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Project Summary

Project Information

For an updated project description, click on the following link for the Project Readiness Package.

Problem Statement:

Most automobile forecasters predict that by the mid-2020’s autonomous driving will transform the automobile market. What started with cruise control, then driver assist, and now highway autopilot, will soon develop into full autonomy. Self-driving cars will make our roadways safer, our environment cleaner, our roads less congested, and our lifestyles more efficient. Commuters around the world eagerly anticipate the changing of laws to allow these vehicles to take over our roadways. What started with cruise control, is now driver assist, will develop into highway auto pilot, and finally into full autonomy. From the U.S. Department of Transportation (USDOT), to the National Science Foundation (NSF), to large private grants, big money is exchanging hands to develop this transformation. Google’s self-driving cars have already logged over 2,000,000 miles, and Tesla can log up to 1M miles per day. All car manufacturers are now working towards driverless vehicles.

The Autonomous People Mover (APM) was conceived as a vehicle for use in transporting people across the campus of a large academic institution in the northeastern United States. Once complete, the APM will be summoned via a text message, after which it would drive itself to the customer’s location, pick them up, and determine a destination using voice recognition. The APM would then plan and traverse a path to the requested destination while maintaining the safety of passengers and bystanders. Ultimately, the purpose of the APM is twofold: to provide accessibility to campus goers, and to act as a platform for research and refinement of Autonomous Vehicle technologies.

Prior APM MSD projects have developed a strong foundation for autonomous capability. With an emphasis on safety and modular development, previous MSD teams have created a platform with state-of-the-art sensors. This year's APM MSD prject will center around software - firstly accurately localizing on a map, then constructing intermediate waypoints, then navigating from one waypoint to the next while recognizing and avoiding obstacles.

MSD Team Statement:

The Autonomous People Mover, or APM was designed and built to serve as a fully autonomous vehicle. Its purpose is to transport people across the campus of an academic institution. By the end of Phase VII of the APM development, the vehicle will be able to safely transport people along a predetermined path during the Imagine RIT Festival in May of 2020. The APM will be able to avoid crowds of festival goers and unpredicted obstacles to reach its destination without collision.

To reach this goal, the Phase VII team will focus on creating a Particle Filter Algorithm to aid in localization and gathering data on APM’s environment. Localization through GPS and the front camera will also be improved. Object detection specifically with curbs and small objects will also be improved. Lastly, the team will take the existing ROS software and form it into a more modular state to promote ease of use and understanding for current and future teams. Safety is of utmost importance to the Phase VII APM team and all developments will be made with this in mind.

In this his phase of the Autonomous People Mover, or Phase VII will concentrate on the following:

  • Localization on RIT Campus Map using a combination of GPS & Video
  • Constructing intermediate waypoints for routes
  • Detection of Objects using both LiDAR technology and a front-facing video camera
  • Obstacle avoidance as the vehicle traverses from one waypoint to the next

Project Title:

Autonomous People Mover - VII

Project Number: P20241

Project Family:

Autonomous People Mover

Start Term: 2191

End Term: 2201

Faculty Guide:

Alexander Loui,

Primary Customer(s):

Dr. Ray Ptucha,

Sponsor (financial support):

  • D3
  • TI (Radar)
  • Additional Funding Provided by Harris Corporation

Team Members

Jon LaosISE

Project Manager
Christopher CassidyCE

Jamie KubeckCE

Lead Software Engineer
Joel AbreuEE

Matthew McGarveyEE

Lead Hardware Engineer

Work Breakdown: By Phase

Work Breakdown: By Topic

Project Management

Design Tools

Design Documentation



Presentation & Dissemination





Risk Management

Problem Management

Communication & Minutes

Use Cases


Functional Decomposition

Morphological Chart

Pugh Concept Selection


Mechanical Drawings

Electrical Schematics

Software Diagrams

Facility Layout



Test Fixtures


Test Plans

Analysis Results


Test Results

Design Review Documents

Technical Paper


Imagine RIT Exhibit


  • Alexander Loui, Faculty Guide

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