Car-Link Enhanced Adaptive Cruise Control



Similar documents
Adaptive Cruise Control

Tips and Technology For Bosch Partners

Road speed limitation for commercial vehicles

Adaptive Cruise Control of a Passenger Car Using Hybrid of Sliding Mode Control and Fuzzy Logic Control

Case Study Competition Be an engineer of the future! Innovating cars using the latest instrumentation!

By: M.Habibullah Pagarkar Kaushal Parekh Jogen Shah Jignasa Desai Prarthna Advani Siddhesh Sarvankar Nikhil Ghate

Autonomous Advertising Mobile Robot for Exhibitions, Developed at BMF

ELEC 5260/6260/6266 Embedded Computing Systems

SuperIOr Controller. Digital Dynamics, Inc., 2014 All Rights Reserved. Patent Pending. Rev:

An Energy-Based Vehicle Tracking System using Principal Component Analysis and Unsupervised ART Network

Synthetic Sensing: Proximity / Distance Sensors

Adaptive Cruise Control System Overview

CHASSIS - 4WD SYSTEM. Realizes stable start-off and acceleration performance

Signature and ISX CM870 Electronics

Implementation of Knock Based Security System

FPGA Implementation of an Advanced Traffic Light Controller using Verilog HDL

Adaptive Cruise Control Unit

Study of Effect of P, PI Controller on Car Cruise Control System and Security

E70 Rear-view Camera (RFK)

Automatic Ration Material Distributions and Payment System Based on GSM and RFID Technology

Mild Hybrids. Virtual

T-REDSPEED White paper

AAA AUTOMOTIVE ENGINEERING

Adaptive cruise control (ACC)

Testimony of Ann Wilson House Energy & Commerce Committee Subcommittee on Commerce, Manufacturing and Trade, October 21, 2015

A Computer Vision System on a Chip: a case study from the automotive domain

Service Manual Trucks

DC Motor Driven Throttle Bodies and Control Valves

Collision Avoidance. The car we couldn t crash! The future for drivers. Compare the technologies. research news

Auto Head-Up Displays: View-Through for Drivers

dspace DSP DS-1104 based State Observer Design for Position Control of DC Servo Motor

Making model-based development a reality: The development of NEC Electronics' automotive system development environment in conjunction with MATLAB

Last Mile Intelligent Driving in Urban Mobility

ADVANCE DRIVER ASSISTANCE SYSTEM BY USING WIRELESS TECHNOLOGY

FEV Parallel Mode Strategy

Low Cost Pure Sine Wave Solar Inverter Circuit

Zigbee-Based Wireless Distance Measuring Sensor System

PLC Based Liquid Filling and Mixing

A PHOTOGRAMMETRIC APPRAOCH FOR AUTOMATIC TRAFFIC ASSESSMENT USING CONVENTIONAL CCTV CAMERA

Science Fiction to Reality: The Future of Automobile Insurance and Transportation Technology

Interfacing with Manufacturing Systems in Education and Small Industry Using Microcontrollers through the World Wide Web

ZF Innovation Truck Turns Maneuvering Long Trucks into a Finger Exercise

JEREMY SALINGER Innovation Program Manager Electrical & Control Systems Research Lab GM Global Research & Development

Research Methodology Part III: Thesis Proposal. Dr. Tarek A. Tutunji Mechatronics Engineering Department Philadelphia University - Jordan

Safety Car Drive by Using Ultrasonic And Radar Sensors

Technical Article. Markus Luidolt and David Gamperl

3D Vision An enabling Technology for Advanced Driver Assistance and Autonomous Offroad Driving

Establishing Great Software Development Process(es) for Your Organization. By Dale Mayes

Electronic Power Control

Optical Fibres. Introduction. Safety precautions. For your safety. For the safety of the apparatus

Operating Vehicle Control Devices

INTEGRATED OPEN DEVELOPMENT PLATTFORM FÜR TEIL- UND VOLLAUTOMATISIERTE FAHRZEUGANTRIEBE

BENEFIT OF DYNAMIC USE CASES TO EARLY DESIGN A DRIVING ASSISTANCE SYSTEM FOR PEDESTRIAN/TRUCK COLLISION AVOIDANCE

System-Level Display Power Reduction Technologies for Portable Computing and Communications Devices

Performance Study based on Matlab Modeling for Hybrid Electric Vehicles

Professional Truck Driver Training Course Syllabus

CHAPTER 3 AVI TRAVEL TIME DATA COLLECTION

BRAKE SYSTEMS 101. Energy Conversion Management. Presented by Paul S. Gritt

Smart Thermostat page 1

The demonstration will be performed in the INTA high speed ring to emulate highway geometry and driving conditions.

Powerchip Singapore Phone : (65) Fax : (65) adrianloh@powerchipgroup.com. Digital Adrenaline For Your Ford Telstar, TX5 2.

