Urban car sharing: an overview of relocation strategies

Cepolina, Elvezia Maria; Farina, Alessandro

doi:10.2495/ut120361

Cited by 25 publications

(19 citation statements)

References 9 publications

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“…This method has been regarded as an easy way to practice and enables fast implementation for carsharing operators [23]. [24] summarized existing studies intended to address the problem of vehicle relocation and categorized some of the approaches. Threshold based method was clearly organized.…”

Section: Study On Vehicle Relocation Problemsmentioning

confidence: 99%

Vehicle Relocation Triggering Thresholds Determination in Electric Carsharing System under Stochastic Demand

Wang

2018

Journal of Advanced Transportation

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Vehicle unbalance usually occurs in multistation electric carsharing systems. Threshold triggering method is one of the most practicable approaches for vehicle relocation, while determination of thresholds has not been sufficiently studied particularly for electric carsharing system. This paper presents an approach on determining the thresholds considering the stochastic demands and system states. Firstly, we establish a state transition model involving the stochastic variables to capture the dynamics of the number and battery status of vehicles as well as the traffic demands. Consequently, a dual-objective optimization model was developed to determine the proper values of thresholds. The solution algorithm employed the min-max robust optimization to tackle the uncertainty and the Pareto optimum to decide the solution under dual objectives. To test the distribution stochastic variables, we involve the orders data and the supplementary user survey. Comparison is conducted among three methods: the empirical rules, the deterministic method, and the stochastic method, where the results suggest that the stochastic method achieves better solutions on the dual objectives under stochastic demands.

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Section: Study On Vehicle Relocation Problemsmentioning

confidence: 99%

Vehicle Relocation Triggering Thresholds Determination in Electric Carsharing System under Stochastic Demand

Wang

2018

Journal of Advanced Transportation

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“…This situation is referred as ZV i.e. Zero Vehicle [7,10,15]. When this condition occurs, the station has a shortage of vehicles and to avoid a possible queue in the next future a request for a vehicle is generated.…”

Section: Introductionmentioning

confidence: 99%

“…Full Port [7,10,15]. When this situation occurs, a station has reached its capacity and therefore vehicles arriving must be redirected to other stations because there is not more free space for parking.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, relocation is necessary. In literature, several relocation schemes are proposed [7]. In operator-based relocation strategies some operators manually relocate a vehicle or a platoon of vehicles from stations having too many vehicles to stations having too few.…”

Section: Introductionmentioning

confidence: 99%

“…The shortest time criterion relates mainly to service levels, while the inventory balancing mainly focuses on cost efficiency. Therefore, an appropriate choice of relocation technique should be made according to the current system situation: in periods of low usage, the most appropriate relocation technique is by inventory balancing whilst in periods of high usage, then the shortest time technique performs best [7,10].…”

Section: Introductionmentioning

confidence: 99%

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A methodology for planning a new urban car sharing system with fully automated personal vehicles

Cepolina

Farina

2013

Eur. Transp. Res. Rev.

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Purpose The paper concerns a transport system for pedestrian areas, based on a fleet of fully-automated Personal Intelligent Accessible Vehicles. The following services are provided: instant access, open ended reservation and one way trips. All these features provide users with high flexibility, but create a problem of uneven distribution of vehicles among the stations. A fully vehicle based relocation strategy is proposed: when a relocation is required vehicles automatically move among stations. The paper focuses on a methodology that allows to plan the proposed transport system for wide pedestrian areas. The methodology aims to determine the fleet dimension and the relocation strategy parameters which minimize the system cost. The system cost takes into account the level of service and the efficiency. Relocation strategy parameters define when and among which stations relocations should be performed. Methods The problem faced is an optimisation problem where the search space is defined by all the possible fleet dimensions and relocation strategy parameters. As this cost function could be a multipeak function and since the search space is discrete and extremely large, a random search algorithm has been adopted. Because of the characteristics of the problem, a parallel optimization technique was required. Given a fleet dimension and relocation strategy parameters, a microsimulator models the activity of each user, as well as the activity of each vehicle over time with the aim of finding the level of service and the system efficiency.Results, conclusions and application The methodology has been applied to planning the proposed transport system for the centre of Barreiro, Portugal.

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Increasing Acceptance of Free-Floating Car Sharing Systems Using Smart Relocation Strategies: A Survey Based Study of car2go Hamburg

Herrmann

Schulte

Voß

2014

Lecture Notes in Computer Science

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Abstract. Rapid growth rates seem to indicate that recently introduced free-floating car sharing (FFCS) can mean a breakthrough for the car sharing idea. Like other vehicle sharing systems, FFCS systems face significant regional demand fluctuations. Thus, providers might have to reposition empty vehicles to not lose potential customers. However, this aspect has been hardly examined in research and practice. This study aims to investigate appropriate relocation strategies for this new type of car sharing systems regarding the case of car2go. For this purpose a survey based evaluation was conducted, new relocation strategies were developed, and a discrete-event simulation model for the evaluation with real time data from car2go was drafted. The results indicate that availability of cars is crucial for customer acceptance, but customers are open for smart relocation strategies. Furthermore, the developed simulation approach provides the basis for an in-depth analysis of various strategies with different objectives using a realistic demand forecast.

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Urban car sharing: an overview of relocation strategies

Cited by 25 publications

References 9 publications

Vehicle Relocation Triggering Thresholds Determination in Electric Carsharing System under Stochastic Demand

Vehicle Relocation Triggering Thresholds Determination in Electric Carsharing System under Stochastic Demand

A methodology for planning a new urban car sharing system with fully automated personal vehicles

Increasing Acceptance of Free-Floating Car Sharing Systems Using Smart Relocation Strategies: A Survey Based Study of car2go Hamburg

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