PRE2019 4 Group8

PRE2019 4 Group8

Group Members

Name	Student ID
Sietse Backx	1255924	s.backx@student.tue.nl
Rien Boonstoppel	0946480	d.j.boonstoppel@student.tue.nl
Luc Geurts	1237117	l.p.a.geurts@student.tue.nl
Mandy Grooters	1236053	m.grooters1@student.tue.nl
Tar van Kieken	1244433	t.m.k.v.krieken@student.tue.nl

Introduction

Visiting a theme park or a festival can be a great stress relief. However, what is worse than to start a relaxing event with trying to park your car in what seems to be a never-ending, saturated parking lot. Event parking is a key issue in society nowadays. With occasional large social gatherings, parking demand often does not meet supply. In combination with a shortage in parking staff, congestion results leaving drivers with frustration.

When organizing a large scale event, there are several key aspects to take into account with regard to transportation and vehicle placement or traffic management in general. The first key bottleneck to consider is the road capacity [1]. Accessibility to event sites is often limited due to the fact that the location was not designed for large events. Next to that, cost is an important factor when planning an event. In most cases, it would not be sensible to construct a parking lot for a single event. Finally, the time scale of an event is important. Can visitors arrive over the course of several days or mere hours? In order to create an effective event transportation plan, the traffic bottlenecks need to be dealt with. The first measure to optimize the transportation, is to create travel capacity. This can either be done by reducing transport system demand or by increasing capacity. For instance, if the event is planned during a holiday, more transportation facilities such as buses are available to be used for the special event. A second approach is to inform visitors that transportation and parking will take considerable time. Essentially, by conveying a warning, visitors might decide to arrive earlier which spreads demand peaks. Another improvement is to take traffic efficiency measures. For example, by using traffic signals to favor the event traffic flow, delays can be reduced. Additionally, travel bans can be implemented to open capacity for event traffic. Finally, the emphasis should be on public transportation to prevent parking issues in the first place [2]. If all these measures still lead to congestion, a new solution must be found.

Analogously with large events, in large cities, parking is also a considerable problem. Nearly 30% of traffic congestion in cities is caused by drivers looking for a parking spot [3]. Designing a parking system such that drivers can find a parking faster is therefore essential. Common solutions involve a LED system to indicate free and occupied parking spaces, however, these solutions do not control traffic flow. Another option which does take into account traffic flow is automatic parking spot assignment. Automatic parking assignment can compute optimal routes taking into account lot occupancy, travel distance, conflict avoidance and walking distance [4]. Nonetheless, this solution is limited to mobile phone use.

Subject

A robotic parking assistant which helps drivers to find a parking spot and simultaneously optimizes traffic flow for faster parking.

Problem Statement

In summary, the key issues to resolve are the enormous rise in demand of parking spaces with special events and the inadequate parking management. These issues result in congestion and frustration of drivers due to the delay suffered from finding a parking space.

Objectives

The purpose of this project is to design a robot which interacts with drivers so to optimize car park traffic flow and car positioning.

User, Society and Enterprise

The primary users of the parking robot are companies that are dealing with large parking lots. Such as theme parks and festival organizations. These companies want to improve the experience of their visitors by avoiding parking problem. The parking robot will significantly decrease the waiting times for a parking spot and thus increase the overall experience of the visitors.

The secondary users are the visitors of theme parks and festivals that are directly interacting with the parking robot to find a parking spot. The parking robot can guide them to a parking spot quickly. Without the parking robot, visitors would have to wait longer which adds stress and frustration to their day which will decrease their experience [5].

For society, the parking robot can have great improvement opportunities. The parking robot will be more efficient than the current traffic controllers, which will improve the traffic flow around the parking lots. Consequently, the traffic flow on high- and motorways around the parking spot will improve. Therefore, people that do not visit the theme park or event will not experience any delay in their travel due to this effect. Furthermore, congestion increases fuel consumption, environmental pollution and traffic accidents.[6] So the parking robot will have a decreasing effect on these matters too.

From an enterprise perspective, multiple groups take advantage of the parking robot. First, the organization of events and theme parks. They don’t have to deploy traffic controllers anymore. Which eventually could decrease their overall costs. Moreover, the research that will be done is interesting for the development of other robots. The navigation and communication technique used in the parking robot could be applied in other areas as well. When the parking robot will be developed on a larger scale, robot companies have to produce more robots than they do now, which will eventually decrease the cost per robot. The profit companies make because of the enhanced traffic flow caused by the parking robot could be used to do more research on parking robots or robots who use this navigation and communication technology in general. Such can lead to the continuous improvement of the used techniques.