DWH-1B. with a security system that keeps you in touch with what matters most

Surveillance System Using Wireless Sensor Networks

E190Q Lecture 5 Autonomous Robot Navigation

AUTONOMOUS VEHICLE TECHNOLOGY: CONSIDERATIONS FOR THE AUTO INSURANCE INDUSTRY

3D Vision An enabling Technology for Advanced Driver Assistance and Autonomous Offroad Driving

HOME APPLIANCES CONTROL SYSTEM BASED ON ANDROID SMARTPHONE

Original Research Articles

A descriptive definition of valve actuators

SEMINAR REPORT 2004 HANDFREE DRIVING FOR AUTOMOBILES

Technology, Safety and ISRI. Garry Mosier CSP VP of Operations Alliance Wireless Technologies, Inc.

A Guide to IR/PIR Sensor Set-Up and Testing

Introduction to Process Control Actuators

Electric Power Steering Automation for Autonomous Driving

INSTRUMENTATION AND CONTROL TUTORIAL 3 SIGNAL PROCESSORS AND RECEIVERS

Optimizing Sortation Throughput in High Volume Distribution Centers

Digital Systems Based on Principles and Applications of Electrical Engineering/Rizzoni (McGraw Hill

Bendix Wingman ACB Active Cruise with Braking Questions & Answers

Accident Notification System by using Two Modems GSM and GPS

Smart features like these are why Ford F-Series has been America s best-selling truck for 37 years and America s best-selling vehicle for 32 years

BEE LINE COMPANY TOTAL VEHICLE WHEEL ALIGNMENT AND THE BENEFITS OF CAMBER CORRECTION

P545 Autonomous Cart

Advanced Vehicle Safety Control System

CYCLOPS OSD USER MANUAL 5.0

Crossrail Vehicle Safety Equipment Supplementary Guidance. Works Information Ref:

OUTCOME 1 TUTORIAL 1 - MECHATRONIC SYSTEMS AND PRODUCTS

How To Fuse A Point Cloud With A Laser And Image Data From A Pointcloud

Stop Alert Flasher with G-Force sensor

Reconfigurable Architecture Requirements for Co-Designed Virtual Machines

Integration of Engine & Hydraulic Controls for Best Operation

Please contact a member of our sales team on

ACCIDENTS AND NEAR-MISSES ANALYSIS BY USING VIDEO DRIVE-RECORDERS IN A FLEET TEST

M.S Ramaiah School of Advanced Studies - Bangalore. On completion of this session, the delegate will understand and be able to appriciate:

WYDOT Quick Facts TRAFFIC SIGNALS

Digital Adrenaline For Your Alfa Romeo V6 24V

Adaptive Driver-assistance Systems

Technical Trends of Driver Assistance/ Automated Driving

Nagpur, Maharashtra, India

Transcription:

Car-Link Enhanced Adaptive Cruise Control By: Graham Allegretto <graham@uvic.ca> David Findlay <dfindlay6@gmail.com> Pelle Bjornert <pelle.bjornert@gmail.com> Maximilian Mclean <mxmclean@gmail.com> Supervisors: Dr. Haytham El Miligi Dr. Fayez Gebali URL: http://web.uvic.ca/~bjornert/car-link/ Group No. 14 Due: December 3, 2012 Dept. Electrical and Computer Engineering University of Victoria All rights reserved. This report may not be reproduced in whole or in part, by photocopy or other means, without the permission of the author.

Table of Contents 1.0.0 Goals... 1 2.0.0 Executive Summary... 2 3.0.0 Indication of Need and Potential Market... 3 4.0.0 Project Description and Discussion... 4 4.1.0 Ranging and Speed Measurement System... 4 4.1.1 Technology Comparison... 5 4.1.2 Ranging System Recommendation... 6 4.2.0 Control System... 7 4.3.0 Mechanical System... 8 4.3.1 Accelerating and Braking... 8 5.0.0 Workload Distribution and Achievements... 9 6.0.0 Summary and Future Works... 12 7.0.0 References... 13 APPENDIX A Logbook... i Supervisor s Comments:... xii Table of Tables: Table 1: Comparison of Range Finding Technologies... 5 Table of Figures: Figure 1: Computer Vision Distance Measurement [2]... 6 Figure 2: Control System Block Diagram... 8 ELEC/CENG 399 Final Report

1 1.0.0 Goals Our primary goal for the Car-Link ELEC 399 project was to explore the possibilities and challenges incorporated with developing Adaptive Cruise Control. Adaptive Cruise Control is a more advanced type of Cruise Control which can detect the speed and distance between itself and the vehicles in front of it and respond with both acceleration and braking. Our belief was that having a computerized system to assume this aspect of driving a car could potentially lead to a more efficient traffic flow. We explored different hardware options that could ultimately perform the above tasks. These included identifying and ranging cars and determining a suitable response from those stimuli. Additionally, our group needed to determine how we can incorporate our system into the existing braking and acceleration systems on production vehicles. Various hardware choices and implementations were considered. The advantages and disadvantages of each alternative were thoroughly considered and a final design was identified. The outcome of the Elec399 project has given a design that can be implemented in Elec499.

