Transportation engineers and planners often are not only interested in the trips a vehicle takes, but also on a vehicle’s ultimate origin and destination. Consider the case of a long-haul truck’s journey from a supply depot to its ultimate destination. This journey could consist of several trips related to the truck’s operation, such as weighing stations, refueling or rest stops. Due to the careful construction of trips, we are able to flexibly “chain” trips together to determine a vehicle’s ultimate origin and destination using post-trip stop information. This is useful information when looking at border crossings, as well as when vehicles move to and from ports.
For many commercial logistical efficiencies, understanding where a vehicle is coming from and what their final destination is helps to keep freight moving at the right pace. Considering the consequences witnessed with multiple disruptions in the supply chain, using trip data along with origin and destination information can aid in investigating delays and their impacts on truck congestion at ports.
Combining trip information with vehicle industry data can also help planners gain a better understanding of which industries are contributing the most to freight traffic overall. Taking a year-over-year approach, planners can then see where the biggest increases were identified in traffic volume.
Getting granular into a vehicle’s purpose, armed also with trip and journey data can also help start to fill in gaps for transportation planners when it comes to understanding vehicle behavior. For example, identifying vehicles used in door-to-door delivery services and then being able to hone in on their trip behavior can highlight infrastructure adjustments that might be necessary to accommodate, like curbside parking.
Origin and destination and “trip chaining” information provides a new level of data-driven insights to planners for those critical infrastructure planning and transportation funding decisions.