Congestion in urban transportation is a significant challenge, often exacerbated by increasing private vehicle use and limitations in public transport. This study introduces a two-stage approach combining multi-criteria assessment and traffic simulation to examine current conditions and propose improvements. Initially, data on five primary and twenty-one secondary factors affecting public transport choice are assessed using the Best–Worst Method (BWM). The findings reveal that convenience is prioritized by working professionals, while travel cost is most important to students. A baseline simulation model is established using a case study at Kaset Intersection in Bangkok. Incorporating weighted preferences into the simulation aims to enhance public transport and encourage private car users to switch modes through potential traffic management policies. Additionally, a micro-simulation assesses the impacts of decreased traffic density, revealing that a reduction in traffic density can shorten overall travel time by about 2.04 s, based on regression analysis. The results suggest policies to improve public transport, reduce traffic density, and enhance urban transport system performance.

The widespread deployment of information and communication technology (ICT) has allowed ride hailing services to grow exponentially over the last few years. This study aims to investigate ride hailing use frequency among university students in Banda Aceh, Indonesia. The city offers unique characteristics since it has limited public transport facilities, a growing number of vehicle ownership, and traffic dominated by motorcycles. Ride hailing services in this city are predominantly motorcycle-based, hence they could potentially have substitution effects on private vehicle use and ownership. This study focused on university students because their travel behaviour often differs from general public, and they form the majority users of ride hailing services. Ordinal logistic regression was employed, drawing from 219 valid responses from a survey disseminated in 2023. The variables explored include individual and household characteristics, travel attributes, and perceptions on ride hailing services. It was found that the most significant factors that encourage students to frequently use ride hailing services include working part-time, having high allowance, perceiving good level of convenience and service. On the other hand, attributes that have the biggest effects in discouraging ride hailing use include low travel cost, sitting in 5th semester or later, and living in a private house. This study offers insights into ride hailing behaviour in the context of a city with limited public transport facilities and severe motorcycle composition, which can help regulators and operators to improve policies around the platforms.

This study applies Evolutionary Game Theory (EGT) to analyze transportation mode choices in Jakarta, a city grappling with severe traffic congestion and diverse mobility options. Four modes are modeled: public transportation, private vehicles, ride-hailing services, and a combination of public transportation and ride-hailing. The research incorporates Jakarta-specific variables, including traffic congestion, odd/even zoning policies, and cost constraints, to simulate how commuters adapt their strategies over time. By estimating payoffs based on travel time, cost, and policy impacts, the EGT framework reveals the evolutionary stability of mode choices. Results indicate that cost and travel time dominate decision-making, with odd/even zoning significantly reducing private vehicle use. These insights offer a foundation for designing sustainable urban mobility policies tailored to Jakarta’s unique context.

This study attempts to observe how settlement patterns influence mobility preferences, with primary attention directed to private vehicle accessibility to Batam International University (UIB). A quantitative approach was taken, where data were collected both online and offline through a survey distributed to 235 respondents drawn from the academic community. The analytical process used descriptive statistics, Pearson correlation, chi-square tests, and multiple linear regression to trace the relationship between residential conditions and perceived accessibility. The results indicate that 68.1% of respondents commute by motorcycle, while 43.8% live within planned housing areas. Certain factors, including private vehicle ownership and residential status, show a statistically significant relationship with accessibility satisfaction, measured through indicators such as travel time, ease of access, and road conditions. The regression output further shows that type of residence, transport mode, and study program together explain approximately 32.9% of the variance in accessibility satisfaction, suggesting an influence that exists but does not fully account for it. Additionally, the findings highlight that two-wheeled vehicles tend to perform better than four-wheeled ones in terms of flexibility and time efficiency, particularly in areas where road infrastructure is congested or underdeveloped. These outcomes point to the necessity of integrating settlement planning with sustainable transportation strategies to gradually reduce reliance on private vehicles. Educational institutions and local government are therefore recommended to strengthen public transport services, promote multimodal accessibility, and implement infrastructure improvements focused on residential zones with low accessibility. By presenting empirical evidence from a Southeast Asian island city, this research contributes to the broader discussion on campus mobility, spatial equity, and transport policy in rapidly urbanizing regions.

