Due to the introduction of lockdown and curfew hours to control and minimize the spread of COVID-19, the most impact part of transport sector is paratransit drivers. This study aims to evaluate the impact of COVID-19 on paratransit services operating with Ride-Hailing App in Phnom Penh. Questionnaire surveys were used to collect data from 233 paratransit drivers who operate their services with RHA from Dec 30, 2020-Jan 02, 2021. The results show that drivers decrease in monthly income by approximately 49%, number of daily passengers by 59%, and monthly revenue by 46%. Drivers also expressed the difficultly of their livelihood during the pandemic such as payment for loans, high app commission fees and financial issues etc. The outcome of this study would be a good assistance for transportation planners, policymaking, government authorities such as knowledge or information to better guideway for COVID-19 pandemic response or another pandemic response.

This study analyzes the ownership of passenger cars, including light motor vehicles and ordinary motor ones incorporating unknown annual income and household structure. The fourth Person Trip Survey data in Nagoya metropolitan area, Japan, are used for the empirical study. According to their family structure, this study divides 85,047 sample data into nine groups. The annual income data are complemented using an ordered probit model. A bivariate binary probit model and a bivariate ordered probit model are used to model the car ownership of a single member and multiple members, respectively. The significant findings indicate that 1) the ownership of light motor vehicles is affected significantly by the household structure; that 2) annual income affects the ownership of light motor vehicles only for childless middle-aged single households. Researchers and engineers can refer to statistical methods proposed in this study to analyze car ownership in urban transportation planning.

From 2010 to 2019, Vietnam through the rural transport development program has built and repaired 345,897 km, 31,364 bridges, 125,639 sewers to increase the ratio of rural roads from 37.90% in 2010 to 68.69% in 2019. However, the mechanism of policies and management models still has many shortcomings, lack of democracy and explicit, limited management, management capacity has not met the requirements, discovering many mistakes, causing doubts in the community, leading to a complaint. By using directions quantitative and quantitative researches, the article assesses the current situation and analysis of four groups of factors affecting community participation management for developing rural infrastructure. The paper thereby proposes practical solutions and models for community participation management in developing rural transport infrastructure in the southeast provinces of Vietnam.

Predicting traffic flow through AI analysis has become popular in the development of traffic control; however, if the potential behaviors of road users, such as adjusting their departure times after being provided with forecast data, are overlooked, the effect of big data on traffic flow predictions is weakened. The third-party APP can provide an interface for road users that adjust departure times based on traffic conditions and provide feedback regarding adjustments. This study constructed a cusp catastrophe model of choice behavior with attitude, switching barriers, and behavioral intention as variables. Scenario simulation revealed that if the travel time forecasting of the app were 95% accurate and a highway toll waiver was offered, 44.1% of study participants would accept the new departure time recommended by the app.

We evaluated the impact of COVID-19 on bus ridership at the grid cell level using smart card data by categorizing ridership time-series in the following three steps; i) computation of dissimilarity indices between two grid cells based on dynamic time warping (DTW) and the difference in the daily average ridership, ii) grid cell mapping based on the dissimilarity indices using multidimensional scaling (MDS), and iii) grid cell classification using k-means clustering. One of the unique features of this study is the combined analysis of time-series trends in ridership, card type usage rates, and macro facility information by zone, which revealed that the decline in the ridership in the zones with visitor attraction facilities can be due to the not a large daily bus user, and that simultaneous school closures can lead to characteristic ridership patterns.

Road disruptions due to disasters can result in low accessibility or isolation of disaster sites. To solve this, we propose to utilize eVTOL (electric vertical take-off and landing) aircrafts to expand air transportation network for better and efficient humanitarian activities. Specifically, we propose to locate emergency ports for eVTOL strategically considering road network vulnerability. A mixed integer programming (MIP) model is formulated to select a suitable location of emergency ports for eVTOL considering road network disruption scenarios caused by disasters. The objective is to minimize the cost of transporting the relief goods and emergency personnel from the airports, that serve as emergency hubs, to disaster sites. Numerical examples with different road disruption scenarios are introduced to illustrate the reduction of travel cost by introducing the emergency ports for eVTOL aircrafts.

