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Smart city article details
| Title | Autonomous Vehicle Decision Making And Urban Infrastructure Optimization |
|---|---|
| ID_Doc | 11501 |
| Authors | Mudrak G.; Semwal S.K. |
| Year | 2021 |
| Published | Intelligent Computing - Proceedings of the 2021 Computing Conference |
| DOI | http://dx.doi.org/10.1007/978-3-030-80126-7_83 |
| Abstract | Highly mobile populations can quickly overwhelm an existing urban infrastructure as large numbers of people move into the city. The urban road networks having been constructed for less traffic will quickly become congested leading to diffusion of traffic and a greater spread of congestion as secondary roads are increasingly utilized. Further unwanted and potentially fatal consequences such as increased accident, stress, driver anger, and road rage will increase. Traditional methods of addressing the growth in traffic density would include increasing lane count and construction of new roads, and can be costly. Yet traditional responses do not take into account the growing number of connected vehicles and soon, possible autonomous vehicles will interact with human-driven cars. In considering a driving population of autonomous vehicles, we identify an increased range of possible traffic management strategies for collaborative experiences. The vehicles themselves can operate according to their own goals and the urban infrastructure can also be enhanced to a greater degree of self-management. This paper will explore the ideas, techniques and approach behind creating an Agent Based Modelling environment to support the interaction of autonomous vehicles with a smarter urban infrastructure. Procedural content generation (PCG) and agent based modelling concepts will be applied in establishing the modelling framework. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 |
| Author Keywords | Agent based modeling; Autonomous vehicles; Population noise maps; Procedural generated cities; Smart cities; Smart infrastructure |
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