Overview for Refine Olli 2.0

What is Autonomous vehicle?

An autonomous vehicle, also known as a robot vehicle, self-driving vehicle, or driverless vehicle, is capable of sensing its environment and moving with little or no human input.

Autonomous cars combine a variety of sensors to perceive their surroundings, such as radar, Lidar, sonar, GPS, odometry and inertial measurement units

Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage.

Example of Autonomous Vehicle: - Olli by LM Motors, Cars by Tesla and Waymo by Alphabet Inc.

What is OLLI?

An accessible version of the bus by Local Motors, called “Accessible Olli” is using IBM’s artificial intelligence powered Watson technology. The electric vehicle “Olli” can carry up to 12 passengers and let passengers interact with it in a conversational manner. For example, passengers can ask questions such as “Olli, can you take me downtown?” and the vehicle would respond. Olli is also answer questions related to specific vehicle functions and offer recommendations on local destinations such as restaurants or historical sites. It creates a pleasant, comfortable, intuitive and interactive experiences for riders as they journey in autonomous vehicles. It uses four Watson developer APIs, namely Speech to Text, Natural Language Classifier, Entity Extraction, and Text to speech. The vehicle also has 30 sensors embedded in to help it move about without hitting anything.

Some Specifications of Olli :-

1). Range: 40 mi/60 km (nominal), 25 mi/40 km (max load, max A/C)

2). Max Speed: 40 km/h (25 mph)

3). Max Torque: 240Nm

4). Charge Time (440 V): 1.5 hours

5). Transmission: 9.59.1 gear ratio

6). Curb Weight: 2654 kg (5850 lbs)

7). Capacity: 612 kg (1350 lbs)

8). Length: 3920mm (12.86 ft)

9). Width: 2050mm (6.73 ft)

10). Height: 2500mm (8.20 ft)

11). Wheelbase: 2526mm (8.29 ft)



My Entry: - What is Refined Olli 2.0?

Refined Olli 2.0 is new features added (Hardware, software and devices) Olli which offer a meaningful, comfortable, unique experience to riders in university campus. The refined Olli 2.0 has Glass(window) projected display, speaker, interior cameras, exterior cameras, haptic feedback on seats, specially designed seats which can be turns into bed for a quick nap, etc. It also has Watson knowledge graph which helps the rider in many ways.

Watson Knowledge Graph: - Personalized answers based on voice (Identity) recognition of travelers (frequent). Watson will create a knowledge graph for each person who travels in Olli based on his disabilities, habits and other information to provide context-based answers and services. it will keep getting better as more information is fed into the system by frequent trips in different ollies. It will know your seat position based on camera feed and provide you haptic feedback when your stop arrives and other information. We will utilize the cloud-based cognitive computing capability of IBM Watson to offer accessibility features to riders. the platform leverages four Watson developer APIs -- Speech to Text, Natural Language Classifier, Entity Extraction and Text to Speech -- to enable seamless interactions between the vehicle and rider. Riders will be able to interact conversationally with Olli and have projected display on the window to get information while traveling from point A to point B, discussing topics about how the vehicle works, where they are going, and why Olli is making specific driving decisions. These interactions with Olli are designed to create more pleasant, comfortable, intuitive and interactive experiences for riders as they journey in autonomous vehicles. This Refined Olli will provide a unique, personalized experience for every passenger while helping to revolutionize the future of transportation for years to come.

Use case: University Campus


Persona Name: Alex

Carries with him/her: Cell phone, Laptop, college bag, identity card, etc.

Thinks: About his class schedule. About his career.

About the college projects.

Feels: Attentive as he is a student. Love for his family and friends.

Sometimes stressed for college exams and projects.


Go to College from his hostel.

Watches his favorite web series.

Sees: A variety of students from different streams.

I will update it soon. Thanks

Team Lead

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Team members