As a pre-disaster risk mitigation plan, evacuation planners allocate specific locations as disaster evacuation shelters. However, existing studies reported the presence of a diverse evacuation choice behavior among individuals rather than evacuating to evacuation shelters. Moreover, the conjunction of a natural disaster with a highly infectious disease such as COVID-19 questions the capacity of evacuation shelters and changes the psychological behavior of evacuees including evacuation destination choice. To this end, as a result of this paper`s literature review, an evacuation choice behavior model is developed based on a stated preference survey, applied to a city to predict the evacuation decision of individuals under compound risk of flood or earthquake disaster amid the COVID-19 pandemic. This paper is aimed to fill the research gap and help evacuation planners by developing an evacuation choice model to distribute facilities and services during a natural disaster based on the new estimated demand.

The number of visitors is a key performance indicator for quantifying the liveliness of tourist attractions. In this study, we analyzed the difference between the data obtained from Wi-Fi packet sensors and the actual number of visitors based on observation. Furthermore, we investigated the data cleaning method using the signal strength. Sensitivity analysis was conducted to set the threshold of the signal strength to clean the data according to the environment in which the sensors were installed. We then performed a regression analysis of the number of visitors using a Wi-Fi packet sensor. The results showed that the accuracy of the estimation is sufficient for monitoring the increase or decrease in the number of visitors throughout the year.

The urban theorist Jane Jacobs's four conditions for “exuberant diversity” in The Death and Life of Great American Cities are more fundamental to the success of downtowns than objective walkability, which is the facilitation of convenient walking by measurable characteristics of the built environment. Because “walkability” as a concept is ambiguous in the literature, Jacobs's “exuberant diversity,” or lively and varied street life, allows a clearer understanding of why downtowns succeed or fail. This is important for cities of the Global South, where streets may be exuberant but fail to meet Global North standards of objective walkability. Baguio City in the Philippines is used as a case study. Key findings are the importance of forms such as the zakkyo building, which are multi-story buildings that permit commercial uses on all levels, and micro-entrepreneurship in creating street-level vitality. Walkability is reframed as also emergent and not only top-down or planned.

In the COVID-19 era, many universities quickly adopted digital learning to overcome the health-related issues with physical Face to Face teaching, yet this switch presented challenges with achieving learning outcomes and ensuring teaching quality. The field of Transportation was heavily affected by these challenges. This paper explores students’ opinions of one online learning platform - TronClass platform - at the National Taiwan Ocean University in Taiwan. Research samples were undergraduate students who enrolled in the Transportation Planning course from September 2021 to January 2022. The questionnaire included 27 items with a five-point Likert scale and 40 valid questionnaires were collected. The Importance-Performance Analysis with four quadrants was used to analyse these 27 items. The results found that “Speed of response” and “Login identity verification” belong to Quadrant II and thus were considered very important but had a low satisfaction rating. Teaching improvement strategies are discussed based on the research findings.

The COVID-19 pandemic has accelerated changes in work styles, particularly leading to an increase in teleworking. This increase has the potential to affect transportation and urban development. In Japan, as telework is gaining popularity with more companies implementing telework systems, the choice of workplaces has become diverse. This study investigates factors influencing workers’ time allocation among different workplaces, such as offices, satellite offices, and homes. A time allocation model is applied to the data collected by the web-based survey, which includes social demographics, evaluation of the work environment, and psychological factors related to work-life balance. The estimation results indicate that socio-demographic attributes, job type, work characteristics, work efficiency, work-life interruption, recreation intention, and work environment satisfaction significantly affect the time allocation among different workplaces.

The sustainability of national transport systems rests to a large degree on public transportation. Although both supply and demand sides of public transportation are analyzed as part of ongoing performance monitoring, little information is available on the routine of using public transport in rural areas to assess customers’ loyalty. In this study, analysis of usage, trip rate, survival profiles, and other travel demand characteristics of public ridership in Kochi city is carried out through smart card data (SCD) gathered over a ten-year period. The findings in relation to the stability of individual customer behavior generate insights for planners and operators in the public transport sector in relation to assessing the mobility variability and better preparing their operation plans. Moreover, a public transport prediction model is developed based on SCD, which, when connected to a transport network, offers useful insights to operators in regard to the potential impact of small changes.

Utilizing historical national social network data and transportation network data, the researchers approximated the travel deterrence pertaining to social interactions, which can contribute to modeling historical transportation accessibility. The researchers first reconstructed the transportation network of ancient China, also delineating the social networks for three distinct periods (763-863, 1052-1152, 1472-1572) symbolizing three pivotal dynasties in Chinese history: Tang, Song, and Ming dynasties. A gravity model was proposed to articulate the social nexus between two cities, and an accessibility model was developed to represent the degree of a city's social integration. Within the framework of the gravity model, travel time deterrence exerted its relatively constant influence throughout the epoch of ancient history, underscoring the potential of transportation infrastructure to induce and perpetuate long-established social network configurations. The accessibility model sheds light on the prevailing societal acceptance for extended travel during different periods, a factor that would invariably influence political and economic architectures.

