PRE2016 1 Groep2

Updating the Current Intersection System to be Compatible with Autonomous Vehicles.

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Group members

• Lisanne van Wincoop (0849855)
• Jeroen van Dongen (0889788)
• Sjoerd Westendorp (0864518)
• Rodger van der Heijden (0851985)
• Johan Hendriks (0824890)

Introduction

updated

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,

After receiving feedback on our second idea, we had a long discussion with Mr. Borghuis. To address all the points in the criticism received: unrealistic assumptions, no contribution, little USE, why 100% autonomous cars. We came up with an idea to update current intersection systems to encorporate autonomous vehicles. The project idea allows a realistic intermediate solution in the process only allowing autonomous cars in traffic.

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 intersections^{citation 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

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Main objective:

• Optimizing traffic flow at intersections by making them compatible with autonomous vehicles.

Objectives:

• Using sensor data from autonomous cars to make traffic light algorithms more aware of current traffic
• 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.
• Create a transition solution that can combine the use of autonomous cars with human drivers by using the current intersection system.
• 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

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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

Sources and References

Sources

• A Multiagent Approach to Autonomous Intersection Management.
• Decoupled Cooperative Trajectory Optimization for Connected Highly Automated Vehicles at Urban Intersections.
• A review on agent-based technology for traffic and transportation.
• Microsimulation analysis of automated vehicles on multiple merge junction highways
• A Review of the Applications of Agent Technology in Traffic and Transportation Systems

Collaboration

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

Week 2

• Give presentation
• Dividing tasks
• Start frontend simulation
• Start literary review

Week 3

• Give presentation
• Literary review done
• Start creating algorithm

Week 4

• Think about link between autonomous cars and intersection
• Start backend simulation

Week 5

• End creating algorithm

Week 6

• Finalize simulation

Week 7

• Evaluate simulation results

Meetings and weekly planning

A record of all held meetings can be found here.