A complex problem in cities is traffic/road and cargo/vehicle density. Since trip computers provide very general information about the vehicle and the journey, it will be possible to make an instant travel flow plan and update the situation in an instant if this information can interact with the traffic/road, cargo/vehicle location data. However, the rate of interaction and depth of data between transportation systems is still unclear and consists of a limited one-way flow of information. This interaction ismore focused on obtaining information and (discontinuous) discrete time evaluating it with the human factor. But it is known that vehicles will start to be self-directed (autonomous) in the future, for example unmanned aerial vehicles (UAV). Through monitoring and planning, it is evident that these expectations will improve traffic/road, cargo/vehicle situation interaction, and management infrastructures more effectively. Within the context of smart city logistics, the technologies that prioritize situations of traffic/road, cargo/vehicle—or ITS interaction for short—are the subject of the study. From a relational and comprehensive perspective, it also assesses advancements in other smart solutions about traffic/road, cargo/vehicle, tracking, and/or planning. All these tracking and planning systems are supported by the ITS framework suggested in this study. The network latency issue will no longer exist because Industry 5.0 enables it to be disregarded.
System Analysis for Intelligent Transportation Systems (ITS) in the Scope of Smart City Logistics
2023
Article (Journal)
Electronic Resource
Unknown
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