Abstract: The government emergency radio system is being developed and operated by the local authority for information sharing on disaster prevention, emergency rescue, and disaster recovery in local areas. In recent years, the quasi-zenith satellite system (QZSS) has been introduced to provide this information. This process is expected to be improved using drones with QZSS Receivers, and smartphones.

This study analyzes the behavior of the residents and local authorities in past disasters and the characteristics of the region, propose a solution for the lack of information sharing by utilized QZSS, drones and smartphones. Moreover, it also proposes the most efficient method of gathering information about the conditions of disaster victims using techniques such as drones approaching the vicinity of disaster victims with smartphones.

In recent years, image analysis methods using AI have been introduced to measure automobile traffic volume, and automatic observation systems have been constructed. On the other hand, the measurement accuracy of bicycles and pedestrians is still low, and expectations are growing for the development of traffic measurement AI that can obtain not only traffic volume but also movement speed and movement trajectory. In this study, we aim to develop traffic measurement AI that can estimate the traffic volume and movement speed of bicycles and pedestrians. Specifically, we trained a convolutional neural network (CNN) using new training labels, and it became possible to measure traffic volume and estimate speed using information obtained from object tracking. In addition, by visualizing the obtained movement speed and trajectory and combining it with TTC, which indicates the danger of collision between objects, it became possible to analyze and discuss each traffic mode in detail.

Long-tailed Remorks, minibuses, and trucks are dominantly used, as commuting modes, among factory workers. These modes are usually old, ill-equipped, and overloaded, with poor maintenance--and thus, unsafe vehicle for passenger transport. This study explored the operational characteristics of commuting modes for factory workers in Phnom Penh, Cambodia. The operational characteristics were investigated via data collected from interview survey (n = 58) and GPS survey (n = 22) with drivers of long-tailed Remorks, minibuses, and trucks, 17th-25th August 2022. It was found that long-tail Remorks (capacity of 20-45) are operated in suburb area, with average travel distance of 25.5 km. Minibuses (capacity of 50-60) and trucks (capacity of 40-70) are operated from suburb area and nearby provinces, with the average distance of 48.8 km and 76.0 km, respectively. The fact findings serve as good inputs into policy dialogues of stakeholders to improve overall workers’ commuting condition in Cambodia.

The present work reports an investigation on the speed characteristics of vehicles on a typical Indian Highways. Speed of vehicle is influenced by several factors like roadway features, vehicle types, mixed traffic condition, lane behavior and presence of vulnerable road users due to proximity of roadside built-up areas. A spot speed survey was carried out on several identified segments, which indicated that there were violations in speed from the posted speed limits. The level of adherence was found to be the least for cars, followed by LCVs and trucks. The violations are maximum at school zones, and minimum at market areas. The effectiveness of different speed control treatments was evaluated by introducing a parameter termed as ‘Measure of Effectiveness’, considering operating speed, measured speed and posted speed limit. Based on the measure of effectiveness of different speed control treatments, recommendations were made for creating safe speed environments along the highways.

This study proposes a weighted rounded departure time (wRDT) index to measure the quality of travel surveys. This index is an extension of Whipple’s index, used in demographic studies to measure age heaping. A comparison was made between the quality of 23 travel surveys conducted by Japan International Cooperation Agency in developing countries using the proposed index, and the differences in the rounding in the reported trip departure times were analyzed. The result yielded three findings. First, age heaping in the travel surveys was higher than that in the census in most cities. Second, rounding departure time to 15 min steps was fewer in East Asian cities. Finally, age heaping and departure time rounding to 60 min were higher in South Asian and African cities. Furthermore, a comparison of wRDT indices between both genders indicated a difference in rounding: female respondents were less likely to round their responses than males.

Transportation sustainability is critical in Asia, given the region's population and economic growth. This research paper investigates the relationship between population and fuel consumption in Asia's ten most populous countries. Using the Granger Causality test, this study examines if a country's population significantly predicts fuel consumption. The findings suggest that no significant relationship exists between the population and fuel consumption, indicating that population growth does not necessarily lead to increased fuel consumption. These results have important implications for policymakers and researchers seeking to understand the factors driving fuel consumption in Asia. To improve transportation sustainability in these countries, there is a need for policies and strategies that focus on reducing transportation emissions and improving energy efficiency. Therefore, there is a need for an integrated approach that considers the development of sustainable transportation systems. This study can inform policymakers and stakeholders in developing sustainable transportation systems.

