Congestion adaptive traffic light control and notification architecture using Google maps APIs

Mishra, S., Bhattacharya, D., & Gupta, A. (2018). Congestion Adaptive Traffic Light Control and Notification Architecture Using Google Maps APIs. Data, 3(4), [67]. DOI: 10.3390/data3040067Traffic jams can be avoided by controlling traffic signals according to quickly building congestion with steep gradients on short temporal and small spatial scales. With the rising standards of computational technology, single-board computers, software packages, platforms, and APIs (Application Program Interfaces), it has become relatively easy for developers to create systems for controlling signals and informative systems. Hence, for enhancing the power of Intelligent Transport Systems in automotive telematics, in this study, we used crowdsourced traffic congestion data from Google to adjust traffic light cycle times with a system that is adaptable to congestion. One aim of the system proposed here is to inform drivers about the status of the upcoming traffic light on their route. Since crowdsourced data are used, the system does not entail the high infrastructure cost associated with sensing networks. A full system module-level analysis is presented for implementation. The system proposed is fail-safe against temporal communication failure. Along with a case study for examining congestion levels, generic information processing for the cycle time decision and status delivery system was tested and confirmed to be viable and quick for a restricted prototype model. The information required was delivered correctly over sustained trials, with an average time delay of 1.5 s and a maximum of 3 s.publishersversionpublishe

The Hierarchical Control Method for Coordinating a Group of Connected Vehicles on Urban Roads

Safety, mobility and environmental impact are the three major challenges in today\u27s transportation system. As the advances in wireless communication and vehicle automation technologies, they have rapidly led to the emergence and development of connected and automated vehicles (CAVs). We can expect fully CAVs by 2030. The CAV technologies offer another solution for the issues we are dealing with in the current transportation system. In the meanwhile, urban roads are one of the most important part in the transportation network. Urban roads are characterized by multiple interconnected intersections. They are more complicated than highway traffic, because the vehicles on the urban roads are moving in multiple directions with higher relative velocity. Most of the traffic accidents happened at intersections and the intersections are the major contribution to the traffic congestions. Our urban road infrastructures are also becoming more intelligent. Sensor-embedded roadways are continuously gathering traffic data from passing vehicles. Our smart vehicles are meeting intelligent roads. However, we have not taken the fully advantages of the data rich traffic environment provided by the connected vehicle technologies and intelligent road infrastructures. The objective of this research is to develop a coordination control strategy for a group of connected vehicles under intelligent traffic environment, which can guide the vehicles passing through the intersections and make smart lane change decisions with the objective of improving overall fuel economy and traffic mobility. The coordination control strategy should also be robust to imperfect connectivity conditions with various connected vehicle penetration rate. This dissertation proposes a hierarchical control method to coordinate a group of connected vehicles travelling on urban roads with intersections. The dissertation includes four parts of the application of our proposed method: First, we focus on the coordination of the connected vehicles on the multiple interconnected unsignalized intersection roads, where the traffic signals are removed and the collision avoidance at the intersection area relays on the communication and cooperation of the connected vehicles and intersection controllers. Second, a fuel efficient hierarchical control method is proposed to control the connected vehicles travel on the signalized intersection roads. With the signal phase and timing (SPAT) information, our proposed approach is able to help the connected vehicles minimize red light idling and improve the fuel economy at the same time. Third, the research is extended form single lane to multiple lane, where the connected vehicle discretionary and cooperative mandatory lane change have been explored. Finally, we have analysis the real-world implementation potential of our proposed algorithm including the communication delay and real-time implementation analysis

Fuzzy Logic in Traffic Engineering: A Review on Signal Control

Since 1965 when the fuzzy logic and fuzzy algebra were introduced by Lotfi Zadeh, the fuzzy theory successfully found its applications in the wide range of subject fields. This is mainly due to its ability to process various data, including vague or uncertain data, and provide results that are suitable for the decision making. This paper aims to provide comprehensive overview of literature on fuzzy control systems used for the management of the road traffic flow at road junctions. Several theoretical approaches from basic fuzzy models from the late 1970s to most recent combinations of real-time data with fuzzy inference system and genetic algorithms are mentioned and discussed throughout the paper. In most cases, fuzzy logic controllers provide considerable improvements in the efficiency of traffic junctions’ management