vehicles miles traveled through route optimization, generate cost saving from idle reduction and reduce maintenance cost. As part of the County s Drive Green initiative, DFMS will pilot telematics in FY14 and demonstrate the costs savings for potential program implementation. Additionally, DFMS will explore grant opportunities to fund vehicle telematics under a clean air or petroleum reduction grant.

Fleet GIS Project Improve Utilization Consolidate & Pool Fleet Identify Opportunities for EV integration Improve Alternative Fuel Use Idle Reduction Improve Routing

What is GIS? A geographic information system (GIS) lets us visualize, question, analyze, and interpret data to understand relationships, patterns, and trends. ESRI For our purposes, we are using GIS to visualize and analyze spatial data to understand what is happening and what will happen in geographic space with the goal of establishing patterns and relationships. The geographic space we are studying is Montgomery county and the spatial data we wish to visualize and analyze is driving patterns and driving behavior. GIS will help fleet make evidence based decisions that is reflected by the data collection and the analysis thereof.

Why GIS?

Why GIS?

Why GIS? Visualization helps convey complex ideas in easy to understand contexts. We can also discover trends, patterns and outliers in data to make actionable decisions. GIS reveals relationships and patterns that are not apparent in tables and charts. The data in the table is the same as the data in the map, but only one can convey information quickly and accurately without having to commit time to a serious statistical analysis of the numbers and data. With a map, we can have a better understanding of vehicle driving patterns, and more specifically, how they behave (idling, speeding, regular driving) depending on varying location.

Service Areas

Service Areas A network service area is a region that encompasses all accessible streets (that is, streets that are within a specified impedance). For instance, the 5-minute service area for a point on a network includes all the streets that can be reached within five minutes from that point. Concentric service areas show how accessibility varies with impedance. Once service areas are created, you can use them to identify how much land, how many people, or how much of anything else is within the neighborhood or region.

Are your facilities properly geo-located & coded?

Service Areas The service area polygons are generated by Analytical tools provided through the Network Analyst dataset. The Road dataset available through the county was used to build the network. The service area in the example represents how much time is required to travel a certain distance, depending on the speed of a vehicle. This is more accurate than calculating a blanket radius around the site, or using distance as an impedance, as roads have different speed limits. Service areas will be used to monitor vehicle behavior. Service areas can also be adjusted for traffic conditions at a certain time of day.

Silver Spring EV Vehicles 3min Drive Radius and Charging Service Area

Silver Spring EV Vehicles and Charging Service Area

Heat maps GPSi data records a data point every 2 minutes that a vehicle is running, at every ignition start, and at every engine shut off. GPSi data also records vehicle behavior, such as prolonged stopping, idling, speeding, or regular driving. We can use these points to calculate the density of features in a neighborhood around those features.

Heat maps The Kernel density tool through the Spatial Analyst extension in ArcGIS enables us to visualize where vehicles tend to congregate or cluster, and make decisions based on the output heatmap. Different statistical classification methods can be used; Quantile distribution is the best sampling method for heatmaps. Certain vehicle classes and behaviors can be filtered out for further analysis. For example, a heatmap can be created specifically for idle points and a heatmap can be made that shows where idling cars tend to cluster. To further represent the issue in question more accurately, we can weigh some features (such as idle time) to make the analysis more accurate.

Idle Heatmap weighted for idle time: Idle Heatmap: There are points that have low density with other idle points, but are given more weight due to high idle time

Speeding Heatmap weighted for Percent over speed limit: Speeding Heatmap:

DTC- Integrate with FMIS

DTC- Integrate with FMIS

Fleet Analytics Team

Summary- Items to Consider Identify - What your trying to achieve? Establish -Goals & Measures Policy Do you have ability to enforce your goals Communication & Education Monitoring Do you have time to Report Customer Involvement FMIS Integration Union Support

Questions? Bill Griffiths Division Chief, Fleet Management Services Montgomery County, Maryland bill.griffiths@montgomerycountymd.gov