Understanding pedestrian behavior at unsignalized intersections becomes crucial for improving traffic safety. In this study, the crossing speeds of pedestrians at four unsignalized intersections in Izmir, Türkiye were investigated. Data were collected on weekdays for one hour each during peak and off-peak hours using unmanned aerial vehicles and cameras. The study incorporated pedestrian crossings executed on the designated crosswalks, as well as those occurring within 30 meters from the crosswalk. Two of the intersections did not have crosswalks, thus pedestrian crossings within the initial 40 meters from the roadway were considered. This study employed the eXtreme Gradient Boosting (XGBoost) machine learning algorithm to predict pedestrian crossing speed based on a comprehensive set of factors. Hyperparameter tuning was performed to optimize the model’s performance. Various features, including the existence of a crosswalk, pedestrian age (young, adult, elderly), gender, group crossings, and load-carrying situations were considered in the model. The results of the study provide valuable insights for traffic management. This research contributes to the ongoing efforts to enhance pedestrian safety.

The idea of sustainable campuses gives particular importance to walking as the primary travel mode. Hence, pedestrian-friendly facilities should be built to achieve this goal. This study investigates the pedestrian walking behavior on the sidewalks on the Ege University campus in Türkiye. The campus is the size of a smaller city with 55,000 students, 3,395 academic staff, and 7,098 administrative personnel. The policy of Ege University is to reduce the number of motorized vehicles on campus. The ‘park and walk’strategy has been adopted to achieve this goal. Two parking lots have been built at the campus entrance, and those entering the campus are directed to park their vehicles in these parking lots. Therefore, walking is the primary travel mode on campus. In this study walking speed of pedestrians on sidewalks and the factors affecting the walking speed were found. Sidewalks provide safe walking areas for pedestrians; however, as the density increases, pedestrians tend to walk on the street either reserved for bicycles/e-scooters or motorized vehicles. Field observations were made at four sidewalk segments of the campus with video cameras in April 2022. Pedestrians were categorized according to gender, group size, item carrying, earphones, and cellphone usage (talking or texting). A total of 1061 pedestrians were observed. The data were used for computing the average walking speed on sidewalks on the campus. ANOVA was used to determine the factors affecting the walking speed. When all pedestrians were evaluated, the average walking speed on the campus was found to be 1.33 m/s.

Urban mobility is a critical aspect of modern city life, and the integration of sustainable transportation modes, such as cycling, has gained prominence. However, in Izmir, a vibrant city in Turkey, there are limited cycling routes, which poses a challenge for cyclists. This study aims to model the behaviour of individuals who choose to cycle in İzmir despite the lack of proper infrastructure, particularly focusing on their interaction with public transportation. To achieve this, we employ binary logistic regression to analyse the factors influencing individuals’ decision to combine cycling with public transportation. Variables considered include travel distance, travel purpose, bike use frequency, socioeconomic factors, and the availability of alternative transportation options. The dataset is derived from surveys conducted among cyclists in İzmir, capturing their preferences, challenges faced, and motivations for choosing this …

Future travel demands should be predicted accurately in order to plan, make operational decisions, and manage urban public transportation systems. The success of the developed prediction model will directly affect the success of the transportation plan. Many factors, such as day of the week, weather, whether there is a large organization in the city, whether schools are open, affect the demand for urban public transportation.

Known for their environmentally friendly, cost-effective, and quiet operation, electric buses come forward as ideal public transportation solutions for urban areas. On the other hand, their limited driving range, depending on their battery capacities, hinders their wider adoption. Implementing the opportunity charging strategy can serve as a solution to address this inherent challenge of electric buses. This strategy allows buses to charge at bus stops using wireless chargers during the dwell time. However, it introduces another challenge, known as the Charging Infrastructure Location Problem (CILP), which involves optimizing the charger locations on transit networks.