Carsharing systems demand estimation and defined operations: a literature review

Jorge, Diana; Correia, Gonçalo Homem de Almeida · 2013 · OpenAlex-citations

DOI: 10.18757/ejtir.2013.13.3.2999

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Summary

This literature review addresses the challenges of modeling demand and managing operations for carsharing systems, with a specific focus on the emerging one-way model. The research is motivated by the growing adoption of carsharing in the European Union as a strategy to reduce urban transport externalities, such as congestion and emissions. While carsharing offers higher vehicle utilization and reduced ownership compared to private cars, its operational complexity—particularly the interdependence of supply and demand in one-way systems where vehicles can be dropped off at different stations than where they were picked up—hinders effective planning and cost-benefit assessment. The authors aim to identify gaps in existing mathematical models and propose directions for future research. The paper synthesizes existing literature through a comprehensive review of mathematical models, simulation studies, and empirical surveys. It categorizes research into two main streams: demand modeling and operational management for one-way systems. For demand, the review examines regression analyses, stated-preference surveys, and activity-based micro-simulation models that predict user behavior and market penetration. For operations, it evaluates system dynamics models, discrete-event simulations, and agent-based models designed to address the "vehicle imbalance problem," where uneven trip patterns lead to stock shortages at certain stations. The review also analyzes optimization approaches for vehicle relocation, including operator-based strategies and decision support systems tested against real-world data from initiatives like Honda ICVS. The findings reveal significant limitations in current methodologies. Demand modeling is complicated by the feedback loop between vehicle availability and trip generation; most existing models are context-specific, focus on round-trip systems, or fail to accurately represent supply constraints. For instance, while micro-simulation models can estimate demand under ideal conditions, they often assume unlimited vehicle availability. Regarding one-way operations, the review finds that while simulation models can predict system performance and accessibility, they frequently lack mechanisms for balancing vehicle stocks. Optimization models for relocation have shown potential for reducing staff costs and improving service levels, but they often rely on simplifications that limit their realism or scalability. Furthermore, empirical evidence suggests that while one-way systems offer greater user flexibility and higher market penetration, they suffer from operational inefficiencies that can lead to service degradation and financial losses, as seen in the failure of the Honda ICVS program. The significance of this review lies in its identification of critical research gaps, particularly the lack of integrated models that simultaneously characterize demand and supply for one-way carsharing. The authors conclude that current tools are insufficient for robust cost-benefit assessments required to justify public and private investment. Future research must develop more complex models that account for the dynamic interplay of supply and demand, incorporate realistic relocation strategies, and validate findings against real-world operational data. This work provides a foundational roadmap for advancing the theoretical and practical understanding of carsharing systems, essential for their sustainable integration into urban mobility networks.

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• micromobility e scooter