Road user behavior: Describing, inferring, predicting and beyond

The continuous increases in the numbers of road traffic crashes (RTC) over the years, especially in developing countries, have been a source of worry. The majority of the RTC are attributed to road user behaviours exhibited by the drivers. This study sets out to investigate the road user attitudes and behaviours in Abuja, Nigeria. A total of 1526 questionnaires were distributed, of which 321 questionnaires were completed and returned. The questionnaires tried to understand four major road user behaviours, namely use of seatbelts, drink driving, use of mobile phone while driving, and use of child restraints. The results after analysing the questionnaires showed that the majority of the road users in Abuja showed high non-compliance with the use of seatbelts, either when driving or when being driven. About 64% of the respondents admitted to not using seatbelts. Results from the cross-tabulation process showed that the high non-compliance to seatbelt usage was statistically associated with young, single road users. Around one-third of Abuja road users admitted to drink driving. Road users who were married engaged in more frequent drink driving than road users who were single, and the association was statistically significant. A high percentage of Abuja road users admitted to using mobile phones while driving and 55.8% of the total respondents admitted to not using child restraints while driving. A lack of child restraints was statistically associated more with male road users than female road users. It is recommended that stricter enforcement of road safety laws should be undertaken and that the government should provide road safety agents with the right equipment (e.g., speed guns, breathalyzers) that would aid road safety agents to perform their duties effectively in order to curb the excessive bad road user behaviours in Abuja.

Human behavior plays a major role in the causation of road traffic crashes and the severity of their outcomes. The accurate and detailed registration of road user behavior is therefore...

Developing a safer road user behaviour index

A human driver determines his/her driving action by predicting future behavior of other road users based on the consideration of relative relationships and reactions between all players. To get as close as possible to human driving behavior, it is important to predict the early and long-term behavior of other road users. For this sake, many motion-based methods has been proposed, although only for short-term prediction. On the other hand, reasoning-based methods for long-term prediction have been proposed recently. However, they can only predict the latest behavior to the observation and do not consider uncertainty, which is necessary to realize smooth autonomous driving behavior. Therefore, we propose a method that predicts long-term behavior of other road users with estimated probabilities based on semantic reasoning that considers interactions among various players. For this purpose, we define an ontology that provides a conceptual description of all road users with their interactions, and infer the likely behaviors with their associated probabilities using Markov Logic Network (MLN). This framework is used with a actual vehicle as it approaches intersections, to demonstrate its applicability. Results from the real-time implementation on the vehicle, operating under controlled conditions, indicate that the proposed approach predicts a sequence of behavioral possibilities with their associated probabilities as expected.

Using the Event Analysis of Systemic Teamwork (EAST) to explore conflicts between different road user groups when making right hand turns at urban intersections

Key challenges in tram/streetcar driving from the tram driver’s perspective – A qualitative study

Virtual traffic benefits a variety of applications, including video games, traffic engineering, autonomous driving, and virtual reality. To date, traffic visualization via different simulation models can reconstruct detailed traffic flows. However, each specific behavior of vehicles is always described by establishing an independent control model. Moreover, mutual interactions between vehicles and other road users are rarely modeled in existing simulators. An all-in-one simulator that considers the complex behaviors of all potential road users in a realistic urban environment is urgently needed. In this work, we propose a novel, extensible, and microscopic method to build heterogeneous traffic simulation using the force-based concept. This force-based approach can accurately replicate the sophisticated behaviors of various road users and their interactions in a simple and unified manner. We calibrate the model parameters using real-world traffic trajectory data. The effectiveness of this approach is demonstrated through many simulation experiments, as well as comparisons to real-world traffic data and popular microscopic simulators for traffic animation.