2 2.0.0 Executive Summary Enhanced Adaptive Cruise Control (EACC) is the first step in automating motor vehicle travel, providing numerous benefits for both drivers and traffic. While EACC is essentially an aid to conventional cruise control, it differs in that when on the road it maintains a safe distance from other cars by detecting vehicles directly ahead, measuring their distance and relative speeds, and appropriately applying the throttle or brake. With EACC the driver decides on the speed, and the system allows the vehicle to continue at that speed until another vehicle is approached in the same lane. EACC has started to make its way into the market, but a great deal of its potential is still largely untapped and undeveloped, especially in the aftermarket sector. The Car-Link UVic product will tap into this market by developing an aftermarket adaptive cruise control system. It will do so using proximity and object detection, a series of servos for mechanical control as well as a dashboard mounted interface device. The proposed system will remove human error, increase road capacity and reduce the occurrence of traffic jams and rear end collisions [1], [3].

3 3.0.0 Indication of Need and Potential Market Roadways are becoming more congested in city centers and accidents are an everyday risk that nearly everyone takes on their daily commute. The current protocol to combat congestion is to widen roadways, an option that is extremely expensive and in many cases, impractical. A second approach, seldom considered, is to improve the way the vehicles travel and react to changing conditions. The speed at which traffic flows is dependent on many variables, a significant one being the driver. Drivers come in many different forms, from the ultra conservative to the overly aggressive. Depending on the drivers dispositions, they can unintentionally contribute to congestion. For example, if a driver is tailgating, and the car immediately ahead lightly applies the brakes, the tailgater may overcompensate by slamming on their brakes. The car behind the tailgater will notice that the car in front is slowing down at an alarming pace and will also apply the brakes, usually beyond what is necessary. When this occurs repeatedly over a long length of cars, gridlock ensues. The slight tap on the brakes by the lead car propagates throughout the line of cars resulting in a dead stop further down the line. The leading factors contributing to this unnecessary event can be attributed to a driver s limited reaction time, tailgating, and overcompensation. By removing the driver from controlling the vehicle s acceleration and braking, inherent human limitations will also be removed. This not only has the effect of speeding up traffic but will also limit rear end collisions and enhance driver convenience. The benefits of removing the driver and replacing them with an adaptive cruise control system has been identified long ago and studied in depth. One study simulated a roadway full of manually controlled vehicles with a proportion being controlled by EACC systems. It was found that when only 20% of the vehicles in the simulation were controlled by EACC systems, traffic jams were entirely eliminated [3]. A similar study found that even an EACC equipment level of 5% improves the traffic flow quality and reduces the travel times for the drivers in a relevant way [4]. These findings have not gone unnoticed; the majority of major auto manufacturers have taken note and have developed their own versions of adaptive cruise control. Adaptive cruise control systems have been in some production vehicles since 1999, and are found in a greater percentage of vehicles each year [5]. According to a report completed by Global Industry Analysts Inc., EACC systems will exceed 6.9 million units by 2017 [6]. Systems will become more common in mid-range vehicles resulting in greater public awareness of the benefits of EACC. Since these systems will only be available as features in brand new vehicles, demand for an aftermarket system will likely follow. Current companies offering EACC systems include Delphi and TRW. Their primary customers include large auto manufacturers such as Ford and Volkswagen yet they do not currently offer a consumer aftermarket product. The EACC system proposed will be able to be installed on any automatic vehicle with a digital vehicle speed sensor, filling a niche that other companies have yet to develop.