Cervical cancer remains a leading public health problem in Indonesia, with low screening and HPV vaccination coverage, particularly in rural areas where knowledge gaps and limited healthcare access persist. This study aims to assess the knowledge, attitudes, and practices (KAP) regarding HPV infection and cervical cancer, and the role of information-seeking behavior in identifying effective channels for raising awareness on these issues. A cross-sectional study was conducted between 20 March 2023 and 20 January 2024, involving 220 women from two rural districts in North Moluccas, selected via convenience sampling. Data were collected using a validated questionnaire administered through face-to-face interviews. Data were analyzed using SPSS version 25.0 with descriptive statistics, normality testing (Kolmogorov-Smirnov), bivariate analyses (Chi-square, Fisher's Exact, Pearson's or Spearman's tests), and multivariate logistic regression (backward LR, p < 0.05), with model performance assessed using ROC curves and AUC values. Most participants demonstrated poor KAP, with 18.7% showing good knowledge, 22.7% expressing a positive attitude, and 44.5% engaging in favorable practices. KAP were found to be positively correlated (p<0.001). Key predictors of good knowledge included higher education (AOR = 7.07), family history of cancer (AOR = 15.20), private vehicle use (AOR = 4.15), and active health-information seeking behavior (HISB) (AOR = 3.41). Determinants for a positive attitude included higher education (AOR = 3.79), family history of cancer (AOR = 4.42), active HISB (AOR = 3.88), and good knowledge (OR = 10.29). Favorable practices were influenced by private vehicle use (AOR = 2.66) and positive attitude (AOR = 20.62). In conclusion, KAP are influenced by HISB, and involving healthcare workers in providing information, particularly through digital platforms, has the potential to improve KAP in rural communities.

Estimating factors influencing mode choice behaviors has posed a significant challenge for decision makers. In this paper, we propose a three-step method to estimate mode choice between public transportation and private vehicles within a heterogeneous metropolitan area. First, we implement a deep learning model, Altaïr, capable of inferring travel times and travel flows by leveraging multi-source input data (Step 1). To identify homogeneous sub-regions regarding mode choice behaviors, two data clustering models are performed: k-means and a Gaussian Mixture Model (GMM, Step 2). The GMM reveals three spatial clusters based on the relationships between relative travel times and relative travel flows in public transportation and private vehicles. Moreover, an econometric model (robust ordinary least squares) is employed to identify additional explanatory variables, including sociodemographic features and location variables (Step 3). This hybrid method is currently employed in the Paris metropolitan area (France). At the metropolitan level, we find that competitive travel times in public transportation lead to higher ridership. Conversely, when the time ratio exceeds approximately 3.5–4, public transportation use becomes negligible in comparison to private vehicles. The method's results align with those of the regional Household Travel Surveys (HTS) regarding the individual attributes influencing public transportation use (share of women and students in the municipality of residence) or private vehicle use (share of car owners and people over 55). There is significant car use in peripheral areas, but public transportation accessibility promotes higher flows in this mode everywhere, with the exception of central Paris. • We use a three-step method to estimate mode choice behaviors in a metropolitan area. • A deep learning model infers travel times/ travel flows from multi-source input data. • Using the relationship between the two variables, a GMM reveals spatial clusters. • An econometric model highlights other explanatory variables for mode choice behaviors. • Our method can guide transport policies in areas where HTS are too difficult or costly to implement.

Agent-based models have become valuable tools in transport planning, particularly for evaluating mobility policies in complex urban contexts. The model simulates the daily activity-travel patterns of approximately 3 million agents (10% of the population in Greater Jakarta), incorporating socio-demographic attributes and activity chains from household travel surveys. The modelling process includes population synthesis, activity imputation, and calibration against observed mode share, trip distances, and activity distributions, resulting in a realistic representation of urban travel behaviour. This study further develops policy scenarios and assesses the impact of distance-based electronic road pricing (ERP) for private cars and motorcycles. ERP scenarios are applied to eight major arterial roads in Jakarta, with tolls differentiated by travel distance and agent income using a Discrete Mode Choice (DMC) framework through Eqasim. Results show that ERP effectively reduces private vehicle use, particularly during the evening peak, where car traffic decreases by up to 19.95% and motorcycle traffic by 14.21% under the highest pricing scenario. However, the impact during the morning peak is more modest, reflecting lower travel flexibility. The results also show that the impact varies across socio-demographic groups, with stronger effects observed among low-income individuals, female users, working-age individuals, and employed persons.

