Decoding the first-and-last mile: Analyzing the transit connecting bike share GPS routes in Hamilton, Ontario with spatiotemporal distance decay

Abstract

The well-known first-and-last mile (FM/LM) problem has long plagued traditional fixed-route public transit systems. Recently, emerging shared micromobility services, such as bike share, have been gaining popularity and quickly developing worldwide. These services present the potential to complement public transit by serving as an FM/LM solution. This study leverages Hamilton Bike Share Global Positioning System routes data and employs a novel spatiotemporal distance decay with built environment adjustment method to quantify whether bike share trips are FM/LM trips on a continuous scale ranging from 0 to 1. This approach provides a more detailed usage pattern at the road level and a more realistic identification of FM/LM trips compared to the commonly used buffer zone approach applied to origin and destination pair trip data. Subsequently, we examine the spatiotemporal patterns and trip attributes of FM/LM trips and how they differ from all bike share trips. The findings reveal distinct differences in temporal, spatial, and trip attributes between FM/LM and all bike share trips. We found that bike share trips are frequently used by riders to cover the distance between transit stops and their workplaces. Additionally, FM trips are generally more challenging compared to LM trips due to a significantly higher number of left and U-turns. Policy recommendations are proposed to enhance wayfinding, expand cycling infrastructure, and promote integrated bike share and transit usage. This research highlights the potential of bike share systems to address the FM/LM problem and provides empirical evidence to inform future urban transportation planning and policy development. It also offers a methodological framework for identifying FM/LM trips using individual trip data such as origin and destination pairs.