Bicycle Data-Driven Application Framework: A Dutch Case Study on Machine Learning-Based Bicycle Delay Estimation at Signalized Intersections Using Nationwide Sparse GPS Data

Data-driven approaches are helpful for quantitative justification and performance evaluation. The Netherlands has made notable strides in establishing a national protocol for bicycle traffic counting and collecting GPS cycling data through initiatives such as the Talking Bikes program. This article addresses the need for a generic framework to...

Comparing three types of real-time data collection techniques: Counting cameras, Wi-Fi sensors and GPS trackers

Nowadays, many large scale events are organised in urban areas that are not designed to accomodate these large visitor flows, as not only the sheer number of people is larger than anticipated, but also their behaviour is different. For a timely deployment of crowd management measures, continuous information on the real-time traffic state on the...

Estimating travel times using Wi-Fi sensor data

Determining travel time information from Wi-Fi (or Bluetooth) sensors is not trivial due to various (often technical) reasons. In this contribution, we focus on the problem of distinguishing travel time from the time people spend performing activities (e.g. fuelling the car, standing still to watch the scenery, buying a train ticket). More...