Assignment on the Traffic System

Introduction of Traffic System

The traffic system is a very important system in every country that ensures citizens are following the rules effectively as well as it also helps to control the accidents and death rates on the roads. After passing some time some ambiguities, as well as some problems, may rise into the current traffic system. Due to this reason, the risk of failure of the complex traffic system may also increase. To make the complex system powerful and successful, it is necessary to validate the complex system. The current study is completely based on the previous assignment and the selected project on the complex traffic system is

the traffic flow of a city. In this document, it is tried to validate a complex system that is selected in the assignment. The complex system for the city traffic modeled in the previous assignment. The research study is providing brief information on the complex system in the form of related studies. The literature study is also providing information on how other researchers have validated their modeled complex systems. Furthermore, the brief justification for modeled traffic flow of a city is also provided in the complex system. The main part of this research work is to validate the modeled complex traffic system. The reflection part is providing the information related to the whole study and providing the analysis on the project.

Literature Review of Traffic System

            As described by Toledo & Koutsopoulos (2004), the dynamics of traffic phenomena’s detailed analysis is supported by traffic simulation models. Therefore, these models are also important tools for the analysis of the transportation systems. Furthermore, the simulation models must be able to repeat reality adequately to evaluate or validate the actual effects of traffic management systems in the city. The validation model for complex traffic systems is discussed in the study which is the process of investigating the model replicates reality. the validation role is defined in the calibration and model development scope as well as the framework to perform the validation is discussed. To validate the different types of replication outputs, the statistical methods hierarchy is investigated against the observed data. Furthermore, the method for validation is introduced on the basis of statistical tests on the metamodels formfitting to the simulated data. The applicability of several methods is illustrated by the case study (Toledo & Koutsopoulos, 2004).

            Balakrishna, Koutsopoulos, & Ben-Akiva (2005) stated in the research that the intelligent transportation systems have the ability to make improvements in the conditions of traffic as well as minimize the delays in traveling through facilitating better utilization of the accessible and existing capacity. To achieve their objectives, this type of system is complicated and employs the algorithms. For the wide range of ITS applications, it has developed many dynamic traffic assignment systems based on the simulation. Furthermore, more realistic approaches are targeted by such systems to short term planning for transportation like work zones and special events. Moreover, it also addresses the growing real-time applications importance like route guidance, incident management as well as emergency response (Balakrishna, Koutsopoulos, & Ben-Akiva, 2005).

            As stated by Schaefer, Vokřínek, Pinotti, & Tango (2016) that an integrated multi-agent simulation unified platform for providing support development and autonomic traffic system validation. The simulation is allowing to validate the coordination strategies of the car to car in different scenarios into the penetration levels of variable technology such as mixing of different strategies. Furthermore, it also allows the acceptance of the users of the traffic system as part of the traffic system or as the external observer of the traffic system. Furthermore, the realistic driving simulation features are combined by the platform while the vehicles were controlled by AI and simulation with a flexible detail level. The platform’s principal idea is to allow the development and the complex autonomic study distributed car to car system for the coordination of vehicles. The development environment is provided by the platform and the toolchain which is essential for the validation of the complex traffic systems. So, the autonomic complex systems are completely based on the coordination approach among the agents (Sutandi & Dia, 2005).

            The traffic of road is demonstrated as a multi-specialist arrangement of agreeable operators. The cooperation between the operators carries autonomic properties into the developed framework (for example the traffic adjusts to a blockage of a path and vehicles converge into a subsequent path). The framework likewise shows autonomic properties from a solitary client viewpoint. The driver moves toward the framework in a type of a driver help framework. The researchers can indicate it as an autonomic driver help framework. With the assistance system though the human-machine interface, it is only being interacted by the driver. The complexity of multi-agent interactions is being hidden by the autonomic driver's assistance from the user. In the last of this study, the specific agent of the car will be responsible to interact with other agents in the system without any intervention of the user (Schaefer, Vokřínek, Pinotti, & Tango, 2016).

                                                    Image below shows the Multi-agent Traffic stimulation.

            As stated by Xiang, Kennedy, Madey, & Cabaniss (2005), the most formalized model validation and verification approaches come from the system and industrial engineering for the simulations of the discrete event systems. Furthermore, such kind of techniques is highly recommended and used in the computational sciences. But the technique of agent-based modeling is completely different from the approaches of discrete event modeling on a larger basis which is mostly used in different several areas of industrial and system engineering. The researchers have also further said that an attractive and efficient way for modeling the complex systems on a larger scale, have recently been become by the agent-based modeling techniques. For agent-based model validation, there are also some formalized approaches existing which have the ability to validate the traffic complex systems. Several types of existing validation and verification techniques are designed, developed, adopted, and applied by researchers in this research study to an agent-based scientific model. Therefore, they have also investigated the importance and sufficiency of such kind of approaches to validate the models of agent-based (Xiang, Kennedy, Madey, & Cabaniss, 2005).

