2019/01/24 by Kevin O’Keeffe, O'Keeffe, Kevin, Santi, Paolo +4
Biochemistry, Genetics and Molecular Biology · Computer Science · Social Sciences · #Diffusion and Search Dynamics #FOS: Physical sciences #Human Mobility and Location-Based Analysis #Optimization and Search Problems #Physics and Society (physics.soc-ph) #Statistical Mechanics (cond-mat.stat-mech)
paper · pdf · doi:10.48550/arxiv.1901.08678
openalex publication_date 2019/01/24 · openalex created_date 2019/02/21 · openalex updated_date 2026/07/28
We study a new random search process: the taxi-drive. The motivation for this process comes from urban sensing, in which sensors are mounted on moving vehicles such as taxis, allowing urban environments to be opportunistically monitored. Inspired by the movements of real taxis, the taxi-drive is composed of both random and regular parts; passengers are brought to randomly chosen locations via deterministic (i.e. shortest paths) routes. We show through a numerical study that this hybrid motion endows the taxi-drive with advantageous spreading properties. In particular, on certain graph topologies it offers reduced cover times compared to persistent random walks.