© 2021 JETIR May 2021, Volume 8, Issue 5 www.jetir.org (ISSN-2349-5162) JETIR2105525 Journal of Emerging Technologies and Innovative Research (JETIR) www.jetir.org d976 Survey of Intelligent Traffic Management Systems with Emergency Vehicle Detection: A Review Thotapalli Nitin 1 ,Umang Sharma 2 ,Virendra Singh 3 ,Karande Sumit Dnyandeo 4 , Kanwaljeet Singh 5 1,2,3,4 UG. Students, Lovely Professional University, Phagwara, Punjab, India 5 Assistant Professor, Dept. of Electronics and Communication Engineering, Lovely Professional University, Phagwara, Punjab, India. Abstract - In metropolitan cities, traffic congestion has emerged as a major problem. The annual increase in automobile population is 14.19 percent, resulting in increased noise emissions, air pollution, collisions, and travel time delays. Owing to a lack of automated processes, current traffic signals in cities are inefficient and insufficient to solve the problems listed above. The traditional traffic system uses pre-determined times for red and green signals, requiring third parties such as traffic cops to manually manage traffic. On average, Indians spend 7% of their day commuting to work, with a time per kilometer of less than 3 minutes. This paper compares and contrasts various traffic control methods and explores the advantages and drawbacks of each approach. Key Words: Congestion control, emergency vehicle detection, intelligent traffic management system, traffic signal control, traffic analysis, traffic density. I. INTRODUCTION India is the world's second most populated country and has a rapidly growing economy. Its cities are experiencing severe traffic congestion. Owing to space and cost constraints, infrastructure development is slower than the growth in the number of vehicles. In addition, Indian traffic is non-lane dependent and chaotic. It necessitates traffic management solutions that are distinct from the standard. Intelligent traffic flow management can mitigate the negative effects of congestion [1]. As the number of cars on the road has increased, traffic congestion has increased. This has made it difficult for ambulances to transport patients to suitable destinations on time in the event of an emergency. According to statistics, more than 20% of patients in need of immediate medical treatment die en route to the hospital as a result of delays [2]. Road incidents take the lives of 3,000 people every day, according to the International Road Federation's Geneva Program Center. This equates to 1.3 million deaths per year and a total of 2.4 million deaths from traffic accidents [3].However, the issue of an ambulance failing to arrive at its destination has yet to be resolved. To fix this problem, a system must be put in place that allows ambulances to easily pass through the traffic to get to the nearest hospital. This paper provides a comparative review of the different techniques that are used by different authors to automate and improvise the traffic management and detect emergency vehicles through Web sockets efficiently. One of the methods uses manual traffic mode to implement an intelligent traffic management system [4] while another author used wireless sensor network [5] which collects data from the sensors installed on the traffic lanes at the junction and interprets the data received. This paper presents a comparative analysis of the various methods used by various authors to automate and improve traffic control and effectively identify emergency vehicles. One approach implements an adaptive traffic management system using manual traffic mode [4], while another author used a wireless sensor network [5] that collects data from sensors mounted on the traffic lanes at the junction and interprets the information collected. A framework in [8] [9] uses Neural Networks to dynamically control traffic and plan future actions. In [11] [12], the author employs an image processing technique to measure and detect the presence of emergency vehicles at a given intersection. Surveillance cameras mounted at traffic signals are used to capture a live feed of traffic and the location of emergency vehicles, which is then processed using image processing techniques in order to automatically change traffic signal timings and thereby manoeuvre emergency vehicles out of traffic as quickly as possible. The remaining part of the paper is laid out as follows. Section II examines the current state of research and development for an intelligent traffic management system. Section III compares and contrasts all of the current processes. Section IV addresses the benefits and drawbacks of all of the approaches discussed in this article. Section V wraps up all of the approaches with a conclusion. II. LITREATURE SURVEY 2.1. Manual traffic management system As explained in [4] a typical traffic system is based on timers that are programmed for a particular interval. This is the most widely used traffic control scheme, which is overseen by traffic cops. This device entails a traffic law enforcement officer who stands at each lane intersection and controls traffic flow with the help of a traffic sign. The vehicle operator receives a signal from the traffic enforcer to drive the vehicle or stop if the frequency of vehicles on the lane is higher. The traffic enforcer will offer priority to the lane with a priority vehicle present, allowing that vehicle to pass first. When there are several emergencies, the person becomes perplexed, and it becomes difficult for him or her to handle the traffic. This method is also effective during rush hour and