IPN wins National Transportation Award 2023

Adda Avendaño

With two research projects involving technology, color psychology, and artificial intelligence to enhance vehicular agility in large cities, the Instituto Politécnico Nacional (IPN), through the Unidad Profesional Interdisciplinaria de Energía y Movilidad (UPIEM) and the Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada (CICATA), Querétaro Unit, secured the first place in two categories at the 14th edition of the National Urban Transportation and Mobility Award 2023.

Announcing the winners, Nicolás Rosales Pallares, president of the Mexican Association of Transportation and Mobility, the organization behind the award, noted that the competition was fierce among projects promoting the use of artificial intelligence and various technologies, while also emphasizing the human factor. He thanked the jury for their work.

Enhanced Safety and LED Lights for Metrobús Platforms

To reduce the risk of accidents, suicides, and fare evasion by passengers at Metrobús arrival platforms, a group of UPIEM students presented a proposal for security doors and LED lights in blue and green implemented on the infrastructure of Metrobús Line 1. This project secured first place in the category of Urban Transportation and Mobility Projects.

Inspired by major cities like Tokyo, Rio de Janeiro, and Madrid, the project was developed by students of Energy Systems and Intelligent Networks Engineering (ISERI): Selene Minerva Guerrero Villeda, Ana Daniela Aguilar Cuevas, and Gabriel Mendoza Mendoza, led by Fernanda Cardenas Montes de Oca, a student of Urban Mobility Engineering, who presented the original idea.

The students and the Polytechnic professor team, advised by Dr. José Alejandro Aguirre Anaya and Ms. Andrea Rendón Peña, explained that this transportation system has faced accidents such as falls or people pushed by the crowd or attempting to enter platforms without paying. This led to the development of a design that combines telescopic and sliding security doors. El equipo de la UPIEM ganó al presentar una Propuesta de puertas de seguridad para andén y luces LED en color azul y verde implementadas en la infraestructura de la línea 1 del Metrobús

"The telescopic doors are vertical folding leaves that pull toward each other using a pulley system. In this case, the dimensions, normally designed for larger entrances, would be reduced to about four meters, and an acrylic and aluminum sliding door system would be used to save space on the platform," explained Selene Guerrero, the project's designer.

LED Lights in Blue and Green for Relaxation

Being a frequent user of Metrobús Line 1, Fernanda Cardenas mentioned witnessing how people become agitated during peak hours for various reasons. She proposed implementing LED lights in blue and green on the platforms to create a calming environment.

"Researching the topic, I found that there are colors that produce certain effects on humans. For example, combining blue, yellow, and green creates the color white, which represents light, peace, and tranquility. Blue is associated with freshness, and green connects with nature. Together, they promote relaxation and calmness," explained Cardenas Montes de Oca.

According to Daniela Aguilar, the proposal provides comprehensive security because the doors prevent suicides or unintentional falls caused by pushing during peak hours. Additionally, it could control access for individuals not paying the fare and the danger they expose themselves to by entering the vehicular traffic area. The LED lights would contribute to creating a calm and peaceful atmosphere, especially during crowded times.

Although the National Urban Transportation and Mobility Award 2023 was a national competition, participants from universities in Argentina, Brazil, and Chile were also registered, and the Polytechnic team outperformed them, showcasing the high-quality education provided by UPIEM, despite being one of the youngest academic units of the Instituto Politécnico Nacional.

Dynamic Behavior in Articulated Vehicles

In the category of Postgraduate Theses, Mauricio Eliseo Cruz Acevedo, a graduate of the Master's level at CICATA Querétaro, secured first place in the National Urban Transportation and Mobility Award 2023 with the thesis: "Development of Vehicle-Driver Models for Articulated Vehicles Using Artificial Intelligence."

According to the World Health Organization (WHO), more than 1.3 million people die annually, accounting for 30 percent of total deaths related to accidents involving heavy vehicles. In 2019, Mexico recorded 18,786 traffic accidents resulting in 2,265 deaths, according to data from the Instituto Nacional de Estadística y Geografía (INEGI).

Transporting large volumes of goods and people on the road, heavy vehicles such as trucks, tractor-trailers, and buses are a crucial part of the global economy's supply chain. However, safety has been a significant issue, as accidents involving these large vehicles can be especially dangerous, even fatal, due to their weight and size.

The thesis, supervised by Dr. Ilse Cervantes Camacho of CICATA Querétaro and Dr. Manuel de Jesús Fabela Gallegos of the Mexican Transportation Institute (IMT), proposes predicting the dynamic behavior and risks of instability that these types of vehicles might face. These include single-trailer trucks (articulated tractor-trailers) and double-trailer trucks (doubly articulated tractor-trailers), considering load distributions, abrupt lane-changing or obstacle-avoidance maneuvers, and the physical-mechanical conditions they may present.

Mauricio Eliseo Cruz Acevedo won first place for his work "Development of vehicle-driver models for articulated vehicles using artificial intelligence".

To develop the predictive model, artificial recurrent neural networks were used along with the creation of a database. This allowed the postgraduate student to develop a model predicting risk behaviors by considering the direction in which the vehicle is moving (Heading Direction), lateral and longitudinal accelerations, and angular velocities of pitch (Pitch Rate), yaw (Yaw Rate), and roll (Roll Rate). These indicators would serve as flags or warnings to avoid accident risks.

Integrating Artificial Intelligence for Prediction

For the algorithm that determines the predictive model, recurrent neural networks were used. Forty-two experimental tests were conducted to obtain experimental data under abrupt lane-changing and obstacle-avoidance maneuvers at different speeds. Nine panic braking tests were also conducted to determine the distance a vehicle would travel and the time it would take to come to a stop.

"The completion of experimental tests would not have been possible without the collaboration of the Vehicle Dynamics Laboratory group at the Mexican Transportation Institute and the Logistics and Distribution Management of the National Cargo Transportation Association (ANT), who supported me in having access to the vehicles," noted the Mechatronics engineer. Master Cruz Acevedo considered that the greatest difficulty in feeding the model with more data was the availability of vehicles and the time required between each test. There was also significant wear on the tires, brake pads, and suspension of the trucks used in panic braking tests. However, the model is ready to receive more data, continually improving the accuracy of its predictions.

The annual call by the Mexican Association of Transportation and Mobility, A. C. (AMTM), aims to encourage, promote, and sponsor the generation of studies, research, and projects that improve, innovate, and modernize transportation models and systems. This contributes to optimizing urban mobility, a crucial factor for economic productivity and the quality of life for citizens living and moving in urban centers.

Selección Gaceta Politécnica #168. (November 30th, 2023). IPN Imagen Institucional: Read the full magazine in Spanish here