Car Users Research Articles

High-Profile Convoy Disruptions: Exploring Socioeconomic and Environmental Ramifications of Road Closures

Congestion persists despite various demand management techniques, particularly for handling recurrent congestion. However, non-recurrent congestion from events like VIP movements poses unique challenges, especially during peak hours. This study investigates the environmental and economic impacts of road blockages due to VIP movements in developing countries, focusing on Pakistan. Considering practiced standard operating procedures associated with VIP movements, this study finds significant delays and economic burdens in debt-ridden economies. It uses discrete choice modeling and microsimulation techniques to evaluate the value of travel time and quantifies road blockage effects on fuel consumption, travel time, and carbon emissions. Data from central blockage locations in Rawalpindi and Islamabad reveal a value of travel time estimated at 1.77 USD/h, with income and gender significantly influencing mode choices during VIP movements. Moreover, road blockages exceeding two minutes substantially negatively impact the environment and economy, particularly in developing nations. Urgent action is needed for effective mitigation strategies and sustainable transportation policies to address the detrimental effects and promote alternative transportation modes. Recommendations include limiting VIP blockages to a maximum of two minutes and implementing policies to discourage private car usage. Despite limitations, the study emphasizes the critical role of sustainable transportation policies in enhancing the well-being of road users in developing nations.

Real-time V2G simulator for grid system frequency and voltage regulation with fault ride-through capabilities

Electric vehicles (EVs) have become one of the promising power grid ancillary services. They can help reduce the intermittent of renewable energy sources by supporting active power and frequency control services. Additionally, bi-directional chargers included into EV batteries can supply/consume reactive power for voltage regulation. To improve voltage quality, a unique control approach is devised to offer fault ride-through. In this study, real-time charging optimization schemes based on particle swarm optimization are developed to coordinate the EVs charging/discharging power with the grid power dispatches depending on the charging priority and preferential electricity prices. Five different car user profiles including different initial state of charge and plug in state have been depicted. Different optimum issues are carried out with comprehensive simulations employing hardware in the loop via real-time simulation for a modified IEEE 14-bus test system. Where different frequency and voltage controls, management strategies, variant fault scenarios, benefits, and challenges for power system regulation with EVs are illustrated. According to the simulation results, the proposed optimized charging strategies reduce the total expenses of EV parking station by 40 % compared to other cases, hence maximizing EV owner satisfaction. The net load curve is smoothed and reduced by 11 %, particularly during peak period.

Embracing Urban Micromobility: A Comparative Study of E-Scooter Adoption in Washington, D.C., Miami, and Los Angeles

E-scooters have emerged as a popular micromobility option for short trips, with many cities embracing shared e-scooters to enhance convenience for travelers and reduce reliance on automobiles. Despite their rising popularity, there is a lack of clear understanding of how user preferences and adoption practices vary by location. This study aims to explore user and non-user attitudes towards e-scooter use in diverse urban settings. A meta-analysis of data from three surveys (N = 1197) conducted in Washington, D.C., Miami, FL, and Los Angeles, CA, was performed to compare e-scooter users and non-user profiles, mode choice factors, and attitudes and preferences towards e-scooter use. Additionally, machine learning (ML) and SHAP (SHapley Additive exPlanations) analysis were utilized to identify influential factors in predicting e-scooter use in each city. The results reveal that the majority of e-scooter users are 25 to 39 of age, male, with higher income and a bachelor’s degree, and 92% possess a driver’s license. Significant differences in attitudes between e-scooter users and non-users highlight the complexity of perceptions towards e-scooter usage. The ML model indicates that employment status negatively impacts the prediction of e-scooter users, while factors such as living without a car and using non-motorized modes positively influence e-scooter use. Educational background is a significant e-scooter mode choice factor in Washington, D.C. and Miami, whereas attitudinal questions on car and technology usage are influential in Los Angeles. These findings provide valuable insights into the factors shaping e-scooter adoption, informing urban transportation planning and policymaking and enhancing understanding of shared micromobility and its impact on urban mobility.