For identification of polluting vehicles, a pre-screening model is developed by application of ID3 algorithm. A database of around 500,000 vehicles, which were screened over one-year period in Kolkata Metropolitan Area (KMA), India, is used for this purpose. The findings indicate the need for a relook at the existing policy of removing polluting vehicle fleets based on only age, and justify the need for considering other vehicle features such as vehicle class, emission norms, fuel type, etc. for identification of polluting vehicles. The findings also justify the need for priority attention on commercial vehicles which are found to have higher polluting rates compared to other vehicles. Overall, the findings from the present work can be readily used by transportation professionals in KMA. The approach demonstrated is likely to be of interest to professionals in other countries for screening of polluting vehicles within an existing vehicle fleet.

In snowy regions, the effective width changes due to the accumulated snow on the road shoulders during snow removal. For efficient snow removal planning, evaluating the effect of such changes in road conditions on traffic flow is necessary. Traffic capacity, which is one of the main measures of road performance, can be estimated by a macroscopic traffic flow model. Since drivers' perception of the accumulated snow varies widely, the parameters of the macroscopic traffic flow model can be considered uncertain. This study proposes an estimation method for stochastic parameters on macroscopic traffic flow model and stochastic road capacity for different width of accumulated snow by using a hierarchical bayesian model.

In order to mitigate the risk of spreading COVID-19, commuters have since prioritized trips and carefully considered transport mode. This research aims to identify the change in trip and transport mode importance before and during the COVID-19 pandemic in Metro Manila, Philippines. Data collected from an online questionnaire survey is used in a multinomial logit model in order to find the importance of each trip and transport mode. Then, the model parameters were calibrated by maximizing the likelihood function. Results showed that trips to work increased in importance during COVID-19. Such results highlight the necessity of traveling for work in order to generate income to support basic needs, specially during a pandemic when global economies are uncertain. Moreover, the use of both public and private transport modes also increased in importance. These results further emphasize the importance of transportation in order to support and continue economic activities during a pandemic.

As part of mobility transitions toward a more sustainable, smart, and resilient transportation, there has been a growing literature on ride-hailing services. These literatures tend to focus on the users, while little is understood regarding the drivers, particularly female ride-hailing drivers. Ride-hailing driver is often portrayed as a male-dominated occupation and female ride-hailing drivers are met with constraining stereotypes (e.g., less able to drive, easy to panic) and higher perception of risk (i.e., risk of harassment, street crime). This research explores the many narratives concerning female ride-hailing drivers drawing from a focus group with ride-hailing drivers, followed by a structured global literature review on female ride-hailing drivers, and contextualized with studies in Indonesian context. Findings identified spatiotemporal constraints experienced by female ride-hailing drivers, indicating a gendered mobility. This research concludes with future research direction and policy insights to address gendered mobility in the rise of ride-hailing services in Southeast Asia.

In recent years, traffic measurements using general object detection AI have been used in various scenes. In Japan, there is a movement to always use CCTV cameras installed on major roads to constantly observe traffic. In general, the traffic volume measurement AI uses a cross-sectional traffic volume measurement using the line separation judgment algorithm, but the criteria and judgment basis for setting this Count-line is not clearly shown. In this study, a comparative verification is performed using a Kernel Density Estimation to set up an appropriate Count-line and manually setting. As a result, changing the position of the Count-line resulted in a maximum difference of 95.7% in measurement accuracy.

Recent concern has grown over the escalating frequency and intensity of natural disasters due to climate change, with significant impacts on railways. This study evaluates the current and future flood risk of Japanese railroads, employing hazard, exposure, and vulnerability indices. Findings suggest a slight increase in flood risk by the end of the twenty-first century in a sustainable scenario and a substantial increase in a fossil fuel-dependent scenario compared to the end of the twentieth century. These results emphasize the need for proactive measures to mitigate flood damage and enhance railway resilience in Japan's transportation network amid climate change.

In this study, we examined the possibility that the spread of coronavirus disease 2019 (COVID-19) affected the use of public transportation among regions within a country, and among countries. The analysis included three to six regions in each of five countries; urban and rural areas were compared. The results indicated that public transportation use was affected not only by the local infection rate, but also by changes in the number of infected people in other regions within a given country having significantly higher infection rates. The United Kingdom and Japan had the highest numbers of affected areas among the countries analyzed. Overall, our results showed that the spread of COVID-19 has had both local and more far-reaching effects on public transportation use.

