Reducing emergency services arrival time by using vehicular communications and Evolution Strategies

Abstract

Nowadays, traffic jams in urban areas have become a problem that keeps growing every year since the number of vehicles in our cities is continuously increasing. One of the most common causes producing traffic jams are vehicle accidents. Moreover, the arrival time of the emergency services could be raised due to traffic congestion. Intelligent Transportation Systems (ITS) have a key role in order to reduce or mitigate this problem. In this paper, we propose four different approaches addressing the traffic congestion problem, comparing them to obtain the best solution. Using V2I communications, we are able to accurately estimate the traffic density in a certain area, which represents a key parameter to perform efficient traffic redirection, so reducing the emergency services arrival time, and avoiding traffic jams when an accident occurs. Specifically, we propose two approaches based on Dijkstra algorithm, and two approaches based on Evolution Strategies. Notice that, when an accident occurs, time is a critical issue, and strategies here proposed contribute to optimal solution within a short period of time.

Non-emergency patient transport services planning through genetic algorithms

“…In particular, we previously proposed an approach focused on traffic accidents urgent sanitary resource allocation based on multi-objective genetic algorithms ( Fogue et al, 2013 ), and a system able to reduce the emergency services arrival time by using vehicular communications and Evolution Strategies ( Barrachina et al, 2014 ).…”

Traffic density estimation in vehicular ad hoc networks: A review

“…However, the proposed density estimation method in [5,54], was evaluated by comparing the results to the actual density specified in the simulation environment. Table 4, summarizes the aforementioned density estimation algorithms which depend on vehicle to RSU communications.…”

“…However, this algorithm depends mainly on the availability and reliability of communication with RSUs and on the analysis of road maps to get the street to junction ratio. In [54], the polynomial equation, obtained in [5], was utilized to address traffic congestion problems and reduce emergency services arrival time.…”

Controlling Emergency Vehicles in Urban Traffic with Genetic Algorithms

“…A technique based on hybrid genetic algorithms was used (Jih et al 1999) for solving the problem of routing a vehicle with size constrains. Another example relies on Dijkstra algorithms (Barrachina et al 2014) and evolutionary strategies for finding an optimum path in a short period of time. Another approach presented in the project Emergency Vehicle Priority implies controlling the traffic lights in favor of the emergency crews (White, 2012), but this solution affects the rest of the urban traffic.…”