4 4.0.0 Project Description and Discussion The proposed EACC system is an independent aftermarket module with the ability of being installed on all makes and models of vehicles, provided they have an automatic transmission and a digital vehicle speed sensor. By removing the driver from controlling a vehicles throttle and braking, driver related errors affecting the flow of traffic can be removed. This system has the potential to increase the capacity of roadways, decrease the number of rear end collisions, and decrease fuel consumption on the Car-Link equipped vehicle [1]. The driver will determine the speed at which they want to cruise at and the system will maintain that speed until it approaches a car in the same lane. The EACC System will determine a safe distance between it and the car immediately ahead, and will adjust its speed accordingly. As soon as the car in front changes lanes or speeds up, the Car-Link equipped vehicle will accelerate to maintain the initial speed specified. The Car-Link EACC system will only operate in speeds lower than 60km/h and will only control the vehicle s acceleration and braking steering is left to the driver. With increased speeds, the computing requirements drastically increase along with risks involved. Also, as speed increases, as does inter-vehicular spacing. Corners will need to be taken into consideration, resulting in a greater difficulty identifying vehicles ahead in the same lane as the installed vehicle. At lower speeds, the vehicle immediately ahead will be easily identifiable and corners will have negligible effects. The EACC system will consist of various subsystems; the ranging system will determine the distance to the vehicle immediately ahead, and the speed measurement system will determine the current speed of the Car-Link equipped vehicle. The control system will receive input data from the ranging and speed measurement systems and determine appropriate actions resulting in output signals to the mechanical system. The mechanical system will then apply braking and acceleration accordingly. This section describes different implementations for the various systems listed above and a recommendation for each subsystem. 4.1.0 Ranging and Speed Measurement System Arguably the most critical subsystem for EACC system is that of Ranging and Speed Measurement. How much the vehicle must accelerate or brake to maintain the preset speed or a safe distance is dependent on the vehicle s current speed and the distance between it and the vehicle immediately in front of it. If this subsystem fails or outputs inaccurate readings, the results could potentially catastrophic. This section includes a comparison of different alternatives and gives a recommendation based on each of the implementations advantages and disadvantages.

4.1.1 Technology Comparison This section compares various technologies that can be implemented for the ranging system. The range finding technologies investigated were RADAR, laser range finding, and computer vision. The contents of this section were used to determine the most ideal ranging system. The Laser Range Finder and RADAR systems were based on premade sensors that are available on the market. The RADAR system considered was Continental s ARS 300 Long Range Radar Sensor (77 GHz). This system was designed for applications that are similar to the task at hand. The Laser Range Finder system investigated was Electro-Optic Devices ERC-2KIT. This system includes all of the control circuitry for time-of-flight measurements including an optical receiver and a ranging controller. The Computer Vision scenario was not based on a single system as there are no premade systems that could be used for this application. Many of the vision-based properties are estimates since they will be highly dependent on software and camera choice. It should also be noted that there are many IEEE peer-reviewed articles that investigate a visionbased ACC system. Table 1: Comparison of Range Finding Technologies Laser Range Finder RADAR Computer Vision Range >100m 0.25 200m <60m 5 Field of View Readings per Second Single point 150Hz 56 degrees short (60m) 17 degrees long (200m) 15Hz Dependent on camera lens Dependent on algorithm and CPU Advantages - Very fast - Relatively cheap - Accurate - Stand alone system - Large Field of view - Real-time analysis - Reveals relative speed - Extremely cheap - Wide viewing angle - Easily customizable - Class offered in field - Image processing software available Disadvantages - Single dot - Mid range cost - Will require scanning - Extremely expensive - Outputs to CAN bus - Very expensive computing wise - Intensive image processing required - Relatively inaccurate

6 Cost $450 $3900-4000 $200+ 4.1.2 Ranging System Recommendation After much debate, the decided upon ranging system will consist of a laser range finder coupled to a computer vision system. The computer vision system will detect vehicles and also return crude distance measurements where the laser range finder will confirm or negate the results. A detailed system overview is listed below. 4.1.2.1 Computer Vision Studies have found that a single forward looking camera coupled with image processing can be used to solely as the ranging system for an Adaptive Cruise Control system [2]. Figure 1: Computer Vision Distance Measurement [2] Prior studies referenced above have proven that using a vision-based ranging system is a practical and relatively cheap alternative for EACC systems. The concept of using a computer vision ranging system is relatively simple. For the EACC application, the camera is placed at a predetermined height, most likely on the roof of the vehicle directly in front of the windshield. By applying concepts of pattern recognition and edgedetection, vehicles immediately ahead can be identified. Assuming that the point at which the lead vehicle meets the road, either the tires or below the bumpers, the distance in pixels is measured between that and the absolute center pixel. By applying the equation below, where f refers to the camera s focal length, a distance can be estimated refer to Figure 1. The major expense for a computer vision system is in implementing the appropriate algorithm. Algorithm development will be done using MATLAB and then the application will be ported to a field programmable gate array (FPGA) for increased processing speed and to reduce the workload of the control processor. The computer vision device will be aided by a laser range finding system to produce more accurate and verified results.