The transportation system is a critical infrastructure with profound impacts on the economy and social well-being. Therefore, understanding and enhancing transportation system resilience in the face of disruptions is of utmost importance. This study presents a framework that utilizes critical-link attacks to disrupt transportation network segments, evaluating their resilience. By utilizing network topological parameters as proxies, the framework holistically captures the network's resilience, considering all potential individual road segment disruptions. In contrast to conventional studies focusing on pre-hazard occurrences, this framework incorporates worst-case scenarios, encompassing all potential individual disruptions. Statistical and spatial analysis techniques are employed to assess transportation network resilience in both macro and micro events, employing topological parameters to evaluate network changes under varying levels of disruption. The results demonstrate the effectiveness of topological parameters in capturing transportation system resilience, enabling the identification of critical road segments from structural and network perspectives. These findings contribute to evaluating network performance and ensuring optimal transportation serviceability.

In this study, we estimated the impact of expressway connectivity on economic growth in Vietnam. We developed a novel distance-weighed harmonic centrality and used it along with the conventional degree and harmonic centralities as the indicators of expressway connectivity. Furthermore, we considered one of the following as the outcome for economic growth: population, in-/out-migration rate, registered foreign direct investment (FDI) capital, number of FDI projects, or the number of passengers on the road (“road passenger numbers”). A conventional two-way fixed-effects model was used to estimate the impacts. The results show that improved expressway connectivity is positively associated with higher in-migration rates, FDI capital and projects, and road passenger numbers.

Sri Lanka Railways (SLR) provides wide-ranging socio-economic benefits to the country while ensuring accessibility and mobility needs of passengers and goods shippers. SLR has been facing a financial shortfall since the early 1940s and needs strategies to mitigate this, which will reduce the burden on the government treasury and economy. The objective of this study is to ascertain the crucial factors of the long-term financial shortfall of SLR and the possible reforms by analyzing the expert opinions in rail transportation. This study adopted a qualitative research methodology, leveraging primary data and conducting an expert opinion survey to identify crucial factors and propose potential reforms. The findings revealed a range of internal and external factors, as well as diverse institutional-level and policy-level reforms to address the financial shortfall. These findings offer valuable insights for transport policy decision-makers, enabling them to implement appropriate reforms that effectively reduce the revenue-expenditure gap for SLR.

This study analyzed the potential of voluntary travel behavior change programs by focusing the secondary school students in Penang Island. The students were divided into four groups: control group (G1), planning group (G2), incentive group (G3), and planning with incentive group (G4). They were asked to fill in two series of travel diaries for 7 days. T-test analyses show significant difference for CO₂ reduction on weekdays, with the sequence by group: G1<G2<G3<G4. On weekends, the CO₂ emission reductions for all groups were significantly different except for G2. The multiple regression analyses show that the high reduction of CO₂ emission on weekdays was influenced by types of voluntary programs, gender, family income and parental escort. It was concluded that the groups that successfully reduced its CO₂ emissions did so not only as a result of the multi-intervention in voluntary behavior change program but also possibly because of sociodemographic factors.

Existing empirical evidence points to an inverse U-shaped relationship between motorcycle ownership and per capita income. Motorists tended to select cheaper modes of transportation, such as motorcycles and mopeds under low purchasing power, which promote a greater motorcycle to private car ownership. Contrarily, urbanisation induced long distance travel and this possibly induces a rise in car ownership at a particular level of per capita income. This study assessed the effect of the consumer price index, as the proxy of purchasing power, urbanisation, road density and per capita income on motorcycle to private car ownership. The panel data analysis is applied over the period of 1963-2013 for 76 countries. The main finding of this study indicates that purchasing power, urbanisation and road density played important role on national private vehicle ownership in a country. Policy implications were discussed in the conclusion part of the study.

Gender is a cross-cutting issue in distributive justice in transport. However, the gender gap in public transport awareness related to the different needs and constraints of daily travel between men and women in emerging and developing cities is not often highlighted. This study aims to scrutinize gendered mobility through a case study of the Jakarta Metropolitan Area (Jabodetabek), Indonesia. To that end, this research examined social constraints and transport choices using the results of an interview survey on public transport. Public transport awareness from individual travel experiences using public transport was also statistically examined from the viewpoint of gendered mobility. Finally, this study suggests public transport-related policies to alleviate gendered mobility and enhance transport inclusiveness in such cities in the long term.