Bibliography

1. Ruan, J. M., Liu, B., Wei, H., Qu, Y., Zhu, N., & Zhou, X. (2016). How Many and Where to LocateParking Lots? A Space–time Accessibility-Maximization Modeling Framework for Special EventTraffic Management. Urban Rail Transit,2(2), 59–70. doi: 10.1007/s40864-016-0038-9

2. Currie, G., & Shalaby, A. (2012). Synthesis of Transport Planning Approaches for the World’s LargestEvents. Transport Reviews,32(1), 113–136. doi: 10.1080/01441647.2011.601352

3. Maheshwari, K. A., & Bagavathi Sivakumar, P. (2018). Use of predictive analytics towards bettermanagement of parking lot using image processing. Lecture Notes in Computational Vision andBiomechanics,28, 774–787. doi: 10.1007/978-3-319-71767-8{\}67

4. Han, Y., Shan, J., Wang, M., & Yang, G. (2017). Optimization design and evaluation of parking routebased on automatic assignment mechanism of parking lot. Advances in Mechanical Engineering,9(7), 1–9. doi: 10.1177/1687814017712416

5. Winter Nie, Waiting: integrating social and psychological perspectives in operations management, Omega, Volume 28, Issue 6, 2000, Pages 611-629, ISSN 0305-0483

Solution Concepts

Our solution can be split into 2 seperate components:

• Tracking what parking places are available
• Guiding user vehicles to parking places

For both of these categories we present and discuss several possible solutions.

Tracking parking spaces

Offline scan

This solution would perform a scan of the parking lot at the start of the day and check what spots are available. Afterwards, it will keep track of available spaces virtually. A spot will only be taken if it was already taken at the start of the day, or the system itself assigned it to a vehicle during the day. This technique would uses the assumption that when a spot is taken somewhere during the day, it will remain occupied throughout the day. If this is not the case, the system will waste parking spots. In addition, the system could perform another scan during the day to catch the spots that might have become available, when the system thinks all spots are occupied.

The scan of the parking lot itself can be rather simple in this case, since it doesn't have to be very efficient (as it doesn't happen often). Two feasible options are:

• Manual 'scanning' by employees. This could be rather feasable in some specific situations, such at our running example of the Efteling;
  • At the start of the day (before opening) there are barely any cars on the lot
  • When employees have to rescan when the system thinks no spaces are left, there will probably not be many empty spaces
• Scanning by autonomous ground vehicles. A ground vehicle, which might be used to guide cars as well, may be used to go over each spot in the parking lot and check if it's taken. If it passes each spot, it could simply use a distance sensor to decide whether a car is present. It may also use a camera with simple computer vision to achieve the same, but this might already be slightly more complex.

Online per spot tracking

A sensor could be used for each parking spot individually to determine whether a car is present. Multiple sensors could be used to achieve this:

• A weight sensor within the parking space to detect the weight of a car
• A distance sensor at the end of the parking space, to detect whether something is within a certain distance

This way the system could easily and accurately see what spots are available at any given time, without having to make any assumptions.

Online global scan

Cameras with computer vision could be deployed to track whole areas of the parking lot at once. This would involve installing enough cameras to cover the whole parking lot, and making use of computer vision to detect whether a spot is taken at any given time.

Semi-Online scan

An autonomous aerial vehicle could regularly fly over the parking lot and scan what spaces are available, using a similar camera setup as with global tracking. The aerial vehicle could cover the area quite quickly compared to ground vehicles and thus makes it possible to perform these scans many times an hour. Moreover, since these are aerial vehicles, the scans don't interfere with car guiding operations at all.

Guiding vehicles

Following ground drones

An autonomous ground vehicle could be deployed to physically guide a vehicle to their designated parking spot. This vehicle would start in front of the car that needs to park, and drive towards the assigned parking spot, somehow signalling the user vehicles to follow. This would requite the autonomous vehicle to be large enough to be noticed by the user vehicle, and not be run over. In addition it should drive fast enough to have a pleasant speed to be followed by user vehicles. Since this process would be rather slow, multiple of these robots should be deployed to guide vehicles in parallel. These vehicles need to somehow return back to the queue after having assigned a user vehicle to their spot. This would require a route to the start that doesn't interfere with guidance of other vehicles.