Background Low Emission Zones (LEZs) aim to improve air quality and encourage sustainable travel in urban areas by issuing fines to non-compliant vehicles. This study investigated initial impacts on travel behaviour and perceptions following the enforcement of Edinburgh's LEZ from June 2024. Methods We conducted an online cross-sectional survey focussing on commuting behaviour inside and outside the LEZ, as well as prior to and several months after enforcement. The survey targeted adults who worked or studied in Edinburgh or otherwise travelled to the LEZ area. We collected data on demographics, travel habits, and reasons for travel choices. To maximise response, we recruited participants via an online survey panel (‘panel survey’ [ n =351]) and social media (‘community survey’ [ n =260]), for which statistical analysis was stratified. Results Following LEZ enforcement, there was a clear differentiation in transport mode usage, with more people using the car alone for their commute outside the LEZ and more people using public transport inside the LEZ. Few respondents changed whether they accessed the LEZ area. Nevertheless, comparing inside to outside commuters, 70 (44%) versus 8 (10%) in the panel survey, and 41 (24%) versus 4 (9%) in the community survey, respectively, reported some change in the frequency, duration, or mode of transport following enforcement. Results suggested a small, but statistically significant, shift towards active travel and public transport within the LEZ, with a decrease in private vehicle use. Panel survey respondents tended to agree more than community respondents with the potential positive impacts of the LEZ. Conclusions We found evidence that active travel and public transport use increased within the first few months after the Edinburgh LEZ was enforced. Future research with objective, quantitative data should confirm these findings and assess impacts over a longer time-period.

Urban traffic congestion is a growing challenge in many rapidly expanding cities, including Daraga, Albay. The study examines the role of infrastructure strategies in alleviating traffic congestion in the barangays of Bagumbayan, Sagpon, and Market Area Poblacion. A combination of road network enhancements, public transit improvements, active transportation facilities, and urban planning measures is explored to address the issue. The research employs a cross-sectional design, collecting data from 1,050 respondents through surveys and interviews. The findings indicate a high level of satisfaction with infrastructure strategies, particularly urban planning policies, which were deemed crucial for long-term congestion mitigation. Road network enhancements, such as road widening and intersection improvements, provided short-term relief, while public transit infrastructure, including Bus Rapid Transit (BRT) and railway systems, emerged as vital alternatives to private vehicle use. However, active transportation infrastructure, such as pedestrian walkways and cycling lanes, remains underdeveloped and requires further investment to maximize its potential. The study highlights the importance of integrated urban planning, including mixed-use development and transit-oriented strategies, to reduce dependency on private vehicles. Environmental and economic impacts, such as increased fuel consumption and productivity losses, are also examined. The study provides actionable recommendations for policymakers in Daraga, focusing on sustainable mobility solutions and the development of resilient transportation systems to improve urban livability.

To alleviate expressway congestion caused by excessive private vehicle use, trip reservation has emerged as a proactive traffic management strategy. However, when too many vehicles are admitted within the same time window, the travel efficiency of reservation users deteriorates, compromising the strategy’s effectiveness. Conversely, admitting too few vehicles leads to underutilization of road resources and degrades the operational performance of adjacent roads. This study addresses this challenge by identifying the optimal reservation quota. A reservation‐based travel strategy is proposed for key corridors in urban road networks, comprising expressway segments and their parallel surface streets. The initial quota is determined through a dual‐threshold bottleneck breakdown analysis, which estimates the capacity of reservation segments under varying service levels. A bilevel programming model is subsequently developed to allocate traffic flow across the network based on the initial quota. Simulation results reveal that the reservation quota significantly affects the performance of the network. The optimal quota lies between 70% of the theoretical maximum capacity and the prebreakdown threshold, within which the key corridor network maintains moderate traffic conditions. Compared to the no‐reservation scenario, the average travel speed of reservation vehicles more than doubles (from 25.86 km/h to above 52.12 km/h), while the average travel delay is reduced by over 77% (from 774.77 s to below 179.01 s). The service level of reservation segments improves to Level C. Moreover, the strategy imposes minimal adverse effects on parallel surface streets, where average speeds decrease by less than 31% but remain above 22 km/h. These findings validate the effectiveness of the key corridors trip reservation system and confirm the optimal reservation quota range.

The concept of Transit Oriented Development (TOD) entails city planning for sustainable urban development, through a system, that aims to reduce the use of private vehicles and increase the interest in walking and transit areas utilization. Jalan Pandanaran is one of the supporting roads located in Simpang Lima area, which is crowded with offices, trade, and service centers. This area has the potential of becoming a regional center or Central Business District (CBD), which implies that it is capable of having a sustainable transportation system through the TOD concept depending on the Regional Center it is being applied to. Therefore, this study aims to identify, analyze and determine the concept of planning the Transit Oriented Development (TOD) system in the Pedestrian Path of Jalan Pandanaran. The method used was rationalistic quantitative with scoring analysis techniques and pedestrian analysis. The result showed a feasibility assessment on the pedestrian path on Pandanaran Street, through the application of the concept of TOD system planning based on the responsiveness of pedestrian users on the path.�

Traffic congestion that occur between the city of Surabaya and the surrounding buffer cities which are 30 to 50 kilometers away are caused by the increasing use of private vehicles and the decreasing use of public transportation because it is considered that the process will be complicated and travel ineffective. This will cause an imbalance between the capacity of the highway and the number of vehicles, resulting in traffic congestion, especially during peak hours. To overcome this problem, improvements are made to sustainable and community liveability in the form of optimal utilization of existing properties in the city, including rivers and existing railroad. With the background above, this paper will present the idea of a solution to overcome traffic congestion by utilizing the drainage channel or rivers and the single tracks railroad to become MRT lanes. This transportation system innovation will be proposed as an evaluation of the Indonesian Railroad Master Plan (2018 to 2030), specifically to be implemented in the city of Surabaya and surrounding.