By using the Data Envelopment Analysis (DEA) Malmquist Productivity Index (MPI), this study measures the efficiency of 33 State Transport Undertakings (STUs) in India, considering the year 2010-16. An output-oriented approach is used with output variables as Effective kilometres and input variables as Fleet Size, Total staff, and fuel consumption. The study attempts to provide an overview of the general status of STUs in India regarding their productive efficiencies in terms of years, firm-wise performance, and organisation-wise performance. The research has policy and managerial implications, with the study’s limitations also discussed.

A trade-off analysis between setting appropriate fares and attracting enough users is very important to ensure profitability for a sustainable public transportation system. The objective of this study is to estimate the elasticity of public transport users in Hanoi due to changes in fares and services. The estimated elasticities were then compared and analyzed with previous fare elasticity studies Manila and Jakarta. The analysis results show that users were inelastic in their demand for fare increases in Hanoi, although the elasticity was higher than in previous surveys in Manila and Jakarta. These findings suggest that Hanoi can raise the fare level of the railway and increase fare revenue without reducing the number of users. In addition, further development of the rail system and better improvement of accessibility to the station could significantly reduce price elasticity and lead to an increase in fare revenue without reducing ridership, even if fares are increased.

Previous studies had assessed the direct effect of income per capita and income inequality on the growth of motorcycle to car ownership ratio (MTC). This study quantified the overall growth pattern of MTC by also including the indirect effect measured as the influence of income inequality on MTC as the level of income per capita changes. The overall effect of income per capita on MTC was taken as the summation of both the direct and indirect effects. Two fixed-effects panel linear regression models were developed to estimate these relationships. The overall MTC growth pattern was found to closely follow the Kuznets inverse-U curve of the direct effect with the same income per capita turning point but with greater differences at the lower and higher ends of income level. These findings showed that MTC increases and decreases at higher rates compared to earlier findings after considering the effect of income inequality.

Universities attract a significant number of trips. Though the university studied in this paper, the University of the Philippines Diliman, has a high public transport mode share, the volume of private cars used by its stakeholders is still significant as seen in the recent return to campus experiences after the pandemic. Hence, this study aimed to understand the significant factors that affect the mode choice of university stakeholders, and to test the implications of changes to these factors using multinomial logistic modeling. Policies that target these changes are also discussed based on experiences of other universities. It was found that car availability for use is the most significant factor considered by the stakeholders. Distance from the university is also seen as significant to shift from private to active modes. Hence, it is recommended that policies targeting these factors specifically be implemented in this university in an effort to reduce car-usage.

Transit-Oriented Development (TOD) is a novel concept in India, wherein the national TOD policy was released in May 2017. This study analyzes factors that would influence users’ choice of living in a TOD, and subsequently their mode choice behavior while residing in a TOD. A binomial choice model assessed users’ location choice, and subsequently a multinomial logit model estimated their modal preferences. Survey samples were collected around the Esplanade (existing) and New Town metro rail stations (future) of Kolkata. Results show that proximity to workplaces, transit accessibility and affordability are likely to significantly influence users’ TOD choice. Subsequently, the factors of travel time, waiting time, and crowding are likely to affect users' mode choice. Individuals willing to relocate to TOD exhibit a greater inclination towards using public transport. However, results also show higher propensity of car usage among younger and wealthier individuals, which have to be disincentivized within a TOD.

In the Philippines, discussions on making public transportation more accessible usually focus on the needs of persons with disabilities. We further expand this by considering “Passengers with Reduced Mobility” (PRMs) who also include those with travel limitations and other contextual factors. Through an online survey, the needs and satisfaction of road-based public transport users were solicited at various stages of the journey cycle (i.e. from planning until arrival at the destination terminal). The results showed that most PRMs only used public transport on an as-need basis. PRMs also expressed higher demand for information for trip planning purposes as well as assistive services in terminals and vehicles. Overall, PRMs expressed lower satisfaction with their public transportation experiences over non-PRMs. The results of the study can be used to inform short to long term accessibility plans, with the end goal of achieving a truly accessible road-based public transport system.

