10 Essential Transportation Metrics to Monitor
Transportation plays a crucial role in any community, connecting people to jobs, services, and opportunities. Monitoring key metrics can provide valuable insight into how a transportation system is performing, and whether it is meeting the needs of those who rely on it.
This blog explores some key transportation metrics to analyze in any community, including measures of mobility, road safety, and accessibility. By understanding these metrics, community leaders and transportation professionals can make informed decisions to improve transportation systems and enhance the overall quality of life for residents in their communities.
Average Daily Traffic (ADT) and Annual Average Daily Traffic (AADT)
ADT and AADT both quantify how busy a stretch of road or highway is. They do this by reporting the number of vehicles passing through over the course of a day, or year, respectively. ADT and AADT have many applications within traffic engineering such as signal timing, determining where infrastructure investments should go, and much more. We wrote a whole blog post diving into AADT; read it here!
Minimum data needed to calculate this metric: traffic volumes.
Corridor Travel Times
Corridor Travel Times help determine how long it takes for vehicles to travel along specific roadways or corridors. Many factors can impact travel times such as poor traffic signal timing, events, or car crashes. Analyzing Corridor Travel Times helps transportation professionals identify when travel times rise above the baseline and develop solutions to improve traffic flow, such as adding lanes, synchronizing traffic signals, or increasing the enforcement of traffic laws.
Corridor Travel Times can also be used to evaluate the effectiveness of transportation infrastructure and policy changes. For example, if a new LRT line is built, travel times on the corridor can be tracked before and after the change to measure the impact of the new service on traffic flow.
Minimum data needed to calculate this metric: Location-based data i.e from Bluetooth devices or smartphones.
Vehicle Miles Traveled (VMT)
VMT measures the total distance that vehicles travel on a specific road or network of roads over a certain period of time. It is a useful metric that is closely linked to important factors such as traffic congestion, environmental impact, energy consumption, and economic activity.
For instance, a high VMT on a road may indicate it’s over capacity and in need of expansion or improvement. As an indicator of the environmental impact of transportation, monitoring VMT can help identify areas to implement emission reduction strategies.
Minimum data needed to calculate this metric: traffic volumes, road segment lengths.
Crash Rates are a key traffic metric to evaluate the relative safety of different roads or intersections. They are based on the number of crashes, traffic volume, and road segment lengths in that location over time.
Analyzing crash rates alongside data like traffic volumes or road design helps officials target and address specific safety issues.
Minimum data needed to calculate this metric: traffic volumes, crash data, road segment lengths, traffic volumes.
Peak Hour Factor (PHF)
PHF measures the variation in traffic demand during the busiest hours of the day for traffic, aka peak hour periods. It does so by comparing the busiest fifteen minutes within the peak hours with the total volume of vehicles that pass through a specific area within those hours.
PHF demonstrates what the traffic flow in a given area looks like, and informs traffic operations such as signal timing. Interested to learn more? Check out our blog post or white paper exploring PHF in-depth!
Minimum data needed to calculate this metric: traffic volumes.
Mode Share quantifies the proportion of people who use different forms of transportation, including driving, biking, walking, taking public transit, and more. Monitoring mode share can assist in identifying regions where alternate modes of transportation are missing or underutilized. This can ultimately help guide decisions about how to improve transportation options for residents.
Minimum data needed to calculate this metric: traffic volumes, transit ridership data, active transportation data.
Transit Accessibility refers to how easily residents of a community can access public transit services and how well those services meet their needs. Improving transit accessibility is an increasingly important goal due to the environmental and social benefits of doing so.
As a starting point, transit accessibility can measure the number of people a transit line serves and the number of destinations (jobs, amenities) that are reachable from different starting points. However, there are many factors and nuances to consider such as safety, type of destination, travel times, reliability of service, and more. As such, accessibility is often measured on a scale and assigned a score that considers different factors like the ones listed above, which will vary from community to community.
Minimum data needed to calculate this metric: transit ridership data, infrastructure data (i.e transit stops), traffic volumes, business lists, census information.
FMLM in transportation refers to the distance between a transit stop and your final destination. For example, your office or school. When these distances are far, commuters will opt to take their personal vehicle over transit out of convenience. Bridging these distances to/from transit stops to reduce personal vehicle dependence can be referred to as the FMLM problem.
Solving the FMLM problem requires an understanding of where transit and transportation gaps exist in relation to where people are commuting. Once transportation professionals identify these gaps, solutions such as expanding transit networks, offering shared mobility options, or providing on-demand transportation services (i.e. ride-hailing) to connect commuters to their final destinations can be implemented.
Minimum data needed to calculate this metric: transit ridership data, traffic volumes, infrastructure data (i.e transit stops).
Bike Lane Network Gaps
A Bike Lane Network Gap refers to a missing connection or deficiency in a network of bike lanes. The goal of a bike lane network gap analysis is to evaluate and identify areas where there are gaps in the network which can make it difficult or dangerous for people to travel by bicycle.
The results of this analysis can be a baseline metric and inform decisions about where to build new bike lanes, and how to connect existing bike lanes to create a more comprehensive and cohesive network.
Minimum data needed to calculate this metric: active transportation data, infrastructure data (i.e bike lanes).
There are many more metrics beyond these 10 that can serve as useful key performance indicators for an effective transportation system, but we hope we’ve made our point! Transportation metrics are an indispensable tool for public officials to effectively plan, design, and implement transportation systems that meet the needs of their residents.
How UrbanLogiq helps agencies monitor transportation metrics
UrbanLogiq helps public officials automate critical traffic metrics in just a few clicks. We process, integrate, and provide analytics on data from various sources to generate fast insights. This helps public officials reduce manual effort, increase accuracy and efficiency, and support data-driven decision-making. Contact us today to book a 30-minute demo!