The development of marine tourism destinations with numerous beaches along a single coastline, such as those in Gunungkidul, must consider tourists' spatial movement patterns. Now, tourists are shifting from crowded destinations, such as Baron Beach, to hidden gems that offer privacy and new visual experiences. This creates a significant shift in spatial movement patterns in the southern coastal region. Uncertainty in travel patterns hinders efforts to manage visitor flows and design efficient connections between destinations. This study aims to identify tourists' travel patterns to Kesirat Beach in Gunungkidul, which is becoming increasingly popular despite not offering white-sand beaches like those in other parts of Gunungkidul. A total of 97 people who encountered the researchers were given a questionnaire with closed-ended questions. The data were processed in SPSS and analyzed using a descriptive, quantitative approach. The results showed that tourist movement patterns were dominated by stopovers (78%), with short visit durations (57% for one whole day and 43% for less than one day). These results suggest that Kesirat Beach serves as a stopover point or as part of a longer travel route rather than as a final destination. Highlighting the high use of private vehicles (90%) and the preference for traveling in groups of friends (56%) underscores the importance of improving accessibility. This can help the audience feel responsible for creating inclusive and convenient access, encouraging better management of tourist flows.

Traffic congestion causes an increase in fuel consumption, vehicle operational cost, travel time, and increased traffic accidents, while at the same time reducing the air quality. Congestion pricing (CP) is one of the strategies that various cities have implemented to reduce private car usage, leading to improvements in traffic conditions and air quality. This study aims to determine the impact of congestion pricing on private vehicle use in Jakarta by modelling the probability of mode shift to public transport. Stated preference and binomial logit model are used to analyze the impact of congestion cost implementation on mode shift. The results show a possible shift from private cars to bus rapid transit (BRT) by 56% with the implementation of congestion pricing. The findings provide insight that congestion pricing has an impact on potential mode shift to public transport. The shift is influenced by the amount of the congestion charge imposed. The more expensive the congestion charge, the more likely car users are to switch to public transport.

The effectiveness of transit-oriented development (TOD) in achieving emission reductions and energy savings is highly influenced by policy frameworks, the accessibility of sustainable transport systems, and the degree of land use integration. This study investigated the implementation of TOD in Dukuh Atas along the Sudirman–Thamrin corridor in Jakarta to assess its role in promoting energy efficiency and lowering emissions. The analysis incorporated carbon emission calculations, annualized traffic volumes, and emissions data, alongside land use metrics such as the floor area ratio (FAR), job-to-housing ratio, and point-of-interest (POI) density. The findings indicate that while TOD implementation in the corridor is still evolving, there were positive outcomes in several key areas. Energy efficiency measures have been partially realized through the operation of electric buses in the bus rapid transit (BRT) system, electrified rail modes, such as commuter lines, mass rapid transit (MRT), and light rail transit (LRT), and improved pedestrian infrastructure, as reflected in a favorable Pedestrian Environmental Quality Index (PEQI). Public transport ridership has significantly increased, contributing to a measurable reduction in emissions from private vehicle use. The land use analysis showed that medium- to high-density housing dominated (78.94% FAR), with a job-to-housing ratio of approximately 1:2. This study also found that the emission estimates were moderately sensitive to changes in both emission factors (EFs) and vehicle kilometers traveled (VKT). Overall, the results suggest that TOD can effectively contribute to energy savings and emission reductions by enhancing public transport usage and reducing dependence on motorcycles. Moreover, the efficacy of modal shifting in the Global South is significantly influenced by population mobility characteristics, which are intricately linked to socio-cultural factors, alongside government initiatives to improve the quality of mass public transportation systems (e.g., integration, availability, service coverage, affordable fares, and inclusive design).