Following air drones

An autonomous aerial vehicle could be deployed to physically guide a vehicle to their designated parking spot. This would work similar to the ground drones, but have one additional problem. Since these are aerial vehicles, it's probably difficult to make them large and remain safe, thus it becomes more of a challenge to make them stand out and noticable by the user vehicle. For these vehicles, lights can be used to grab user attention instead. Having return paths becomes easier for these vehicles, compared to ground vehicles, because they could simply be flying at an other attitude to prevent collisions.

Following ground drone instructions

In certain cases, when the parking lot is rather simple/structured, a pair of autonomous ground vehicles could be deployed to point indicate the parking spot to be used. If the parking spot is a simple structured grid, any parking spot can easily be indicated by showing the row and column of the spot. Ground vehicles could do this physically by stopping at the row and column to be parked in. One of these vehicles would always remain on the main path and indicate the row to be parked in. The other vehicle would be present within said row and indicate the column to be parked in. These autonomous vehicles should be provided with a means of pointing the user vehicle in a direction to move, since user vehicle is not expected to physically follow the vehicles in this situation. The autonomous vehicles would simply move to the next column and or row whe a spot is taken.

Solution Concepts Discussion

None of the suggested solutions is perfect, so below is a discussion of the pros and cons of each approach. For each of the solutions, it's also mentioned how feasible it would be to develop the technology by our group.

Tracking parking spaces

Offline scan

Pros:

• Can be very simple to deploy in case:
  • Employees are used and the parking lot is always almost completely full or empty at time of the scane.
  • Ground vehicles are also used for guiding vehicles already.
• Doesn't require any electronics to be permanently installed.

Cons:

• Relies on the assumption that vehicles primarily leave at the end of the day.
• Scanning may take a considerable amount of time, and may block the guidance system from functioning.

Feasibility:

• May not require any electronics when relying on employees (and is thus entirely feasible).
• May reuse behavior that must already be present in guidance by autonomous ground vehicles, and thus not present any new challenges.

Online per spot tracking

Pros:

• Gives an entirely accurate live overview of the parking lot.
• Is very robust, due to the simple sensor setup.

Cons:

• Requires installation of each of the parking spaces of the parking lot.

Feasibility:

• Requires only very simple sensor usage, and thus be very feasible.

Online global scan

Pros: - Gives a live overview of the parking lot. Cons:

• Requires installation of several cameras throughout the parking lot.
• Is not entirely reliable due to usage of computer vision, which is error prone.

Feasibility:

• Requires usage of computer vision, which can be challenging.

Semi-Online scan

Pros:

• Doesn't require any installation.
• Gives an almost live overview of the parking lot.

Cons:

• Is not entirely reliable due to usage of computer vision, which is error prone.

Feasibility:

• Requires usage of computer vision, which can be challenging.
• Requires autonomous operation of an aerial vehicle, which can be very challenging:
  • Usage of GPS for approximate location tracking, which is doable, but may not be accurate enough to target exactly 1 parking space.
  • Requires some very precise autonomous control in order to be docked, which is very difficult.

Guiding vehicles

Following ground drones

Pros:

• Can be a large vehicle, with large capacity batteries, thus not requiring an autonomous docking solution.
• May be easy to understand by user vehicles (research would need to be conducted).

Cons:

• Requires many vehicles to be efficient.
• Wastes a lot of resources:
  • Requires to drive all the way from the start of the queue to the designated parking spot per user vehicle, costing a lot of energy.
  • Requires to drive all the way back to the queue, during which it's not of use to anyone.
• Requires a separate return path that doesn't interfere with the other vehicles being guided.

Feasibility:

• Requires autonomous operation of a ground vehicle, which can be challenging but should be achievable:
  • Usage of GPS for approximate location tracking, which is doable.
  • Usage of computer vision for more accurate obstacle avoidance, which should be doable.
• Requires usage of computer vision, for checking whether user vehicles are parked and for obstacle avoidance, which can be challenging.
• Can be challenging to coordinate multiple autonomous vehicles at once.

Following air drones

Pros:

• Doesn't require a special return path, a different altitude can be used instead
• Doesn't have a lot of wasted time by returning to the queue, due to the speed fyling vehicles can easily have.

Cons:

• Requires many vehicles to be efficient.
• Wastes a lot of resources:
  • Requires frequent recharging due to the small battery capacity in order to be light enough to fly.