4.1.2.2 Laser Range Finding System A laser range finding system will be used in conjunction with computer vision to obtain more accurate readings of distance from the Car-Link equipped vehicle to objects in front of it. Three laser range finding devices will be mounted on the front of the vehicle, one in the center, and one below each headlight. The range finders will detect objects to the left, right, and directly in front of the vehicle. When the computer sees an object ahead, it chooses the laser best suited to detect the distance. The laser device proposed for the Car-Link system will use a time-of-flight measurement technique where a pulse is sent from the laser (at frequencies safe and non-detectable to the human eye ~850nm) and the time for the pulse to travel to the target and back is recorded. From this time the distance may be calculated by knowing the speed of light. This type of distance measurement is found to be ideal when coupled with a computer vision system. It is relatively inexpensive compared to other systems such as RADAR and maintains a high degree of accuracy. 4.1.2.3 Speed Measurement In order to make precise calculations for the minimum safe distance between the Car- Link equipped vehicle and the one directly in front, it will be necessary to have an accurate value for the speed of the vehicle. Luckily all cars are equipped with a speedometer and for most vehicles post 1990, the speedometer is driven by a square wave pulse train. To utilize this output we hope to split the signal before the dashboard speedometer and feed it into our computer where it will be used for the minimum safe distance calculation. Systems like this are already in place with taxi cab metering and based on initial research, are relatively easily implemented. 4.2.0 Control System The control system will determine safe following distance dependent on the current distance to the vehicle immediately ahead and the current speed of the vehicle. Utilizing a PID controller, this system will determine how much the installed vehicle will need to accelerate or brake in order to maintain the safe distance. An idealized system is shown in Figure 2. To implement this control system, there are several different microcontroller alternatives. In today s market there is a nearly infinite amount of choices for microcontrollers and prototyping platforms. The Arduino prototyping platform with an Atmel microcontroller is a viable option that is both cheap and readily available. If the project was turned into a marketable project we would most likely attach just a microcontroller to a circuit board design of our own. 7

8 Figure 2: Control System Block Diagram 4.3.0 Mechanical System This system consists of the mechanical components of the proposed product. This section is primarily concerned with applying pressure to the brake and accelerator pedals. 4.3.1 Accelerating and Braking In order for the system to function as specified we need to take control of the braking and acceleration of the vehicle. This will be accomplished by using a series of servos that will pull the brake and throttle peddles. In contrast to the large area linear actuators demand, DC servos are small and compact for the power and control they can provide. For the application of this project, it is envisioned that the DC servo for the brake pedal would be mounted below the pedal, and would attach to the control arm via a chain. In a braking situation the servo would apply a force to the chain thus pulling the pedal towards it. The application of the chain would not impede normal function of the pedal in situations when the product was deactivated. In contrast, the servo for the throttle would likely be mounted in the engine much like the current systems in place for normal cruise control. Servos were decided upon over actuators based on their small size and accuracy. Actuators would require a substantial amount of modification of the vehicle in order to accommodate their large size. Although, actuators are cheaper than servos, the difference in price between the two technologies is negligible in comparison to the amount of work that would be required to install servos. Another benefit of servos are their ability to measure disturbance torque. To deactivate the ACC, the driver simply has to press on the brakes. The servo will report a disturbance torque which can be used to disable the ACC.

9 5.0.0 Workload Distribution and Achievements At the beginning of the term in September 2012 the student group Car-Link was formed to investigate the design of EACC systems. For the overall project a group advisor is required as per ELEC 399 requirements and thus Dr. Fayez Gebali was contacted to fill this role. From here Dr. Haythem El Miligi also became involved and it was decided weekly meetings were required to ensure proper flow of project tasks and therefore minutes could be kept for proof of project progress. Outside of the formal meetings held with Dr. Gebali and Dr. El Miligi group meetings amongst the team members were held to determine the work-load required by each person and the deliverables for the following week s meeting(see Appendix A post Oct 31, 2012 Meeting). An overall gant chart was produced to ensure the ELEC 399 course s objectives were met as well as several opportunities for the project were listed. This chart may be seen below: Figure 3: Initial Gantt Chart As with any project objectives may change and the group must be dynamic enough in its work flow to adapt to changes in requirements. Throughout the term it was decided that a fine tuned algorithm was not required as well as a prezi presentation. The reasons for these two pivots are the fact that an animation would show the idea or algorithm to the general public better than a complex block diagram. However, a simple block box description of the project was created. The prezi presentation was eliminated from the scope of work when it was found that an intro on the website may be just as effective without requiring a Prezi embedded into the website. While the Prezi presentation was taken off the requirements for before the end of the term it may still be required for future work or funding opportunities. To balance the tasks specific to the objectives of ELEC 399 the following breakdown was created to ensure each team member was used to his full ability: Graham Allegretto: Technology Research Director: responsible to delegate research duties to each group member on different technologies used for the project. Computer Vision researcher: responsible with designing an overall Car-Link system using computer vision as the sensing technology by end of November Contribute findings and research to overall final report

