PRE2016 3 Groep13
Introduction
This wiki page will display the possibilities of self learning navigational software. Throughout the report several points of attention will be introduced, investigated and processed in the prototype navigational system. The goal of the system is to create a cooperative/inter-vehicular, high-level (Think about; no traffic lights) and based on the current situation (hardly any self driving cars, not all people have navigational systems). This research is set up trying to answer the following research question:
How can the travel time be minizied while maximizing overall utility, looking at user and society, by using a self learning, inter-vehicular cooperative navigation system?
Objectives
Minimize travel time
The main goal of the system is to minimize travel time by rerouting users, to prevent longer waiting times caused by traffic jams.
Maximize overall utility
The utility can be split in three groups.
User
- Minimize travel time, this is the main objective as mentioned above.
- Estimate arrival time by predicting traffic jams so the user knows the optimal route and best moment of departure to reach the goal location on time.
- Making the system fair for all users. This will require user research in finding the fairest solution.
- Taking the privacy of the user into account by doing user research.
Society
- Traffic jam prevention to minimize unnecessary pollution, by rerouting to minimize unnecessary waiting time.
- Minimize disturbance by rerouting through less populated locations.
Enterprises
- Creating a system that is better than the present navigation systems, so potential users will be interested in buying this system.
State of the Art
There are a lot of different navigation devices available currently. The most simple one is only able to tell you the shortest route. A small upgrade also allows the user to exclude certain routes, like toll roads and tunnels. These often also give a choice for the user to either take a fastest (time) or shortest (distance) route. Some devices also allow traffic information incorporation which ask you to reroute if there is a traffic jam. When combining such a navigation system with a self driving car it is also possible to make the decision automatically. These all however respond to a situation instead trying to avoid certain situations.
Improvement over state of the art
To improve the state of the art it is important to know what the implications are of the current system. These systems will reroute users as soon as there is a faster route available and thus will distribute traffic equally over the roads available, which may seem like the optimal situation. A selflearning system however should have more roads available, since it can predict traffic jams that havent even happend yet. It can reroute the user many kilometers before the actual traffic jam and thus prevent new traffic jams in reroute roads.
Approach
The goal of the research is to improve the current traffic situation. This can only be considered an improvement when the changes do not diminish the overal utility. This means that within the navigation system the user aswell as the society have to play an important role. As the time window is quite a tight one this research will be conducted simultaniously. The group of researchers will be split where four members of the team will work on making the selflearning navigation work. The remaining two members will focus on the users and society. By frequent interaction, the team will be able to create a working navigational system in which the user and society will be strongly embedded. This also allows the prototype to be as representable as possible.
The completion of the program will also include a visual simulation which allows all team members as well as external personel to use and understand the way the system operates, and what conclusions it provides.
User and Society
People behave differently when wearing something to hide their identity[1]. This also happens in a car. People are not directly visible and thus act more selfish. As long as people are driving their car (instead of autonomous), we can investigate further if/how we want to incorporate this.
Furthermore our navigation idea will request people to drive different roads, which at points will probably make them lose time on their journey. When looking at literature we find something called: “risk aversion”[2][3]. Risk aversion is a human trait where someone would avoid taking a favorable bet (overall travel time decrease) when it means they can directly lose out (more travel time)[4].
User research
To make sure all user preferences are taken into account a user research is conducted, focussing on the key aspects which should provide a strong basis for the product to be released to the public. The aim of the research, and thus leading factors into choosing the approach, is the gain as much information about as many different drivers as possible. Since the aspects of the research are pre determined, the best research method available is a questionaire. Google drive is used to host the questionaire, because it has all features (sort of questions/ set-up) required for this research.
The link below will bring you to the questionaire:
https://docs.google.com/forms/d/e/1FAIpQLScDPnmNoF6QXpMX930HC-V1ydxndn6kBt-_NZO-LiEaaBGuWA/viewform
The questionaire is devided in several sections. Just like any research the questionaire begins with a brief introduction of our idea followed by asking the participants permission to use the data they provide through an inform concent form. In all following sections the key issues are presented to possible users.
Section 1: Introduction questions
Section 2: Willingness to follow the system
Section 3: Fairness
The system can decrease travel time and traffic jams in several ways. The participants are presented with these way, in a honest way. This means that we do present options where a user of the system is always equal or worse of to a person not using SLIVCS. This sections is designed to get a better understanding of the target group, and to give a better insight into the goal our system should aim for.
Section 4: Privacy
The current state of the world means that almost all information gets shared. (insert link/reference) This however doesnt mean that all users all neccesarely willing to share all information. Since our system needs to know certain things about users it is important to know that people dont mind sharing this information (anonymously). We ask the participants if they would be willing to share their current location aswell as their destination. If the participant is willing to share this he/she is taking to the next section with follow up questions. If the participant is not willing to share this information he is taking to the final stage of the questionaire.
Section 5: System interaction
In this section the participants are asked to think about the idea of SLICVS, and how they would see such a system fit in their daily lives. It contains three subsections. The first subsection asks the participants what inputs they would like to have on the system. There are six predetermined options, like what type of roads, should the system take pollution into account etc. It is also possible to write your own input, if this is not present in the premade questions. The second second makes the participant think about how they would like to communicate with the system. As explained in Chapter %%%%%%%% it is important that the system knows when an user wants to travel from a to b. This means that an user would need to interact with the system quite frequently, which means that this interaction should be easy. Possible communications are for example a mobile app, a online website or a custom made interface. Once again the questionaire provides room for a written answer. The final subsection is regarding the route planning of possible users. For the system to work optimally it is beneficial to know way in advance when users are gonna drive. This section ask of different occasions (different destinations) the time a user would be able/willing to provide the system with its travel plans before departing.
Section 6: Finalizing questions
This section is focussed on the the aim of the navigational system. In this section the participants are asked about possible approaches the system could take regarding traffic/travel time distribution.
A participant is free to not answer a question if he/she does not want to answer, without having to provide an reason. All information helps towards optimizing SLIVCS for the user, and thus there are no mandatory questions (excluding accepting the inform concent form).
To be continued
References
[1]https://newrepublic.com/article/117152/how-sunglasses-and-masks-affect-moral-behavior
[2]http://www.jstor.org/stable/2937956?seq=1#page_scan_tab_contents