Abstract
Traffic congestion is one of the significant contributors to global warming and a major factor deteriorating logistic efficiency, thereby impeding efficiencies and economy. Infrastructure expansion and improvements render a short-lived solution. Significant improvisation is achieved only through technological approach to the problems with challenges in signaling shortest route and ensuring fair treatment to all the directions without a deadlock-like situation. One of the firsts to address is signaling electronics. Signaling electronics are not maintained. Besides, traffic signals do not align with the traffic patterns. Traffic congestion is characterized as dynamic, stochastic, random, and unpredictable phenomenon. Consequently, traffic congestion cannot be addressed by static, predetermined signal phases, preprogrammed periodically changing signals based on a prior knowledge of traffic behavior as the dynamically changing traffic pattern will dislocate and disrupt the assumptions of traffic changes. Hence traffic signals have to be devised to adapt to changes as per the traffic situation. Secondly, signaling electronics is oblivious to vehicle densities, intended direction of travel, and available capacity on road ahead to accommodate oncoming vehicles. This leads to a green phase resulting in deadlock situation. The paper describes exploring utilization of green phases for other directions while maintaining exclusive and non-conflicting movement with other directions. The paper proposes computation of dynamic signal phases while ensuring fair assignment to other directions and avoidance of deadlock situations.
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Parmar, R.S., Trivedi, B.H. (2018). Computation of Dynamic Signal Phases for Vehicular Traffic. In: Kolhe, M., Trivedi, M., Tiwari, S., Singh, V. (eds) Advances in Data and Information Sciences. Lecture Notes in Networks and Systems, vol 38. Springer, Singapore. https://doi.org/10.1007/978-981-10-8360-0_1
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