            Pütz, Zlock, Bock, & Eckstein (2017) have stated in their research that the signing of highly automated vehicles is an important problem for the industry of autonomous vehicles. the high test efforts are caused by the assistance systems for automated vehicles. The validation framework is developed by the project PEGASUS for the sign of the process of such vehicles. The relevant traffic scenarios are being contained by one element of this framework. Different types of database entities are combined by the database. Moreover, such kind of database entities is described by the researchers in this study and the processing chain steps including the resulting benefits for the validation. Furthermore, the collection approach to sign off on the common database, as well as the criteria for the common evaluation, are also discussed in this study (Pütz, Zlock, Bock, & Eckstein, 2017).

Complex System of Traffic

            The complex system for city traffic flow which is modeled in the previous assignment is completely based on logic. In the design of the road map model of the complex system was generated randomly in every setup but the size of the roads and map based on the input size. Every intersection on the roads has signal lights because the different roads are intersecting each road. That’s why the signal lights are essential in every intersection to control the movement of vehicles and give the instructions to cars to run or stop. The design is also selected because the traffic simulation weather sensitive. The traffic signaling and the workability will have the standard behavior but the rainy weather will make the road slippery. Because of this situation, it is possible to increase the number of accidents. But the design for weather will be effective because the network of roads and signals and the barriers fixed on the roads can reduce the rate of accidents in different weathers. On the other side, the main challenge in the design was the pedestrians but it was also handled by setting some rules and regulations on crossing roads and they will not be hit by cars on roads.

                                                                      Image shows the complex and increasing capacity of traffic system that lies on different factors.

Validation Metric of Traffic System

Reflection of Traffic System

            In this section, the brief information on this research study by reflection on the models, literature study as well as the findings. First of all, the study is providing brief information that the design of the road map is completely logical which will be changed in every setup. there is a huge network of roads which are intersecting each other and they all have the traffic lights that will control the traffic. The detectors are counting the movements and activities of vehicles and pedestrians on the roads. The validation metric is providing information that the detectors are working normally and the whole traffic system too. The satisfying fact of this study is that the model is preventing deadlocks and accidents and any kind of blockage.

Conclusion of Traffic System

            It is concluded that the traffic system is a very important system in every country that ensures citizens are following the rules effectively as well as it also helps to control the accidents and death rates on the roads. The complex system for the city traffic modeled in the previous assignment.  The dynamics of traffic phenomena’s detailed analysis is supported by traffic simulation models. More realistic approaches are targeted by such systems to short term planning for transportation like work zones and special events. Furthermore, the realistic driving simulation features are combined by the platform while the vehicles were controlled by AI and simulation with a flexible detail level. The traffic of road is demonstrated as a multi-specialist arrangement of agreeable operators. The complexity of multi-agent interactions is being hidden by the autonomic driver's assistance from the user. For agent-based model validation, there are also some formalized approaches existing which have the ability to validate the traffic complex systems. The validation framework is developed by the project PEGASUS for the sign of the process of such vehicles. The relevant traffic scenarios are being contained by one element of this framework. In the design of the road map model of the complex system was generated randomly in every setup but the size of the roads and map based on the input size. The traffic signaling and the workability will have the standard behavior but the rainy weather will make the road slippery. The study is providing brief information that the design of the road map is completely logical which will be changed in every setup. The validation metric is providing information that the detectors are working normally and the whole traffic system too.

References of Traffic System

Balakrishna, R., Koutsopoulos, H. N., & Ben-Akiva, M. (2005). Calibration and Validation of Dynamic Traffic Assignment Systems. In Transportation and Traffic Theory. Flow, Dynamics and Human Interaction. 16th International Symposium on Transportation and Traffic TheoryUniversity of Maryland, College Park.

Hоуеr, R., & Fellendorf, M. (1997). Parametrization of Microscopic Traffic Flow Models Through Image Processing. IFAC Proceedings Volumes, 889-894.

Pütz, A., Zlock, A., Bock, J., & Eckstein, L. (2017). System validation of highly automated vehicles with a database of relevant traffic scenarios. 12th ITS European Congress, Strasbourg, 19-22.

Schaefer, M., Vokřínek, J., Pinotti, D., & Tango, F. (2016). Multi-Agent Traffic Simulation for Development and Validation of Autonomic Car-to-Car Systems. Autonomic Road Transport Support Systems, 165-180.

Sutandi, A. C., & Dia, H. (2005). Performance Evaluation of An Advanced Traffic Control System In A Developing Country. Proceedings of the Eastern Asia Society for Transportation Studies, 1572 - 1584.

Toledo, T., & Koutsopoulos, H. N. (2004). Statistical Validation of Traffic Simulation Models. Transportation Research Record: Journal of Transportation reserach Board.

Xiang, X., Kennedy, R., Madey, G., & Cabaniss, S. (2005). Verification and validation of agent-based scientific simulation models. In Agent-directed simulation conference, 55.