David Findlay: Funding Research Director: responsible for assigning tasks to group members regarding funding opportunities LIDAR and Microcontroller Researcher: responsible with designing an overall Car-Link system using computer vision as the sensing technology by end of November Contribute findings and research to overall final report Pelle Bjornert: Website Design Director: Responsible for website and animation design and delegating tasks and events associated with this. Contribute findings and research to overall final report Creating animation to show what Car-Link would be capable once implemented Max McLean: Project Flow Director: responsible for taking and distributing meeting minutes and notifying group of shortcomings and deadlines/requirements. (Also a collaborative effort) RADAR Researcher: responsible with designing an overall Car-Link system using RADAR as the sensing technology by end of November Responsible for term logbook Contribute findings and research to overall final report With the above defined roles in the project each group member was able to know what is required of them and when help was required from the other team members it was an easy delegation. This system took time to develop as each team member needed to assume a role that was not pre-defined. However, for future work on the Car-Link system the roles listed above allow for efficient and effective workflow and proved to be during the latter half of this term. The Car-Link team s success is measured in the quality of the documents produced as well as the team member s personal advancement. Overall the quality of the documents produced was to a high standard and the team members were pleased with this success. The Car-Link system design was another notable success of the Car-Link team as there were multiple challenges to overcome including personal time conflicts and project management. The design of a realizable system was also in our project goals and therefore it was achieved. On short notice it was found that the Wighton Fund Proposal was an excellent opportunity for funding should this project be realized in ELC 499. Once this idea was on the table a lengthy document explaining the need for such a system and the overall costs for a prototype were submitted within 48hrs. This is also an undeniable achievement of the whole group to work collaboratively to meet an unexpected deadline. Ultimately the team learned a great deal about the design of EACC systems and how to implement them. Furthermore, the general ability to apply the design sequence and project management learned during this project to other projects in the future will be a 10

valuable contribution. ELEC 399 gave the team members the ability to design a technical system that solves an everyday problem while doing so with peers and professors in a supportive environment. 11

12 6.0.0 Summary and Future Works This report outlines the fundamentals of the Car-Link system proposed. We outlined the goals we started out with and the hardware options and potential capabilities of the system. This included the numerous options available for detecting the cars in front it and the visions systems needed in order to make the car aware of the existing conditions and environment. We also explored the available possibilities for controlling the acceleration and braking of a car. The report also introduces the initial concept for the control system governing the sensors and outputs. The system proposed by Car-Link utilizes many different advanced technologies. As a result this project will require a significant funding investment. For this reason we took the opportunity to apply for Wighton Engineering Product Development Fund. This fund exists to make funds available for further development of promising ideas and final projects towards commercial exploitation. This could provide our group with up to $5000 in assistance toward development. For this reason our team submitted a proposal which incorporated much of the research included in the report. We will continue to utilize the information we complied during ELEC 399 to pursue additional funding opportunities. In order to develop this system we also require the use of a vehicle to develop this product with. We believe that because of the potential ecological benefits we may have an opportunity to work with the Eco-Car student group at UVIC. There is great potential for mutual benefit with Eco-Car. Car-Link will get a car to develop the product and Eco- Car will end up with a more ecologically friendly vehicle. We will be working to foster a relationship with Eco-Car. The complexity of this system is great and as a result there is a much greater understanding required about some of the components. Primarily this will be the computer vision portion of the project. This report outlines the basic method of implementing range finding in with computer vision but there is potential for a large environmental awareness provided with computer vision. We also need to determine the processing power the system will require. Our group must work to develop a higher understanding of this technology. We will also be working toward realistically modeling traffic so we can tune our control algorithms.

13 7.0.0 References [1] W. D. Jones, Keeping cars from crashing, IEEE Spectr., vol. 38, iss. 9, pp. 40-45, Sept. 2001. [2] G. P. Stein et al., Vision-based ACC with a Single Camera: Bounds on Range and Range Rate Accuracy, in Intelligent Vehicle Symposium, 2003 IEEE, doi: 10.1109/IVS.2003.1212895. [3] L.C. Davis, Effect of adaptive cruise control systems on traffic flow, J. Phys. Rev. E, vol. 69, 06110, Oct. 2003. [4] Trieber et al., Adaptive cruise control design for active congestion avoidance, J. Transportation Research Part C, vol. 16, iss. 6, pp. 668-683, Dec. 2008. [5] W. D. Jones, Keeping cars from crashing, IEEE Spectr., vol. 38, iss. 9, pp. 40-45, Sept. 2001. [6] Global Adaptive Cruise Control Systems Market to Reach 6.9 Million Units by 2017, According to New Report by Global Industry Analysts, Inc. PRWeb, Available at: http://www.prweb.com/releases/adaptive_cruise_control/acc_systems/prweb923 8040.htm

i APPENDIX A Logbook During the term, meetings were held each week with the Car-Link group long with advisors Dr. Gebali and Dr. El Miligi. The following documents show the meeting minutes that where generated from each of the weekly meetings. This serves as our logbook for the term.