This research explored the impacts of COVID-19 on travel behaviour by gender in public in the pandemic world, the current state of personal safety in general, and sexual harassment on public transport over the last three years, and recommended public policies to encourage residents to use more buses. An online questionnaire investigated 311 respondents’ demographic characteristics, feelings of safety, experience with sexual harassment, and reactions to acts of sexual harassment in public transport. The results showed that females and LGBT people were facing sexual harassment when heading to the bus stations, waiting at the bus stations, and using buses, especially after dark before COVID-19; COVID-19 changed respondents’ travel. A gender safety audit was a recommendation to include LGBT and females in all phases of public transport system development, aiming for a safer public transport system for females and LGBT and satisfying all users’ needs.

This study aims to identify a methodology that would more realistically represent the Electric Vehicle (EV) adoption and usage characteristics of the individuals, especially in India. The study also explores the effect of travel-related factors, direct experience, conventional vehicle-related factors, EV-related factors, and battery-swappability etc. on EV adoption. For this, a thorough review of important factors affecting the adoption of EV and the various methods adopted to analyze the data in the previous studies from past 10 years was done. A latent class based dynamic discrete choice modelling was proposed and the model will take into account both the dynamics of product attributes and the heterogeneity in population. The model will yield reliable outcomes that would help the decision-makers to formulate efficient strategies for successful EV market. The proposed methodology can be used to model the adoption of any other AFVs after making specific changes to the technology being focused.

Urban morphology studies define how settlements are formed to support human activities. Population, urban activity, and land use can influence transportation choices, such as decreased public transit availability in high-density locations due to increased expenses. The research gap between urban morphology and transport preferences leading to issues in Indian cities is yet to be addressed in depth. Currently, the focus lies in providing improved public transportation services and limited attention is being paid towards analyzing existing urban forms and their influence on changing travel behaviours. Therefore, through a primary survey, this study attempts to link this gap in an eco-sensitive region of South 24 Parganas utilizing Structural Equation Model to regenerate the relationship in two pilot study areas of the region. The findings of this study suggest that urban morphology influences people's transportation preferences far more than demographic and socioeconomic factors due to the closeness of various activities and infrastructures.

Vientiane’s public transport (PT) modal share decreased by around 70% from 2007 to 2019, and due to COVID-19, only 8 city bus routes are operating in 2023 (50% decrease from 2019). Private modes are increasing since they are reliable and comfortable, but at the cost of traffic congestion and environmental degradation. Shifting to PT is needed to reverse this trend, however, the state bus operator Vientiane State Bus Enterprise (VCSBE) is unable to improve services without financial support. This paper studies the potential of mode shift of government officials from private modes to increase PT ridership in CBD using commuting allowance policies. Statistical analysis was used to study modal choice factors of government officials. Additionally, multinomial logit regression model was used to identify commuting allowance policy preference based on sociodemographic and PT service characteristics. The model revealed specific service improvements and policy preferences to improve PT service in Vientiane.

Transport in the cities of Vietnam in general and in Hai Phong city in particular is changing rapidly due to economic growth, urbanization and motorization, problems such as traffic congestion, traffic accidents, air pollution and difficulty in accessing city services. In the development plan of the city, the residential, educational, industrial and service industry functions of the city will be distributed and gradually moved from central area to the satellite towns. However, the development of these new satellite towns has not necessarily been proceeding smoothly. One of the causes for the late development of the satellite towns is the poor public transport network and lacking connect the satellite towns with the central area. In addition, recent studies showed that public transport with only bus system is not adequately attented during operation process. The curent bus system only meets less 2% of the city's travel needs. The city needs to develop an advanced public transport system that is enough attractive and environmentally friendly to attract people to use. At the same time, contribute to reducing traffic jams and traffic accidents and in doing so promote metropolitan regions.

The paper presents an analysis of current public transportation situations in Vietnam, and to focus on the case study in Haiphong city. Then, the study presents opportunities, challenges and how to develop of A Bus Rapid Transit System (BRT) for Haiphong city and for the cities of Vietnam in general.

In 2008, the usage-based insurance (UBI), that insurance premium was calculated based on driving behavior data recorded with a plug-in telematics device or a mobile APP on board was introduced. Between years 2016 and 2019, 8 insurance companies providing UBI insurance policies were on Taiwanese market. However, this innovated insurance policy was not successful. The possible reason might be the insurance premium were simply measured by distance traveled. This study is to understand customers’ attitude towards UBI insurance policy and find out appropriate UBI pricing factors. A total of 580 valid samples were obtained. This study found respondents are not familiar with UBI car insurance. The factors of hand-hold mobile phone usage, speeding, sudden lane-changing, and following distance are more acceptable to the public. To campaign UBI policy, we suggest providing customers on-board telemetric in their own cars. It will help to increasing the public’s acceptance of UBI insurance policy.