Incorporating systems thinking approach in a multilevel framework for human-centered crash analysis

UDRIVE is the first large-scale European Naturalistic Driving Study on cars, trucks and powered two-wheelers. The acronym stands for “European naturalistic Driving and Riding for Infrastructure & Vehicle safety and Environment”. The purpose of the study is to gain a better understanding of what happens on the road in everyday traffic situations. The paper describes Naturalistic Driving Studies, a method which provides insight into the actual real-world behaviour of road users, unaffected by experimental conditions and related biases. Naturalistic driving can be defined as a study undertaken to provide insight into driver behaviour during everyday trips by recording details of the driver, the vehicle and the surroundings through unobtrusive data gathering equipment and without experimental control. Data collection will take place in six EU Member States. Road User Behaviour will be studied with a focus on both safety and environment. The UDRIVE project follows the steps of the FESTA-V methodology, which was originally designed for Field Operational Tests. Defining research questions forms the basis of the study design and the specification of the recording equipment. Both will be described in this paper. Although the project has just started collecting data from drivers, we consider the process of designing the study as a major result which may help other initiatives to set up similar studies.

This paper describes the method of field trips to traffic parks which are expected to instill awareness of passing in early childhood. The background is that in general the community does not see the correct knowledge of traffic. The level of awareness of road users on the importance of safety is minimal, due to the lack of attention from families and educators. As an educator, it is not only based on completing the preparation, but also must be able to provide or instill a good personality education because of the character education for students, it can be ascertained that the student's personality will be good. The core of planting traffic awareness in Early Childhood Education through the field trip method is that educators try to convey and convey the steps in cultivating awareness to early childhood using the field trip method, namely the learning process while playing integrated with the introduction of values which opens up an agreement so that children enthusiastic children, the core activity of instilling traffic ethics is the behavior of road users in implementing traffic laws and regulations as well as norms of courtesy among road users, namely around questions and answers about core activities, greetings and prayers. The learning process using the field trip method is expected when the child understands the knowledge of traffic rules and behaves as a correct road user.

Understanding interactions between Automated Road Transport Systems and other road users: A video analysis

This research investigates the potential implementation of Electronic Road Pricing (ERP) in Bandung City, Indonesia, focusing on its effectiveness in reducing traffic congestion. The study employs a quantitative approach using a survey method, experiments, and statistical analyses to evaluate ERP's impact on road traffic performance and cost efficiency. The research design includes traffic volume analysis, vehicle operating costs, and data collection through questionnaires from Bandung residents selected randomly. The research subjects include frequent road users in congested areas, and the study was conducted in 2023. Using binary logistic regression, the results show significant shifts in road user behavior, with reductions in traffic volumes of 33% on Jalan Sukajadi, 38% on Jalan Dr. Djunjunan, and 23% on Jalan Terusan Jakarta. Additionally, ERP was found to improve cost efficiency in traffic management. The study concludes that ERP is a promising solution for managing congestion in Bandung, with broader implications for other congested cities in Indonesia.

When humans share space in road traffic, as drivers or as vulnerable road users, they draw on their full range of communicative and interactive capabilities. Much remains unknown about these behaviors, but they need to be captured in models if automated vehicles are to coexist successfully with human road users. Empirical studies of human road user behavior implicate a large number of underlying cognitive mechanisms, which taken together are well beyond the scope of existing computational models. Here, we note that for all of these putative mechanisms, computational theories exist in different subdisciplines of psychology, for more constrained tasks. We demonstrate how these separate theories can be generalized from abstract laboratory paradigms and integrated into a computational framework for modeling human road user interaction, combining Bayesian perception, a theory of mind regarding others' intentions, behavioral game theory, long-term valuation of action alternatives, and evidence accumulation decision-making. We show that a model with these assumptions-but not simpler versions of the same model-can account for a number of previously unexplained phenomena in naturalistic driver-pedestrian road-crossing interactions, and successfully predicts interaction outcomes in an unseen data set. Our modeling results contribute to demonstrating the real-world value of the theories from which we draw, and address calls in psychology for cumulative theory-building, presenting human road use as a suitable setting for work of this nature. Our findings also underscore the formidable complexity of human interaction in road traffic, with strong implications for the requirements to set on development and testing of vehicle automation.

Developing public safety relations in large public infrastructure tunnels

Road user behaviour with a special focus on vulnerable road users—technical, social and psychological aspects