Traffic congestion is one of the prominent problems even for smart cities due to the constant rise in population and automobiles in urban centres. There is often a financial and physical constraint when it comes to building additional roads. Thus, it is desirable to improve existing traffic conditions by adopting new strategies and technologies that can help address the problem. In order to take care of the ever-increasing and complex traffic situation, cities are using adaptive traffic control and traffic analytics to improve congestion and increase safety. The advent of the Internet of Things (IoT) and the high availability of cloud resources are helping in creating mechanisms that can automate the transporting system and enhance the utilisation of existing infrastructure (Khanna, Rohit, & Joshi).
Intelligent Transportation System (ITS) combines information and technologies used in transportation management systems to improve the transportation network’s safety, efficiency, and sustainability, thus reducing traffic congestion and improving the driver experience.
Sensors are used in traffic systems to gather real-time information regarding traffic flow, traffic congestion, etc. A network of sensors is thus able to map the entire city and collect the tiniest of the details with minimum time and cost overhead. These On-Road Sensors (ORS) perform analytics like vehicle classification, speed calculation, and vehicle count. Through machine learning algorithms predictions regarding the level of traffic congestion in a particular region of the city are made. The system depicts the pattern of traffic flow and suggests measures to curb traffic-related problems. In simple terms, the system suggests an optimum route that considers the parameters like travel time, travel cost, and travel distance.
The main objectives of Intelligent Transport Management System:
Traffic Monitoring: It is one of the key components of the Smart City. Traffic Monitoring allows the city authorities to monitor the traffic of different routes, areas, and streets. The historical traffic monitoring data can be beneficial in smart city planning and city infrastructure development.
Pollution Avoidance: The extent of air pollution and noise pollution is directly proportional to the intensity of the traffic congestion. Thus, reducing congestion led to reduced pollution levels in the city.
Route Optimisation: The system applies a tradeoff between total time, distance, and fuel consumption to optimise the travel route bringing time and money savings to the traveller.
Green Corridor: The green corridor caters to emergency vehicles by allowing them to reach the destination without waiting. It creates a route from source to destination comprising multiple/ all green signals.
Accident Detection: Accident detection is a crucial part of a traffic management system that informs the medical services to attend to the accident. The system can further manage the traffic flow in that region to aid emergency vehicles.
Traffic Management in Perth, Australia
Multi-skilled Road Network Operation Centre (RNOC) manages traffic across 18500 Km of Western Australia roads. The nerve centre for traffic operations in the metropolitan region and the state operates 24*7 monitoring the roads in real-time. The information about the live state of the road come from a range of sources through Sensors, CCTV Cameras, and Bluetooth Beacons. Traffic control in Perth happens each time one gets in the car.
Traffic Management in Moscow, Russia
Moscow has witnessed a rising share of the automobile on roads. By the end of 2020, Moscow Metropolitan Region had 8.4 million registered cars. Traffic Control Centre in Moscow applies information technologies for traffic management. The installed system controls 40,000 traffic lights, 185 information screens, 3000 photo-video cameras, and 3900 sensors to track the traffic flow. The system evaluates the road traffic situation in real-time, makes a short forecast, and informs the travellers through SMS and push notifications about changes in the public transport operation and traffic situation.
The management of road traffic problems has been an ongoing process in developed and developing worlds. Intelligent Traffic Management is significant to utilising the modern key functions of transportation like traffic control, traffic law enforcement, and traffic enforcement dissemination in the city. The growing trend in the Internet of Things (IoT) and Artificial Intelligence (AI) can surely shape a better future for Intelligent Transport.