How City Sensors Contribute To Understanding Traffic Conditions

Everyone tends to get frustrated getting stuck in traffic. As the global population increases, the time people spend in traffic jams also increases. Cities that were once built for small population sizes are now made to plan anew to adjust for more traffic jams. To cite an example, in 1982, it was estimated that people living in the US spent around 18 hr per year sitting in congestion. In 2015, US residents spent around 42 hr per year.

City planners need to gather data that provides them a fair idea of how their city commutes before implementing effective solutions. While effective public transportation and newer technologies such as driverless cars have an impact on the situation, the key to developing a long-term strategy is to have a good understanding of the city’s traffic flow.

As far as driving conditions are concerned, the three main factors are speed, density, and flow of each road throughout different times of the day. With this information, cities can introduce proper traffic policies, public transportation, adjust road infrastructure (lane changes, traffic signal adaptations, etc), as well as steer city development in the proper direction. But before they do so, cities need to collect data. Thankfully, nowadays there are many data sources that can be leveraged to obtain information on these aspects.

GATHERING NECESSARY DATA

To understand the traffic conditions in a city, it is imperative to have a detailed knowledge of as many roads as possible. For example, understanding whether a street’s traffic operates in unsaturated, saturated, or oversaturated conditions. For this, a representative and true traffic model is vital. Traffic theory argues that a traffic model provides information on the relation of speed, flow, and density variables specific to each road throughout a given day. This is otherwise known as the macroscopic fundamental diagram.

In the past, municipalities retrieved this information, especially the flow parameter, by manually counting cars on the streets. Progressive cities were installing inductive loop detectors for the same end result. Today, the technology has improved significantly, especially with regards to sensors and the internet of things to obtain these data in a more rich and reliable way as well as in real-time.