A novel formulation for the distributed solution of load balancing problems in mobility on-demand systems

Acquaviva, Francesco; Paola, Donato Di; Rizzo, Alessandro

doi:10.1109/iccve.2014.7297687

Cited by 6 publications

(11 citation statements)

References 10 publications

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“…The design of novel mobility solutions based on the optimization of both the provider's profits and the user's satisfaction is a hot research topic at present [8], [13], [14]. On the one hand, the system should generate income that allows its sustainability, covering all costs and generating revenues.…”

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confidence: 99%

“…In this context, MOD systems aim at providing citizens with an affordable service offering the same benefits of flexible transportation systems through the use of a fleet of shared vehicles. Crucial aspects in the management of MOD systems are optimal vehicle assignment [1], fleet balancing [6], [7], and maintenance of low operational costs and good level of service [8]. Fleet balancing, vehicle assignment, and user behavior have been usually tackled separately in recent research efforts.…”

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confidence: 99%

“…The aim of the strategy defined in [8] is to optimize costs and revenues for both customers and the provider, while trying to keep the system balanced. Here, we extend the approach in [8] by modeling a station-to-door MOD system and defining an objective function that explicitly accounts for the customer's impatience, which is posited to be related to the waiting time at the departure station. This characteristic makes the proposed model representative of the real way customers experience urban traveling [17], [18], [19].…”

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confidence: 99%

“…In this paper, an optimal vehicle assignment strategy for a station-to-door MOD system is proposed. The approach is inspired to [8], where the system has been modeled leveraging the Profitable Tour Problem [16] to design an optimization strategy for a station-to-station MOD system. The aim of the strategy defined in [8] is to optimize costs and revenues for both customers and the provider, while trying to keep the system balanced.…”

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confidence: 99%

“…The approach is inspired to [8], where the system has been modeled leveraging the Profitable Tour Problem [16] to design an optimization strategy for a station-to-station MOD system. The aim of the strategy defined in [8] is to optimize costs and revenues for both customers and the provider, while trying to keep the system balanced. Here, we extend the approach in [8] by modeling a station-to-door MOD system and defining an objective function that explicitly accounts for the customer's impatience, which is posited to be related to the waiting time at the departure station.…”

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confidence: 99%

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Customer-Oriented Optimal Vehicle Assignment in Mobility-on-Demand Systems

Acquaviva¹,

Núñez

Paola

et al. 2015

2015 IEEE 18th International Conference on Intelligent Transportation Systems

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In this paper, we introduce a novel optimization framework for a station-to-door mobility-on-demand system that aims at ensuring an efficient transportation service for the daily mobility of passengers in densely populated urban areas. We propose a mixed integer linear programming approach that maximizes both the customers' satisfaction and the provider's revenues, keeping at the same time the number of vehicles in each station within given bounds towards the improvement of system balancing. The proposed customer-oriented approach aims at meeting as many customer requests as possible, while maximizing the provider revenues and reducing the customers' impatience, thus increasing their satisfaction. This implies, in turn, a better reputation for the service provider. The performance of the proposed approach is assessed through an extensive Monte Carlo simulation campaign. In particular, through the analysis of different performance indices, we compare the optimal solution of the proposed approach with the optimal solution achieved by a previously presented approach based on the Profitable Tour Problem.

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confidence: 99%

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confidence: 99%

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confidence: 99%

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confidence: 99%

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confidence: 99%

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Customer-Oriented Optimal Vehicle Assignment in Mobility-on-Demand Systems

Acquaviva¹,

Núñez

Paola

et al. 2015

2015 IEEE 18th International Conference on Intelligent Transportation Systems

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Modeling shared autonomous electric vehicles: Potential for transport and power grid integration

Iacobucci

McLellan

Tezuka

2018

Energy

116

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One-way car-sharing systems are becoming increasingly popular, and the introduction of autonomous vehicles could make these systems even more widespread. Shared Autonomous Electric Vehicles (SAEVs) could also allow for more controllable charging compared to private electric vehicles, allowing large scale demand response and providing essential ancillary services to the electric grid. In this work, we develop a simulation methodology for evaluating a SAEV system interacting with passengers and charging at designated charging stations using a heuristic-based charging strategy. The influence of fleet size is studied in terms of transport service quality and break-even prices for the system. We test the potential of the system to supply operating reserve by formulating an optimization problem for the optimal deployment of vehicles during a grid operator request. The results of the simulations for the case study of Tokyo show that a fleet of SAEVs would only need to be about 10%-14% of a fleet of private cars providing a comparable level of transport service, with low break-even prices. Moreover, we show that the

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