Car-Link Weekly Meeting ii Attendance: G. Allegretto (GA), D. Findlay (DF), M. Mclean (MM) Apologies: P. Bjornert (PB) Date: Sepember 18, 2012 Meeting Number: 1 Project Details: Car train using wireless links Definition/Practical Uses : Car will stay a set distance away from an object in a straight line Speeding up traffic by eliminating driver lag between stop and starts. Reducing the occurrence of rear-end accidents. Equipment/Info Needed: Arduino microcontroller platform. One or multiple electric car (models) that may be controlled Research implementation Action Responsibility Deadline Complete: Obtain Arduino controller. Bring to Next meeting. Research Electric Car Models (Bring findings to next meeting) Research Communication Systems (Bring findings D. Findlay Sept 25, 2012 CMP GA/MM/DF Sept 25, 2012 CMP GA/MM/DF Sept 25, 2012 CMP

to next meeting) iii Get supervisor (Possibilities: Fayez Gebali Reuven Gordon Agathoklis KFL) MM to Email CC group. Sept 25, 2012 CMP Website find out about hosting source through University (DF) How to build a website/ examples of how past groups have built them (PB) DF/PB Sept 25, 2012 CMP

Car Link Weekly Meeting iv October 03, 2012 Attendance: Graham Allegretto, Mac McLean, David Findlay, Pelle Bjornert, Dr. Gebali, Dr. El Miligi, Dr. Li Defining Project Ideas: A system that will speed up traffic and reduce the amount of rear end accidents by utilizing wasted road space. To be achieved either on a individual basis using various sensing technology or by using a network and defining a protocol on which cars will communicate (VAN). Key discussions of Ideas: Car will remain individual without a network however the ability to implement a network at a future time is open for discussion Various sensing technologies include laser, infra-red, sonar etc. Staying away from laser technologies as there could be numerous difficulties with this Other companies/agencies working on similar technology include Honda and a visual based system AutoNOMOS from Germany To Do before next meeting: Define all project specifications including: I/O and Communication Power Requirements etc. Gant Chart (time definitions Max) What exactly is to be implemented for ELEC 399? Alternatives for this technology ie find out what is lacking in other technologies and define what ours should achieve from looking at deficiencies

Car Link Weekly Meeting v October 10, 2012 Attendance: Graham Allegretto, Max McLean, David Findlay, Pelle Bjornert, Dr. Gebali, Dr. El Miligi, Main Discussions: System specification document: 1. Update title page 2. Specific technologies required for each specification 3. Numbered bullet points 4. Mention VAN (network) system Midterm Report/ Logbook: 5. Include motivation 6. Literature search 7. Target Technologies 8. Logbook to include all relevant project details and timelines Algorithm: 9. Develope using black box approach (simply inputs and outputs) 10. Further refine this algorithm once most simple approach in made Implementation: 11. Simulator to show wave aspect of cars breaking (possible use in driving instructional sessions) 12. Use simulator to get hard numbers for the motivational section of report Deliverables for October 17, 2012: - Gantt Chart outlining project deadlines and to dos - Algorithm: refined black box - Possible technologies used for input and outputs - Literature Search - Midterm Report - Spec document updates

Car Link Weekly Meeting vi October 17, 2012 Attendance: Graham Allegretto, David Findlay, Pelle Björnert, Dr. Gebali, Dr. Li, Main Discussions: Further streamlining project goals: 1. Need to determine exactly what the system specifications will be a. Highway system/high speed? b. City system/low speed/stop and go? c. Congestion automation 2. Sensors and implementation will be different depending on specifications 3. System intended for strait line only or corners as well? 4. Will the system be able to exceed the speed limit? Safety and Security 5. To gain the publics trust, the system must be failsafe 6. Considerations of how we will test and verify our system 7. Design test verify 8. Is the system vulnerable to hacking? Hardware 9. Current (similar) systems using LIDAR 10. Drive by wire systems 11. Brake systems currently available? Hydraulic, electromagnetic, etc 12. How could we mechanically actuate the brakes? Implementation 13. How will the system be? a. Activated b. Deactivated 14. When more cars are fitted with this system, will traffic patterns improve; emissions decrease; road rage decrease? Etc Deliverables for October 24 th, 2012: - Research brake system, types, actuators, control etc - Streamline project goals

Car Link Weekly Meeting ELEC 399 vii October 24, 2012 Attendance: Graham Allegretto, Max McLean, David Findlay, Pelle Bjornert, Dr. Gebali, Dr. El Miligi Key discussions: 1. To go ahead with specific versions which will advance in development difficulty and performance 2. Reason for 60km/hr discussed as range to price ratio not favourable and difficulty navigating curvey high speed roads 3. Saanich Smart Road ideas for future. To discuss with Saanich if time permits 4. Overall deliverable for ELEC 399 may include report on RC Car vs actual car implemtation 5. What is to be carried out in ELEC 499 as a final deliverable? RC demo, Simulation, Actual Car with video presentation? Deliverables: What will be report topic for ELEC 399 deliverable Furthermore what is final deliverable in ELEC 499 Time permitting discussion with Saanich on smart road technology

