Combinatorial Auction-Based Pricing for Multi-tenant Autonomous Vehicle Public Transportation System

TL;DR

This paper proposes a combinatorial auction-based pricing mechanism for multi-tenant autonomous vehicle public transportation, aiming to optimize social welfare and ensure strategy-proof bidding in a smart city context.

Contribution

It introduces a novel auction-based pricing model with a strategy-proof VCG mechanism for multi-tenant AV transit systems, enhancing efficiency and fairness.

Findings

The proposed mechanism maximizes social welfare in AV transportation.

Simulations confirm the strategy-proof property of the pricing scheme.

The model effectively balances competition and service quality.

Abstract

A smart city provides its people with high standard of living through advanced technologies and transport is one of the major foci. With the advent of autonomous vehicles (AVs), an AV-based public transportation system has been proposed recently, which is capable of providing new forms of transportation services with high efficiency, high flexibility, and low cost. For the benefit of passengers, multitenancy can increase market competition leading to lower service charge and higher quality of service. In this paper, we study the pricing issue of the multi-tenant AV public transportation system and three types of services are defined. The pricing process for each service type is modeled as a combinatorial auction, in which the service providers, as bidders, compete for offering transportation services. The winners of the auction are determined through an integer linear program. To prevent the bidders from raising their bids for higher returns, we propose a strategy-proof Vickrey-Clarke-Groves-based charging mechanism, which can maximize the social welfare, to settle the final charges for the customers. We perform extensive simulations to verify the analytical results and evaluate the performance of the charging mechanism.