PRE2016 1 Groep2: Difference between revisions
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= Introduction = | = Introduction = | ||
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On day 1 our idea for a project was to build a small robot that could teach itself to walk by using self learning AI. This idea was quickly abandoned when it was brought to our attention that these already exist. We were also unable to combine lots of USE aspects with the idea. | On day 1 our idea for a project was to build a small robot that could teach itself to walk by using self learning AI. This idea was quickly abandoned when it was brought to our attention that these already exist. We were also unable to combine lots of USE aspects with the idea. | ||
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Our main focus area concerns <u>Automated traffic regulation (ATR)</u>. | |||
Narrow that down is our specific focus: <u>Updating the Current Intersection System to be Compatible with Autonomous Vehicles (Vehicle Intersection Control).</u> | |||
Restrictions on the focus area: | Restrictions on the focus area: |
Revision as of 10:57, 16 September 2016
Updating the Current Intersection System to be Compatible with Autonomous Vehicles.
Group members
- Lisanne van Wincoop (0849855)
- Jeroen van Dongen (0889788)
- Sjoerd Westendorp (0864518)
- Rodger van der Heijden (0851985)
- Johan Hendriks (0824890)
Introduction
On day 1 our idea for a project was to build a small robot that could teach itself to walk by using self learning AI. This idea was quickly abandoned when it was brought to our attention that these already exist. We were also unable to combine lots of USE aspects with the idea.
The next idea was investigate algorithms of intersections with only autonomous vehicles and to build a simulation of it. We could compare different algorithms and decide in which was best in certain situations. The problem was that it didn't contribute to real world scenarios because lots of algorithms used unrealistic assumptions, including: all traffic must be autonomous and there is no packet-loss in communication between car and intersection,
- Updating the Current Intersection System to be Compatible with Autonomous Vehicles.
Focus
updated
Our main focus area concerns Automated traffic regulation (ATR).
Narrow that down is our specific focus: Updating the Current Intersection System to be Compatible with Autonomous Vehicles (Vehicle Intersection Control).
Restrictions on the focus area:
- Crossing has 4 directions.
- Traffic is randomly generated, the ratio between autonomous and normal cars will be changeable.
A multitude of traffic accidents happen at intersectionscitation needed. These are also the bottlenecks in terms of efficiency since human drivers have varying reaction times. Drivers can also get stressed behind the wheel and lose valuable time while commuting. Contemporary intersection could make traffic more efficient by utilizing data from sensors of autonomous cars and controlling autonomous cars passing the intersection. By making the intersections smarter, user comfort can be greatly increased. Also society will benefit from more efficient driving past intersections, since emissions can be greatly reduced, which benefits the environment. Enterprises will also be positively influenced, since people will be able to get to work quicker instead of being stuck at an intersection.
Objectives
updated
Main objective:
- Optimizing traffic flow at intersections using autonomous cars.
Objectives:
- Using sensor data from autonomous cars to enhance the traffic lights.
- Choose a suitable communication protocol between autonomous cars and the intersection.
- Find existing efficient algorithms for autonomous cars at intersection in a literary review
- Combine said algorithm with current traffic light algorithms to optimize traffic flow of both normal and autonomous cars.
- Make sure the traffic flow is optimal, which results in less waiting time and less emission.
- Contributing to the transition of partial participation of autonomous cars in traffic to full participation. needs tweaking
- Keep in mind the perception of safety and the actual safety of passengers inside the autonomous cars.
- Decrease the number of traffic accidents involving cars on crossings.
Approach
updated
The approach that is chosen is research and simulation oriented. Most information on existing solutions must come from literature and ongoing research. By identifying the state of the art, we will try to combine traffic light algorithms with algorithms that only work with 100% autonomous cars at the intersection. When such combination has been made, a simulation will be created and tested, after which an evaluation will follow.
Literature review
Intersection algorithms now
Alles 100% normaal verkeer Kruispunten nu
== Sensor and communicationsystems of autonomous cars Sensoren en communicatiemogelijkheden van autonome auto's van nu
Existing communication systems in traffic
Communcatie systemen (bussen/ambulances) nu met kruispunten
Milestones
- Literature review
- Kruispunten nu
- Sensoren en communicatiemogelijkheden van autonome auto's van nu
- Communcatie systemen (bussen/ambulances) nu met kruispunten
- Koppeling tussen kruispunt en autonome auto
- Algorithme / simulatie
- Algorithme (backend)
- Visualisatie (frontend)
- Test
- USE aspecten (doorlopend) Doen we dit in een enkel hoofdstukje of komt het terug in het gehele verslag?
- Evaluation of Simulation
- Wiki
- Presentatie
- Final simulation
Planning
- Presentatie maken/voorbereiden/geven: Lisanne
- Literatuurstudie: kruispunten nu: Rodger
- Frontend simulatie(visualatie)+ literatuurstudie sensors en communicatie van autonome auto's nu. Sjoerd
- FOCUS, objectves aanpassen, planning maken, milestones/deliverables/whowilldowhat/uren budget, wiki bijhouden: Jeroen
- Communicatiesystemen in kruispunten nu: Johan.
USE Aspects
User
User need
- Primary Users
- Secondary Users
- Tertiary Users
User impact
- Primary Users
- Secondary Users
- Tertiary Users
Society
Need
Impact
Enterprise
Need
Impact