Edinburgh Napier University

  Shared ownership and ridership models to determine driverless car use in Edinburgh
This research explores the shared ownership and ridership possibilities of driverless cars (DC) among Edinburgh residents. The mobility landscape is likely to observe transformative changes over the coming years due to the advent of driverless cars (DC). DCs are machines with intelligent technology instruments that allow them to control driving function without human intervention and thus likely to replace human driving. Ageing seniors and those mobility impaired who otherwise have to depend on others to go around can use DCs as and when they need them. Moreover, DC can offer more enjoyable and productive in-vehicle time since there are no essential driving tasks. DCs may attract more people to use motorised transport due to the hassle-free riding opportunity, thus generating further delays and congestion in the road network. In contrast, shared DCs can reduce road traffic, increase car usage efficiency, and make mobility affordable and cities liveable. These are why the advent of DCs may lead to marked changes in individual mobility sharing behaviour.
The impact of shared DC on travel behaviour has led to significant research efforts within recent years. However, these researches have primarily focused on a single aspect of DC use (e.g., DC effect on trip generation, land-use change, vehicle-miles-travelled). Besides, several agent-based simulations analysed area-wide hypothetical shared DC market scenarios, where the researchers underscored the importance of the socio-demographic variations of individuals n making DC sharing decisions. A few studies discussed several household mobility sharing factors and compared the scope of sharing with strangers and family members. We also have limited research emphasising the possibilities of flexible DC ownership at present. With these shortcomings from the current findings, the present study: (a) looked at the household usage data to unearth various DC sharing propensities advances the discussion of shared ownership of DC within 3 – 4 members who are not from the same household; (b) discussed hypothetical DC shared ownership and ridership scenarios; (c) provides insights into comparing socio-economic data to understand DC shared ownership and ridership possibilities; (d) this research is the first of it's kind to include the personality and social norm attitudes in assessing shared DC use.
We consider two aspects of DC "use": shared ownership and ridership. For shared ownership, we studied (a) private DC, for which the owner buy, maintain, ensure the DC to avail that any time; (b) fractionally owned DC, which 3-4 people own, share all liabilities (e.g., car cost, tax, insurances, maintenance, fuel), and ideally divide usage time by signing to a web-enabled scheduling system; (c) driverless taxi, for which users have to pay a usage fee for the time being used instead of the purchase cost (we note that lower costs are likely to pay because of the absence of a driver onboard). DC shared ridership options are : (a) ride alone in a hired DC without any close contacts with one-time rental cost; (b) riding in a rented DC with at least one of the rider's close contacts with the convenience of shared rental cost; (c) riding in a rented DC with a stranger who is out of renter's close contacts with the convenience of the shared rental cost.
For this research, we collected data through an online questionnaire survey in Edinburgh disseminated with leaflets conducted during August – December 2019. The leaflet explained the aim of this survey and the role of DC in sharing. 7500 households were invited in this survey following seven social disparity indicators (e.g., income, education) mentioned in the Scottish index of multiple deprivations (SMID). The addresses were carefully selected to draw a representative sample of the Edinburgh population resulted in 500 responses. Our questionnaire, based on a thorough literature review and interviews with mobility experts. It had four core sections (respondents' current carsharing and ridesharing attitudes; determinants of attitudes towards carsharing and ridesharing; the likelihood of adopting different DC ownership and ridership models; personality traits, social norms, and socio-demographic characteristics), featuring a total of 26 questions. The online questionnaire was initiated with a video demonstrating the shared usage of DC. The likelihood of adopting DC options was measured on a 5-point Likert scale from very unlikely to very likely.
Working-age (16 – 64 years) respondents are 69.54%, then 69.6% of the same for the Edinburgh population. Initially, respondents' present carsharing and ridesharing behaviour was clustered to form the present sharing variables. Then, the ordered probit models were estimated to explain respondents' propensity for selected DC shared ownership and ridership with present sharing behaviour, personality, social norms, and socio-demographic characteristics. Environment-sensitive frequent household car-users are inclined to adopt private DC, whereas highly-educated upper 55's are less inclined. In addition, high-earning (>£50,000 per year), younger adults (23-55 years), cooperative and resource-sharing behaviour are significant determinants of driverless-taxi use. City-centre dwelling cooperative millennials with resource-sharing behaviour are willing to share DC with a stranger. Upper 55's people with family are reluctant to ride alone in DC, but frequent household car-using millennials with environment-preserving feelings are likely to ride alone. Respondents living in outer-city suburbs are inclined to shared DC with their family members. In contrast, city centre dwelling millennials bearing cooperative and sharing mentality are likely to share their family-used DC with strangers.
We followed ordered probit and multinomial logit models to identify the determinants of DC shared ownership and ridership in Edinburgh. Modelling results found that age, car ownership, personality, and social norm behaviour are significant determinants for shared DC use. Millennials are the likely early adopters of shared DC, while ageing seniors (baby boomers) are indifferent to use non-shared DC. Present car-owning, environment-savvy respondents are willing to use non-shared DC. Peoples cooperative and sharing attitudes are responsible for deciding them for shared DC use. The high-earning part of society valued driverless taxis as a single-used option, contrary to DCs potential for reducing traffic from the urban road network. Therefore, policy formulation concerning synchronous DC sharing is crucial to facilitate the modal shift from single-use taxi to shared-use driverless taxi. Besides, policymakers should encourage privacy-preservative DC interior design to ensure this modal shift. DC sharing is likely to be different in various urban contexts and pricing scenarios within various socio-demographic cohorts. Potential choice experiments concerning shared use of DC should include the personality and social norm perspectives in more detail along with hypothetical pricing scenarios to address possible constraints in transforming private to service use of DC.
Keywords: driverless car, shared ownership, ridesharing, online survey, ordered probit models