As described before, car sharing has different social, environmental and land use impacts. Most of them are positive, such as a reduction of car ownership, due to users who decide to dispose of an owned vehicle or not to buy an extra car after joining the service. This contributes to decrease the parking space occupied by private vehicles; in this way, cities with limited public areas can gain further space for different land uses. The decreasing private car usage induces travellers to adopt alternative and more sustainable transport modes, such as public transport, bike and walking.
Furthermore, the introduction of car sharing is found to reduce vehicle miles travelled, since users lowered the number of their private cars; in addition, they became more conscious of driving cost and, consequently, they used vehicles more appropriately, shortening travel distances. Moreover, car sharing contributes to reduce carbon fossil emissions, as a consequence of these aspects and since fleets are often equipped with efficient low-emission or electric engines. However, the quantification of these impacts is often difficult and uncertain, due to the complexity of this evaluation. Therefore estimating and analysing travel demand of this mode is important to evaluate these impacts, thus providing sound basis to policy makers and local authorities, who have to decide whether to address public resources to promote car sharing.
Furthermore, car sharing can significantly alter the modal share of travellers, since it can substitute or complement existing travel means, with relationships that are still not clear and often site-specific. In particular, car sharing can complement public transport solving the “first and last miles” problem, increasing its spatial and temporal accessibility, since car sharing can be used in areas with low public transport penetration or in time periods when it is less frequent. However car sharing can also substitute transit for systematic trips. This controversial relationship can change according to car sharing operational model, due to different types of trips which can be addressed by each service model. The same ambiguity is reported for bike, walking and taxi. Moreover competitiveness can arise even among car sharing operators with different business models within the same city. The analysis of complementarity and substitution patterns can help transportation planners and policy makers in providing travellers with a range of mobility options which can accommodate all their mobility needs. In addition, previously described benefits can be effective only if car sharing is able to attract private car drivers and, therefore, if it does not substitute other existing sustainable modes (such as public transport, bike and walking).
According to this last consideration, few authors developed specific analysis for each transport modes that car sharing can substitute. In the present work of thesis, the effect of car sharing on existing travel modes is modelled by separately considering the shift from private car, public transport, bike and walking. In this way, it is possible to identify factors affecting the choice to switch to car sharing and the relationships of complementarity and/or substitution between car sharing and each travel modes. Therefore, through the proposed approach, the use of car sharing can be promoted or avoided, by varying mode-specific factors.
Furthermore modelling results of the switch from private car towards car sharing are used to quantify the reduction of public space. Unlike previous works, the decreasing of parking space is not linked to car ownership changes. On the contrary, through the developed method, the new parking configuration is related to the different modal share of travellers deciding to adopt car sharing.
In order to reach these aims, different models and methods are adopted: logit models based on Random Utility Theory, data mining techniques and a new visual approach. Each technique can
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complement each other providing different information, which are useful to create the global framework to model travel demand, to estimate impacts after the introduction of car sharing and to define the best ambit of use of each travel means.
Data used to calibrate and apply proposed approaches are obtained from a travel survey, carried out in the Municipality of Turin, where three One-way car sharing services are operating. Unlike the majority of previous works, this survey was administered to a representative sample of the population living in the study area. Therefore results are reliable and can be generalized to the whole universe1 of the population living in the study area. It is worth noting that obtained results are site-specific and, for this reason, they cannot be transferred to other cities or countries. Furthermore, the survey contains also a section with Stated-preferences experiments. Differently from previous works where these choices tasks are based on a hypothetical trip, in this case, travellers are asked about using different transport modes in the future, referring to a trip that was performed before the interview. Therefore respondents focused on a real trip, rather than an abstract choice. Moreover, attributes of the opt-out alternative are those directly obtained from the reported trip, and attributes of the alternative modes are derived from the real transportation network, public transport agencies and information about current car sharing services. These aspects increase the realism and reliability of respondents’
answers, thus providing sound basis for the results of applied modelling approaches.
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1Here and in the following, the universe is considered, from a statistical point of view, as the population of interest from which a sample is selected in order to represent it with certain attributes (Hensher et al., 2005; Ortuzar and Willumsen, 2011).
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