Interviews with wide variety of commuters illustrate that commuting is more than commuting. Commuting is time for reflection, learning, organizing, and sharing. Participants coin the themes ‘me-time’, ‘family-time’ and ‘flexibility’ describing their preferences. The study takes on the ‘flexibility’ theme and suggests ways in which people can find time for rich experiences surrounded by commuting. Casual ride sharing emerged as more promising sweet spot for future efforts addressing alternative transportation methods.
This project addresses a mobility issue of stress occurring during the daily commutes, and an adaptation issue of switching roles from a solo driver to a ride-sharer. The goal is to understand both the positive and negative aspects of commuting, and to design a new ride-sharing service that facilitates transitions between contexts. By providing frames for composing routines, performances, and rituals, this project exemplifies how products can help people develop strategies and interventions to support their transitions.
Scenarios inquiring into the needs of people, paving the way to understand people’s desires as well as boundaries
Process
To understand the dynamics of commuting and unveil both individual and contextual aspects affecting individuals’ commute choices, we deployed an experience design framework, called modes of transitions (MOT) and framed commuting as a transition problem [37]. MOT is a practical framework for understanding issues stemmed from transitions and translating them into product ideas. A transition can be defined as the activity of changing from one mode to another and happens through daily and long-term interactions. According to MOT for instance, commuting, on one hand, involves a spatial transition, traveling from A to B. On the other hand, it involves role transitions of switching between family and work roles [33], and adapting from solo driving into ridesharing role. While bridging different daily contexts and life stages, transitions carry possibilities of decline in peoples’ wellbeing: they can destabilize people’s routines, discord their role enactments (home, work), drain the meaning away from people’s rituals, and threaten people’s identity. MOT takes an active stance on these challenges by framing experiential issues using the routine [41], ritual [11], performance [19], and narrative themes. MOT situates these themes both in the understanding and translation phases of the design research process.
In the understanding phase, MOT helped us to frame the semi-structured interviews and a nation-wide survey with thirty commuters in a university campus setting, including solo drivers, carpoolers, and bus riders. In this phase, we found that convenience, cost, commute time, and personal preferences motivate commuting choices. Participants characterized their best commute times as when they are experiencing “me-time,” “traffic-free time,” or “ritual time”; and their worst experiences when there is a traffic-jam or a socially awkward situation. We followed up interviews with an online survey on commuting choice and collected responses from 240 participants across the United States. We found that our previously observed motivations remained significant in the larger population. However, we also observed that individuals who most valued convenience and flexibility tended to be least motivated by cost.
In the translation phase, MOT helped us to generate 13 ride sharing service concepts and assess them in a series of speed dating [12] sessions. Based on user feedback, we refined the most popular concepts and developed a concept service, and evaluated its interfaces as a paper prototype in a laboratory study.
Design
We developed a service design concept addressing flexibility, incentives, and dynamic information feed. Adapt-A-Ride is a service design that helps people to coordinate casual ridesharing and provides an incentive program for them to engage in habitual change. It provides an online social network platform built on a website, a mobile device to match drivers and riders, and a reward card for collecting incentive points. For this phase of study, we decided to focus on the idea of an online social network using the website component.
In our interview and survey results, we identified five profile features people care about in their ride mate preferences: age group, gender, affiliations, social networks (Facebook, IM, Twitter, etc.), and interest groups. We designed a profile page, where people can input their preferences for their ride mates.
To explore the users’ flexibility in depth, we designed flexibility controls on time, location, and ride mate (Fig 2). People can input their time and location flexibility both for departure and arrival. They can also indicate whom they want to ride with: friends, friends of friends, affiliates, interest groups and service members (strangers).
Fig 2. Interface for Rideshare search, flexibility controls
We envision an algorithm that can respond to individuals’ flexibility preferences with dynamic scenarios, providing people flexibility choices for time, location, ride mate, and incentives. Figure 3 shows the template we used in our study and displays rideshare choices.
Fig 5. Flexibility Choices
Each rideshare option provides dynamic information on whether the person is taking or giving a ride, ride-mate candidate, time and location proximity and the cost of the ride. In particular, Ride 1 is a ride in which the participant would give a ride to a stranger and who would share costs, however the driver would arrive later than their specified arrival time. Ride 2 is a ride in which the participant takes a ride from a friend of a friend but needs to meet the other person at a certain distance from their starting point; Ride 3 is a ride in which the driver participant gives a ride to a person from her interest group but waiting for a certain time at the starting point; Ride 4 is a ride in which the rider participant takes a ride from a stranger driver but will be dropped of at certain distance from the arrival point; Ride 5 is a ride in which the driver is using his/her own car; and Ride 6 is a ride in which the participant takes a taxi.
Based on our speed-dating study, we identified the relevance of incentive programs for ridesharing and decided to explore its effect along the other flexibility dimensions. We follow an approach similar to Nuride: an individual can get discounts from local stores by using alternative ways of commuting such as ridesharing, bike, or public transportation. However, we make the means the program open to probe participants’ preferences.