How might we improve the experience of travelers using driverless cabs?


Rover is a conversational user interface that creates seamless ride experiences for travelers in a foreign land.

1. The Problem Space

We decided to design for a future in which most people prefer using a ride-sharing service to owning a car.

Our competitive analysis showed a fragmented landscape of products and services, comprising both established car manufacturers as well as startups. As of October 2017, some potential players in the space include Google Assistant, Teslabot, Bot Studio, and Uber.

Here is a table summarizing our competitive analysis.

2. Our Concept

Rover is a multimodal user inferface with voice, text, and visuals.


Visuals are used inside the car as a cue to indicate pre-attentive and attentive states.


Speech is used for conversations in the car.

remote contact

Text is used for out-of-car contact.


Text is used inside the car for media-rich conversations, such as restaurant recommendations.

Designing for Speech

Ubiquitous. Unforgiving. Short attention spans.

CUIs need to speak a simple, succinct language with lots of repetition. CUIs must be highly flexible in their journey from intention to fulfillment. Finally, CUIs must be exceptionally adept at error recovery. To learn more, read my article on the politics of voice design.

3. Adding essentials

Here are seven of the most fundamental interactions for a conversational interface. We designed Rover with these interactions in mind.

pre-attentive state

How does the CUI indicate that it is listening?

recognize utterance

Can the CUI process what the user is saying?

predict intention

Can the CUI understand what the user really means?

provide response

Can the CUI respond appropriately to the user's request?

recognize error

Can the CUI detect errors in the conversation?

recover from error

Can the CUI recover from errors transparently and promptly?

terminate session

How does the CUI end a conversation?

4. Creating a personality

Rover is male, with a full, deep voice. He is a friendly and proactive assistant.


Rover stays with users across rides. He remembers past conversations and references recent ones.


Rover's overarching goal is to make passengers feel more at ease as they order and ride cabs.


Rover is able to access maps, traffic informaiton, dining options, events, and transportation schedules.

5. Conversation Modeling

We focused on a few key intentions and modeled each of those conversations from beginning to end.

Our conversational models identified the user’s intentions and mapped a range of possible utterances to responses from the system. We also came up with a happy path for each intention. A happy path is a direct conversation that leads from utterance to fulfillment of an intention. Here's an example:

A model of a happy path from utterance to fulfillment.

A model of a complex conversation showing the pre-attentive and attentive states of the CUI.

If we had more time...

We would build out multiple conversations on DialogFlow, from beginning to end, and try them out with real users. In parallel, we would prototype a graphical interface that might accompany the CUI in autonomous cabs of the future.

As prototyping lead, I iterated on conversation and personality design for Rover. The team also included J. Liu and X. Zhang. Specials thanks to F. Maturana.