Feasibility:

• Doesn't require active obstacle avoidance, since there are only other drones in the air (which should just be properly coordinated)
• Requires autonomous operation of an aerial vehicle, which can be very challenging:
  • Usage of GPS for approximate location tracking, which is doable, but may not be accurate enough to target exactly 1 parking space.
  • Requires some very precise autonomous control in order to be docked, which is very difficult.
• Requires usage of computer vision, for checking whether user vehicles are parked, which can be challenging.
• Can be challenging to coordinate multiple autonomous vehicles at once.

In short, when compared to following ground drones, it's easier in the sense that no active obstacle avoidance is needed, but harder in the sense that it requires docking.

Following ground drone instructions

Pros:

• Only requires 2 ground drones.
• Doesn't require the drones to cover a large distance (and are thus relatively energy efficient).

Cons:

• Requires the parking lot to have a really specific and simple layout.
• Has to have a clear way of signalling instructions to cars
• Can not easily fill random spots that have become available
• Has some reset time once it hit the end of the parking lot, and may even pose difficulties if the entire queue already moved along to the last row

Feasibility:

• Requires autonomous operation of a ground vehicle, which can be challenging but should be achievable:
  • Usage of GPS for approximate location tracking, which is doable.
  • Usage of computer vision for more accurate obstacle avoidance, which should be doable.
• Requires usage of computer vision, for checking whether user vehicles are parked, which can be challenging.

In short, when compared to following ground drones, it's easier since it doesn't require complex coordination of multiple drones.

Planning

	Activities	Person(s)
Week 1	Introduction lecture Brainstorm on possible subjects Choosing subject Literature study	All All All All
Week 2	Tutor meeting 1 Problem definition State of the Art research User analysis Possible solutions Planning Updating wiki page	All Sietse Luc Mandy Tar Rien All
Week 3	Tutor meeting 2 Literature study User analysis, interviews Research on hardware solution Start on computer vision software Updating wiki page	All Name Name Name Name All
Week 4	Tutor meeting 3 Finishing user analysis Prototyping hardware solution Continuing on computer vision software Research on further neccesary software Updating wiki page	All Name Name Name Name All
Week 5	Tutor meeting 4 Prototyping hardware solution Continuing on software Updating wiki page	All Name Name All
Week 6	Tutor Meeting 5 Finishing hardware solution Implementing software User feedback Updating wiki page	All Name Name Name All
Week 7	Tutor meeting 6 User feedback Start on presentation Finishing wiki page	All Name Name Name
Week 8	Tutor meeting 7 Finishing presentation Final presentation Finalizing project	All Name Name Name

Final Deliverables

• Hardware prototype
• Software for recognizing parking spaces
• This wiki page
• Presentation video

Log

Week 1

Name	Hours	Summary
Luc	X	Summary
Mandy	X	Summary
Rien	15	Introduction lecture, two meetings, brainstorm on possible subjects, literatury study
Sietse	X	Summary
Tar	X	Summary

Week 2

Name	Hours	Summary
Luc	X	Summary
Mandy	X	Summary
Rien	X	Summary
Sietse	X	Summary
Tar	X	Summary

Week 3

Name	Hours	Summary
Luc	X	Summary
Mandy	X	Summary
Rien	X	Summary
Sietse	X	Summary
Tar	X	Summary

Week 4

Name	Hours	Summary
Luc	X	Summary
Mandy	X	Summary
Rien	X	Summary
Sietse	X	Summary
Tar	X	Summary

Week 5

Name	Hours	Summary
Luc	X	Summary
Mandy	X	Summary
Rien	X	Summary
Sietse	X	Summary
Tar	X	Summary

Week 6

Name	Hours	Summary
Luc	X	Summary
Mandy	X	Summary
Rien	X	Summary
Sietse	X	Summary
Tar	X	Summary

Week 2

Name	Hours	Summary
Luc	X	Summary
Mandy	X	Summary
Rien	X	Summary
Sietse	X	Summary
Tar	X	Summary

Week 7

Name	Hours	Summary
Luc	X	Summary
Mandy	X	Summary
Rien	X	Summary
Sietse	X	Summary
Tar	X	Summary

Week 8

Name	Hours	Summary
Luc	X	Summary
Mandy	X	Summary
Rien	X	Summary
Sietse	X	Summary
Tar	X	Summary