Algorithms Tested and Results Obtained
6.3 Possible future work
As with most research projects, there is often not enough time available to investigate every aspect of the specific problem at hand. This section is dedicated to highlighting ideas for further work related to improving traffic flow control through implementation of self-organising traffic
control algorithms at signalised intersections in a traffic network.
6.3.1 Improving traffic simulation model accuracy
In order to improve upon the accuracy of the simulation model it is suggested that the scope of the model be widened in an attempt to incorporate a greater number of real-world characteristics associated with traffic flow and traffic flow control. More specifically, these characteristics may include vehicles of varying size, which have varying maximum speeds. The rates of acceleration and deceleration may also vary for each vehicle, as is the case along real-world road sections.
It is also suggested that further research take place into more detailed mathematical models describing the motion of individual vehicles along a road section. One such example is that of a vehicle following model which accounts for driver reaction times associated with braking and accelerating.
6.3.2 Investigating alternative self-organising rules
Before any investigation can take place in terms of alternative rules for self-organising traffic control algorithms, it is suggested that a more thorough investigation is performed in the form of a sensitivity analysis with respect to the parameters of the algorithms presented in §5.1.
In particular, it would be beneficial if a relationship could be determined between the arrival rate of vehicles into the system and the optimal parameter values and combinations in the self-organising traffic control algorithms (U and Umax in the case of SOTCA I, and U , Umax and in the case of SOTCA II).
In terms of investigating alternative self-organising rules it is suggested that efforts be made with respect to the research and development of alternative optimising or prioritisation strategies and stabilisation strategies, as well as their combinations. An ideal self-organising traffic control algorithm would be free of any predetermined parameters, i.e. the optimal operation of the traffic control algorithm would depend solely on the input received from the immediate local traffic conditions.
It is suggested that clustering techniques be considered in determining alternative optimising prioritisation strategies in which the size of a platoon or cluster of vehicles is considered rather than individual vehicles themselves. Also, the critical values which are used to determine when a group of vehicles may be considered a cluster require further investigation and motivation. It is also suggested that the speed of vehicles feature more prominently such that priority is placed on vehicles which will occupy the intersection for a shorter period of time depending on their distance from the intersection and the speed at which they are travelling.
6.3.3 Improved real-world case study
In an attempt to better gauge the performance of any self-organising traffic control algorithm it is suggested that that simulation runs be implemented for actual road network topologies, using actual data relevant to the road network which is being modelled. The corridor along the Adam Tas Road in Stellenbosch, South Africa would, for example, make a good case study.
Between the Adam Tas Road and Dorp Street intersection, and the Adam Tas Road and Bird Street intersection, there are six signalised intersections (inclusive). Traffic along the corridor is known to become heavily congested during certain hours of the day, making it an appropriate site for investigating the potential effectiveness of self-organising traffic control algorithms.
The quality of the output of a simulation model, however, depends on the quality of the data which are used as input to the simulation model. For this reason, accurate data which are relevant to the road network being investigated is crucial in order to validate the results of the simulation model. Due to the fact that the data necessary for the execution of a simulation study on a microscopic level are not readily available, or easily obtainable, it is suggested that various traffic data collection methods and techniques are researched and implemented so as to provide a solid starting point for a proper case study.
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