Car Link Weekly Meeting viii Oct 31, 2012 Attendance: Graham Allegretto, Max McLean, David Findlay, Pelle Bjornert, Dr. Gebali, Dr. El Miligi, Main Discussions: Technologies: 1. Breaking: - Actuator on brake pedal - Actual depression of brake pedal - Valve on vacuum? No 2. Sensing Distance: - Near infared - Array of lasers (15) used in other sensing technologies - Disassembling Realtor measurment device - Either sensor only or whole detecting package (whole detecting package preferable) 3. Accelerator: - Drive by wire (tap into the accelerator signal from the gas pedal) No steering will be involved in this version (ie V1) To discuss current technologies with SAE at Uvic discuss with Eco-Car Funding will be required for Actualization: 1. Possible Funding ventures include: - City of Saanich Roads - ICBC - Honda/Other Car Dealers - Competitions such as pitchit/planit - Other local technology/ car companies 2. Dr. Gebali to speak to Technology company The Funding ventures may be discussed in the next meeting with possible oppourtunites for advertisement etc.

Car Link Weekly Meeting ix Nov 7, 2012 Attendance: Graham Allegretto, Max McLean, David Findlay, Pelle Bjornert, Dr. Gebali, Dr. El Miligi, Main Discussions: Technologies: 1. Compare and contrast different sensing technologies 2. Specify set of assumptions for a vehicle in the final report No steering will be involved in this version (ie V1) Project Outcomes: 1. To be able to discuss Eco-Car add-ins with Dr. Zuomin Dong when final report finished. - Possibilty to audit the Eco-Car course - Get help from other students working on the Eco-car 2. A animation explaining our idea and how it improves upon current traffic Group member Tasks for next meeting: 1. Analyze a specific distance sensing technology and report on findings to produce a accurate compared and contrasting document: a. Graham Allegretto Computer Vision b. David Findlay Time of Flight c. Max McLean Radar 2. Create a website and animation displaying our systems benefits Pelle Bjornert

Car Link Weekly Meeting x Nov. 21, 2012 Attendance: Graham Allegretto, Max McLean, David Findlay, Pelle Bjornert, Dr. Gebali, Dr. El Miligi, Main Discussions: Technology Discussion: 1. With a list of the different sensing technologies available a benefit to cost ratio was analyzed the result was: - To use computer vision coupled with a distance sensing laser. Best option for the price and practical implementation - To understand the workings of computer vision a course may be taken in January 2013 on this topic. In addition this course has a project section where, if possible, a partial art of the Car-Link system may be complete 2. With a more finalized design for the Car-Link system (At the end of ELEC 399) discussions with Dr. Zuomin Dong and the Eco-Car Team/ Course may be had as far as suggestions and continuation of the Car-Link Project incorporated into Eco-Car 3. Various other articles on similar ACC systems were explored and discussed (A paper given to the group by Dr. Gebali) Funding: 1. The Wighton Fund was discussed in detail and the group decided to submit an application by the deadline of Friday Nov. 28, 2012. - It is noted that other funding opportunities may match what is given by the Wighton Fund so this oppourtunity could yield good results for the project (Max, Graham, Pelle/David to work on this before Friday) David to research other funding opportunities for future Discussion Topics for Next meeting and deliverables: - Final Report contents - Funding Proposal discuss on how well this was implemented and what could be improved upon for future proposals - Website - Final meeting for ELEC 399. Other deliverables for future work etc?

Car-Link Weekly Meeting xi November 28, 2012 Attendance: Graham Allegretto, Max McLean, David Findlay, Pelle Bjornert, Dr. Gebali, Main Discussion: 1. What to include in the final report for ELEC 399 2. Ideal deliverables for ELEC 499 given a go ahead with the system: - Video of operating system along with simulation - Implemented with Eco-car team ( ideally) 3. Overall project completeness and accomplishments: -designed a theoretical system -underwent various project pivots to allow for design issues such as capital limitations -applied for capital with the Wighton Fund Proposal Final Deliverables for ELEC 399 Dec 3, 2012: - Graham Allegretto Final Report Skeleton and Body - David Findlay Final Report Skeleton and Body - Max McLean Logbook - Pelle Bjornert Website finishing touches and animation

Log book grade (25%): Report grade (75%): Total Grade (100%): xii Supervisor s Comments: Supervisor s name (Print) Signature Date Notes for the supervisor: 1. Please return the marked hard copy to Prof. Tao Lu by Monday, December 10. 2. Attached additional pages for comments if necessary.