We’ve just started the first participatory part of our project, which is really exciting. Once the first iteration of the game was ready, we booked in sessions at five local schools to go along and get the input of our “end users” (children aged 7-9) on the game so far. We’ve run sessions at three schools so far, and the feedback has been very interesting and useful.
The sessions have been facilitated by Dr Catherine Purcell, the Principal Investigator, who is a psychologist with lots of experience of running participatory research projects like this one. That’s particularly important, because it’s quite a skill to draw out relevant and constructive information from a group and make sure that everyone’s voice is heard.
The children (whose parents had already signed consent forms to let them take part) were divided into groups of 5-10, and able to play the game on our tablets. This iteration of the game is not fully developed, but it gives a good representation of what the final gameplay will be like: the children use the tablet like a magic portal and have to navigate to a school in the virtual city by crossing roads as safely as possible. After the children played the game, Catherine asked for their feedback on various elements of the game. Where possible, one of the members of our team who is involved in game development went along too, to help make sure that the technological aspects of the discussion were covered and to answer techy questions.
The children have been very eager to help, and have given us some excellent feedback to work with. Some of the things they’ve asked for were already in development for the second iteration of the game, such as harder levels and a points system, but it’s good to know more specifically what the children want. Some of their suggestions are things we hadn’t yet considered, like having a pause button and adding an underpass/subway, which are becoming more common and are of course a safe road crossing place.
One thing we were particularly pleased about was that the children had absolutely no difficulty in understanding how to play the game. This level of intuitiveness is a good sign for us, as we want this game to be play-able and enjoyable for children, as well as teaching them safe road crossing behaviour.
To avoid a player feeling lost and not knowing where to go, the game will feature a level map. The map is displayed once the player points the device towards the floor. The exact details of the map’s interactivity abilities are not available at this point, however, while at the map screen, the player might be able to change some settings on-the-fly.
The Main Menu that is currently implemented into the game is mostly a placeholder and it will be replaced/improved with the functionality for logging into a user’s account.
Artificial Intelligence for Traffic
AI required a lot of planning and is still a work in progress, however, it is nearly finished. The traffic system is supposed to control all the vehicles in the game as well as traffic lights. Vehicles are intended to react to each other as well as to traffic lights and traffic signs. Naturally, a single vehicle has to be able to detect when the player is in front of it. At the moment, most of these requirements are implemented, with the exception of the traffic lights/signs. This means that a vehicle can accelerate, drive or slow down (when there is another vehicle in front or if it is about to come into a sharp corner). The vehicle can also follow the road as intended by the design of the world.
Initially, we needed to decide which game engine to use for development. The decision had to be made between Unreal Engine 4 and Unity 3D. Unreal Engine 4 was chosen for the project mainly due to its ability to develop very specific parts of the game. For example custom camera control using mobile device sensors and later custom data tracking for analytics purposes. This doesn’t mean that the Unity engine would not enable us to do the same thing, but the game programmer has more experience with Unreal Engine 4 and C++.
Controlling the Camera
We wanted to have as much control over the camera orientation as possible in order to store the orientation information for later analysis. Originally, the camera was controlled using the raw sensor data from the mobile device. However, the noise of the data that was generated was very high and it caused a jittery effect in orientating the camera. Additionally, there were inflection points in the data that would cause impulses in the camera’s orientation values. At the moment, reducing the noise and removing the inflection points are still under development and a temporary approach of using the GoogleVR plugin has been put in place which solves both of these issues at the cost of not having full control over the camera.
Player Character Movement
With the camera control in place and attached to a player’s character, the movement through the world needed to be implemented. Input for movement control has to be done through touch gestures (e.g. swipe, tap, double tap, etc.). At the moment there are two different approaches for movement locomotion:
Walk and run ability by using the user interface buttons (implemented)
Teleport to the targeted location using the safe-point system (in development)
In our next post we’ll cover other aspects of the early development of the game, including the artificial intelligence implemented for traffic.
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