Integrating Gamification with Demand-Responsive Transportation: An Approach to User-Driven Optimisation

The successful implementation of demand-responsive transportation services is often hindered due to difficulties associated with economic viability. With the aim of reducing service operational costs and environmental impact, this paper proposes an architecture that enables user-driven optimisation through the modification of their travel preferences. Specifically, the paper presents two modules which, integrated with a demand-responsive system, enable vehicle route optimisation, thus saving on costs derived from travelled kilometres and vehicle maintenance. On the one hand, the request modification module computes feasible modifications of the origin or destination stops in a customer travel request, changing them to neighbouring stops such that the transportation routes are simplified. On the other hand, a gamification module is implemented to motivate the customer’s acceptance of their request modification. Such a motivation is achieved by offering a personalised reward coupled with each modification, computed taking into account user preferences. Upon the acceptance of a modification, the user receives the reward, which may represent social or monetary benefits within the gamified demand-responsive service. The current research formalises both modules and tests their optimisation potential through the development of a case study in transportation scenarios with variable fleet sizes and demand intensities. The results indicate that the implementation of request modifications can save up to 5 % of a fleet’s operational costs if the right conditions are met. Moreover, when the flexibility of the request modification module is increased, savings may increase, however, at the cost of the customer’s preferred travel parameters. Thus, a balance between optimisation potential and user satisfaction must be sought.

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Publication Details

Journal
ADCAIJ ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL
Published
2025-07-04
DOI
https://doi.org/10.14201/adcaij.32956
Primary Topic
Educational Games and Gamification
Type
article
Field-Weighted Citation Impact
0.00

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article

Integrating Gamification with Demand-Responsive Transportation: An Approach to User-Driven Optimisation

Bogdan Okreša Đurić, Markus Schatten, Jaume Jordán, Vicente Julián et al.
ADCAIJ ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL
Educational Games and Gamification
article

Integrating Gamification with Demand-Responsive Transportation: An Approach to User-Driven Optimisation

Bogdan Okreša Đurić, Markus Schatten, Jaume Jordán, Vicente Julián, Pasqual Martí
article en

Abstract

The successful implementation of demand-responsive transportation services is often hindered due to difficulties associated with economic viability. With the aim of reducing service operational costs and environmental impact, this paper proposes an architecture that enables user-driven optimisation through the modification of their travel preferences. Specifically, the paper presents two modules which, integrated with a demand-responsive system, enable vehicle route optimisation, thus saving on costs derived from travelled kilometres and vehicle maintenance. On the one hand, the request modification module computes feasible modifications of the origin or destination stops in a customer travel request, changing them to neighbouring stops such that the transportation routes are simplified. On the other hand, a gamification module is implemented to motivate the customer’s acceptance of their request modification. Such a motivation is achieved by offering a personalised reward coupled with each modification, computed taking into account user preferences. Upon the acceptance of a modification, the user receives the reward, which may represent social or monetary benefits within the gamified demand-responsive service. The current research formalises both modules and tests their optimisation potential through the development of a case study in transportation scenarios with variable fleet sizes and demand intensities. The results indicate that the implementation of request modifications can save up to 5 % of a fleet’s operational costs if the right conditions are met. Moreover, when the flexibility of the request modification module is increased, savings may increase, however, at the cost of the customer’s preferred travel parameters. Thus, a balance between optimisation potential and user satisfaction must be sought.

ADCAIJ ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNALVol. 14
University of Zagreb (HR), Artificial Intelligence Research Institute (ES), Universitat Politècnica de València (ES)
European Regional Development Fund, Agencia Estatal de Investigación
Openalex Percentile: Top 83%
Educational Games and Gamification
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