Vehicular crowd-sensing: a parametric routing algorithm to increase spatio-temporal road network coverage

Towards Uniform Urban Map Coverage in Vehicular Crowd-Sensing: A Decentralized Incentivization Solution

“…Solutions belonging to the latter category, on the other hand, typically involve custom routing algorithms that aim at distributing vehicles more uniformly on the road network, and do not consider the problem of incentivizing drivers to accept possibly sub-optimal routes (e.g. : [2], [23], [24]). Thus, the solution we propose is not directly comparable with any of the above-mentioned approaches, as it combines the idea of a custom routing algorithm designed to achieve a more uniform sensing coverage with the key concepts of incentivization and budgetary constraints that are typically used only in solutions supporting ad-hoc sensing tasks.…”

“…: [44], [48]) require, to some extent, a centralized component which might be difficult to deploy and expensive to operate at metropolis or regionlevel scale. Asprone et al, in [2], quantified these costs: in the Municipality of San Francisco (USA) the Transportation Network Companies (TNCs), like Uber or Lyft, served on average 170 000 trips per day [36]. Having their routes calculated in the cloud with Amazon Web Services would cost roughly 72 000$ per year, just for the computational resources, without considering other costs such as data access, load balancing, network transfers, etc., and other factors, such as the need of guaranteeing short response times and high reliability.…”

“…Having their routes calculated in the cloud with Amazon Web Services would cost roughly 72 000$ per year, just for the computational resources, without considering other costs such as data access, load balancing, network transfers, etc., and other factors, such as the need of guaranteeing short response times and high reliability. When scaled on a nation-wide level, these costs might rise to millions of dollars per year, which might significantly reduce the amount of economic resources available for the incentivization [2].…”

“…Moreover, most incentivization mechanisms presented in the literature require a centralized, sensing demand-aware computing infrastructure to decide which vehicles should be recruited for sensing [47], to compute their new trajectories and to allocate the given incentivization budget. A major drawback of these architectures is that such a centralized, mission-critical computing infrastructure can be very costly to deploy and operate, especially at a nation-or region-wide scale, limiting the budget available for incentivization [2].…”

“…We formalize the set of admissible routes satisfying the incentivization budget constraint by leveraging the concept of Potential Path Area (PPA) [31], often applied in many fields to quantitatively analyze and describe the spatial behaviour of people. Let us note that the proposed solution is based on some intuitions presented in [2]. That work, however, only reported the feasibility of a decentralized, randomized approach to improve the spatio-temporal sensing coverage of probe vehicles, not taking into account the key issues of incentivization and budgetary constraints, which are crucial to deploy VCS solutions.…”