Most studies advocate that to reduce reliance on private cars, alternative forms of mode should be made attractive. This study aims to explore the factors and consideration of parents that influence their willingness to shift away from private cars for their child’s trip to school. A total of 109 parents in Metro Manila have participated in the survey, and using logistics regression, the sex of the child, distance of house to school, and quality of public transport vehicles were found to be the significant factors. When the Covid-19 pandemic happened, more parents became unwilling to use the public transport. Findings indicate that improvement in the quality of public transport may be the most effective strategy in inducing mobility behavior towards sustainable transport. Further, school siting and implementation of a School Bus Program should be an extensive collaboration between parents, school officials, and the government.

Variable message signs are expected to minimize congestion by assisting drivers in making better routing decisions. In addition to filling the literature gap while considering the rapid growth of motorcycles, this study aims to investigate the primary attributes that affect the route-switching behavior of motorcycle riders. A stated preference experiment was performed to capture the en-route route choice in response to traffic information. The estimated parameters were accomplished by a binary logit model with respect to the two choices: stay or switch. The results revealed that riders prefer to deviate when the alternative route offers shorter distances, wider roads, less traffic, and lower travel times. Individual characteristics, including age, occupation, education, and habit of observing traffic information sources, significantly impacted. When route guidance was provided, riders had a strong propensity for route switching, leading to the research implication of distributing traffic flow to establish more balanced networks.

‘Traffic peak hour’ is an arguably unclear yet widely used concept in urban transport studies. It is common to see the term ‘peak hour’ used interchangeably with ‘peak period’. However a clear definition is necessary to undertake quantitative and analytical assessments. Spatial variation in peak hour across larger size study areas adds to the complexity. This study considers the spatial distribution of traffic peak hours across the Adelaide metropolitan area which leads to deriving the nominal traffic peak hours. A simplified version of a methodology commonly used in travel demand models to determine peak hour volumes is replicated in this study. Comparisons are made between observed and estimated values. These comparisons coupled with the definition of nominal peak hour are used to reinforce the argument for the need for future forecast demand adjustment. Observed site-specific peak hour volumes are recommended to inform such adjustments in forecast traffic volumes.

Traffic flow data is one of the essential traffic parameters to quantify traffic loadings and characteristics for illustrating road congestion. A conventional method of collecting road traffic information mainly relies on traffic sensors. Because it is impossible to carry out the full-scale deploy traffic sensors within budget constraints. Under the issue of the limited number of traffic sensors, determining the appropriate deployment logic of traffic sensors to find suitable deployed locations is the purpose of this study. According to the spatial relationship in a transportation network, this research will build up the traffic sensor deployment model and the corresponding algorithm based on the concept of graph theory. The framework this research proposed can simplify the complex mathematical models and use a simple manner to figure out the suitable deployment strategy for collecting the full-scale vehicular flow information in a transportation network.

In metropolitan areas, transit networks have been extending and becoming increasingly complex, thus enabling more route choices. Apart from fare and travel time, interchange and crowding conditions also affect route choice behaviour. This paper reviewed factors influencing route choice, focusing on interchange and crowding effects. A stated preference (SP) technique was used to develop transit route choice models, based on standard logit and random parameters logit (RPL) models. The study found that these values are rather high, compared to the value of in-vehicle travel time. Therefore, it is crucial to ensure that interchange facilities are comfortable and sufficient for passengers. Additionally, the effects of interchange and crowding should be coordinated with demand forecasting models. Although, the absolute values for Bangkok cannot be directly compared to the values found in developed countries, the relative values (multiplier of in-vehicle time) are comparable and would be transferable to other cities and countries.

Transportation is an indispensable factor on the successful hosting of the Olympic games. Comprehensive traffic management measures are essential to alleviate the traffic congestion during the Olympic games. In this paper, we studied the effects of the Traffic System Management (TSM) of the Tokyo 2020 Olympic games on the Tokyo Metropolitan Expressways (MEX). We further proposed a methodology to estimate the effects of TSM and Traffic Demand Management (TDM) separately based on the empirical data, and applied the methodology on a specific route as a case study. The results for the case study suggested that TSM was efficient for reducing onramp traffic demands, which will further contribute to the total delay reductions at merging bottlenecks. We found that on several days TSM was excessively implemented, and TSM worked more efficiently during the latter part of Olympic games.