# Human and Environmental Factors Analysis in Traffic Using Agent-Based Simulation
## 1 Introduction  
Problems related to traffic management are among the most frequently discussed in countries all around the world. Such problems include traffic accidents and congestion [1]. Traffic congestion refers to long queues of vehicles waiting for the activation of a traffic signal or for other vehicles. This situation can cause environmental pollution by excessive expulsion of gases into the atmosphere, fuel consumption and noise pollution [2]. In addition to environmental damage, it causes a delay in the routine and work activities of drivers and pedestrians [1]. The occurrence of unfortunate traffic situations is often caused by imprudent human behavior [3]. Human performance is a determining factor in the traffic scenario [3]. Road users decide whether or not to obey the signals, the travel speed, and whether or not to commit infractions; therefore, the evaluation of traffic configurations must consider human behavior [4]. Characteristics such as age, gender, or driving experience have been shown to be determinants of a person's behavior on the road [5, 6]. In addition, other external elements can affect people's decisions, including road pavement [7] and weather [8, 9]. The effect of these external factors will vary according to the main characteristics of the person. Therefore, in addition to analyzing how the person behaves on the road, it is also necessary to evaluate their reaction to events such as driving on a bad road or the occurrence of rain or fog. Because of the number of factors that influence the results of a configuration, and the economic and labor costs of a counterproductive placement, they should be simulatedprior to installation [10]. A technique that has proven to be effective in the evaluation of traffic configurations is agent-based simulation [11]. Intelligent agents offer advantages in modeling human behavior because they are autonomous, reactive, proactive and socially skilled [4]. Through simulation, it is possible to obtain--with a degree of certainty--the performance of such a signal configuration once in operation. There are many metrics to evaluate the performance of a configuration: the number of accidents, the number of violations, and the waiting time of the simulation. Since the number of accidents, violations and the volume of vehicles directly influences the time that each vehicle delays within the simulated traffic region, it was decided to use the waiting time as an evaluation metric in this paper [12]. Therefore, to represent waiting situations that are generated on the road, queuing systems are used [13], where vehicles and people are customers waiting for the signal activation service. Although the literature reviewed models various characteristics of people and their influence on traffic, there is no association between the different factors that confluence on the road, which can be human, vehicle or external, based on the human response to each of these factors. The approach in this paper is novel in addressing human factors in an agent-based simulation model of urban traffic. Note that with agents it is possible to model different behaviors for traffic users, so they do not act all uniformly, but some variations can be specified, such as drivers not always respecting norms and signals on the road, or certain disabilities for pedestrians. The external elements modeled are weather, pavement, the technical condition of the vehicle and animals on the road. The experiments are based on the age of the traffic users, and in addition, the age-dependent reaction to pavement conditions. Thus, the relationship between various types of factors on the road, both human and environmental, will be also shown. The main contribution of the paper is given by the integration between the characteristics of traffic users and the external elements to evaluate their behaviors and reactions. The model can be easily extended to include new characteristics and human behaviors that are considered of interest for the analysis of signal configurations.