Public transportation is a fundamental element significantly influencing smart cities and smart mobility within communities. Banyumas Regency is currently one of the regions implementing the smart city concept in its urban development. One of the tangible proofs of this implementation by the Banyumas Regency government is the introduction of BRT Trans Banyumas, aimed at increasing public interest in using public transportation, facilitating more effortless mobility, reducing air pollution, and boosting the local economy. Evaluating public transportation services is essential to attract public interest, particularly regarding the intelligent public transport system (IPTS) aspects. This study evaluates Trans Banyumas services to analyze the level of IPTS implementation from the perspective of female passengers. Female passengers′ perceptions are used because women have unique mobility patterns, making them an essential indicator for assessing smart mobility. The method used in this research is General Linear Model ANOVA. Data collection was conducted qualitatively with 357 respondents. The test results show that demographics significantly influence the intelligent public transport system aspects: ICT, IoT, integration, safety and security, and smart accessibility and mobility. The result can be used to develop recommendations for improvements in the Trans Banyumas service related to intelligent public transportation system technology. However, implementing an intelligent public transport system in the Trans Banyumas service cannot be done individually. Therefore, there needs to be cooperation from both the government and the private sector to promote sustainable transportation, reduce the use of private vehicles, and minimize environmental impacts.

The rapid increase in private vehicle use has also boosted the growth prospects of repair shops in Indonesia. In this context, service plays a crucial role in creating new revenue streams for businesses while contributing to improved company performance. However, risk-taking is crucial in bridging the gap between the concept and implementation of this strategy. This study aims to identify the influence of service on company performance in repair shops in West Sumatra, with risk-taking as a mediating variable. Using quantitative methods, this study collected data from 80 repair shops in West Sumatra and analyzed it using a Structural Equation Modeling-Partial Least Squares (SEM-PLS) approach. The results show a positive and significant relationship between servitization and risk-taking, as well as between risk-taking and company performance. Furthermore, servitization has also been shown to have a positive and significant effect on company performance. Further findings indicate that risk-taking mediates the positive and significant relationship between servitization and company performance. Thus, this study confirms that servitization and risk-taking play a significant role in improving company performance. This research contributes to the broader understanding of business models, particularly in the repair shop sector, where the concept of service is generally studied more in the context of manufacturing companies. This research highlights how servitization can shape firm performance through its mediating role in risk-taking.

The influence of the built environment in the social impact of the low emission zones of Madrid (Spain)

Jakarta, the capital of Indonesia, faces persistent challenges with its public transportation system due to rapid urbanization, increased use of private vehicles, and poor service quality. While social media platforms such as X (formerly Twitter) offer valuable insights into public opinion, their unstructured nature complicates analysis. This study uses deep learning models to categorize user sentiments into six labels that cover positive and negative aspects of comfort, safety, and punctuality. The results show that IndoBERTweet achieved the highest performance, with 95.43% accuracy and a macro F1-score of 0.9545. It also required the shortest training time, at six minutes and 30 seconds. IndoBERTweet+GRU followed closely behind with an accuracy of 94.62% and a macro F1-score of 0.9460 in six minutes and 50 seconds. This shows that adding a GRU layer provides competitive results, but does not surpass the baseline model. Error analysis revealed that, while the models performed well with explicit sentiments, the models struggled with implicit expressions, such as sarcasm and mixed opinions. These results demonstrate the potential of sentiment analysis in real-time monitoring systems, which could help policymakers identify urgent issues and support data-driven improvements in Jakarta’s urban transportation services.

The transition to sustainable mobility requires the implementation of strategies that make the sector more environmentally friendly and efficient. In recent years, we have witnessed a transition phase, i.e. the implementation of policies and actions that reduce the use of private vehicles (especially those with combustion engines) and promote greener modes of transport such as public transport, cycling, walking and innovative, climate-friendly mobility solutions. It is therefore possible to implement a series of improvement measures and strategies (e.g. innovative tariffs, service quality, complementary services and greater efficiency, as well as the transition to green fleets). It is also essential to implement complementary transport services such as on-demand or shared. This research study analyses connections in the province of Ragusa—where a Demand Responsive Transport service (DRTs) operates—using a hub and spoke model to discretise travel patterns. This research analyses the aspects related to the time slots in which the service is used using a modelling linked to the Random Utility Models (RUMs) and through the definition of a binomial logit model (BNL). The choice of RUM enables identifying relationship between the chosen alternative and the individual decision. The calibrated model reveals that the most influential attribute in the choice of the time slot, for the service analysed, is the area of origin. This highlights how users choose the time slot mainly based on the area of origin, which, given the characteristics of the service, corresponds to the direction of travel; among other attributes tested, the availability of buses was found to be significant. The results are meaningful for improving the existing services and for defining a complementary service of local public transport and on-demand services. Furthermore, the proposed framework can be extended to other aspects of the decision process involved in DRT adoption.