M Barth
M Todd

Document Type

Journal Article

Publication Date


Subject Area

infrastructure - track, infrastructure - vehicle, economics - appraisal/evaluation, organisation - management, technology - intelligent transport systems


User behavior, University of California, Riverside, Tracking systems, Software, Smart cards, Shared electric vehicle system, RTI, Road transport informatics, Operational analysis, Monitoring systems, Monitoring, Management, IVHS, ITS (Intelligent transportation systems), Intelligent vehicle highway systems, Intelligent transportation systems, Integrated circuit cards, Evaluation and assessment, Electric vehicles, Contactless fare cards, Chip cards, Battery powered vehicles, ATT, Advanced transport telematics


Critical to any new transportation system technology is how users respond to the new technology or system. Various intelligent transportation system studies and demonstrations have shown that the greatest likelihood for success comes when users adjust their behavior and embrace the system. However, user behavior is often difficult to predict and is often overlooked as a critical component when introducing new transportation systems or technology. To better understand user behavior in shared vehicle systems, an intelligent shared electric vehicle system test bed has been developed at the University of California-Riverside (UCR), named UCR IntelliShare. Faculty and staff use this system, consisting of 15 shared electric vehicles and three stations, for their daily travel needs. The system technology includes smart cards, touch-screen registration kiosks, vehicle monitoring and tracking hardware, and sophisticated management software. With this test bed system, researchers can develop and implement new operating techniques, perform experiments in travel demand management, collect data for supporting models, and quantify the energy and emissions savings associated with the system. The user behavior aspect of the system is the focus of this study. Much information has been collected through user surveys and operational analysis. The surveys have provided good insight on user satisfaction and on how the system is used. The operational analysis has brought forth key results on trip characteristics and travel demand patterns. Initial results indicate that the UCR IntelliShare system may be temporarily producing approximately 15% more trips. Other results indicate that trips between stations are fairly well matched, requiring few relocations. Further, day-by-day travel patterns are relatively consistent; however, approximately 14% of the travel patterns deviate significantly. These results, along with calibrated simulation models, can be used to help design other shared vehicles systems before implementation, potentially reducing associated risks and liabilities.