Who's afraid of pedestrianisation? Residents' perceptions and preferences on street transformation

While urban pedestrianisation schemes typically attract vociferous opposition, it is often unclear whether these negative views are representative of the general population. For this reason, understanding how residents perceive the impacts of such schemes is critical to their evaluation. To this aim, this article assesses residents' perceptions and preferences regarding the pedestrianisation of multiple streets in the Eixample district of Barcelona in recent years, through a representative survey of the district's residents (n = 1211). Our research examines how residents' views on pedestrianisation vary depending on their mobility habits, sociodemographic background, and the level of traffic calming of the street they live on. Our results show that most respondents (66%) consider that the impacts of existing pedestrianisations have been positive regardless of whether they live on a pedestrianised street or not, even though residents of recently pedestrianised streets are more positive than those living on other streets. At the same time, many residents of pedestrianised streets consider that the benefits of reduced traffic externalities may be partially counterbalanced by new problems caused by an intensive use of public space (e.g. noise from people and cafes, touristification, nightlife). Our results also show that there is a strong relationship between support for pedestrianisation, age and mobility habits: daily car and motorbike users are much less supportive of pedestrianisation than public transport users and cyclists, while support for pedestrianisation decreases markedly with advancing age.

Characterizing clinical trials for CAR T targeting solid tumors from 2018 to 2023: A systematic review.

e15080 Background: In the last decade, there have been many advances in the treatment of solid tumors, including new chemotherapy agents, immunotherapy, and most recently, cellular therapies. Chimeric antigen receptor T-cell (CAR T) therapy, first approved for acute lymphoblastic leukemia in 2017, represented a paradigm shift in hematologic malignancies, producing response rates that dramatically outpaced alternative regimens in a relapsed/refractory patient setting. Approvals in large B-cell lymphomas and multiple myeloma followed. Excited by the potential of CAR T, investigators worldwide have initiated trials to investigate the use of CAR T in solid tumors. This review explores the trials conducted globally, evaluating the potential molecular targets and the status of current clinical trials. Methods: This systematic review identified CAR T clinical trials specifically targeting solid tumors starting in 2018 to 2023 registered at ClinicalTrials.gov as of January 8, 2024. Trial-related variables including trial phase, primary trial site location, primary endpoints, start and end dates, and molecular target were captured. Results: We screened 110 clinical trials, ultimately including 103 studies for analysis after excluding trials without a CAR T construct in the methods. The number of new clinical trials increased over time, with a significantly larger increase (440%) seen with non-US sponsors compared to US sponsors (100%), p< 0.0001. Only 19 trials (18%) are/were being conducted in the United States in the studied time period. There were 33 unique molecular targets used, with mesothelin (17%), and the claudin protein family (13%) as the most frequented targets. Conclusions: The success that CAR T has demonstrated in hematologic malignancies has created great hope in solid tumor malignancies, although tempered by differences between the two categories. Unlike hematologic cancers, solid tumors exhibit significant biomarker variation, with interpatient biomarker expression varying greatly, even within the same tissue diagnosis. To deal with this issue, the majority of clinical trials that were reviewed here were not restricted to a single disease location such as breast cancer or esophageal cancer but were rather restricted by the expression of the targeted epitope, to allow for the heterogeneity inherent in these tumors. As presented here, substantial efforts are being made worldwide to improve these technologies, but the United States appears to be lagging in clinical trial efforts, compared to other nations. Further investigation is warranted into this topic, as the usage of CAR T quickly spreads from a therapy only used in hematology to one with promise in solid tumors, infectious diseases, and beyond.

THE ENVIROMENTAL AND SOCIAL IMPACT OF CARPOOLING

Abstract: Car pooling System is an automated system which reduces the misery of travelers and makes them find cars in short period of time. Car pooling is an application of finding car in which drivers who are traveling to work alone can ask for fellow passengers through our application. For those who use public-transport system to go to work daily can use this application to find drivers who are traveling to the same destination in a short path. It provides with a simple riding platform between the car owner and car user. This project enables users to access mobility assets own by others exactly when they need. I t shows a medium for available cars to pick up them on the interest of car owner with time and capacity. This project aims at creation of a Car-pooling System. This paper delves into the design and implementation of a novel carpooling project aimed at addressing the challenges of urban transportation sustainability. With burgeoning urban populations, congestion, and environmental concerns, the need for innovative solutions is paramount. Carpooling presents a viable avenue to alleviate these issues by fostering shared mobility, reducing traffic congestion, and cutting down carbon emissions. The project employs a multi-faceted approach, leveraging advancements in mobile technology, data analytics, and user incentives to optimize the carpooling experience. Key components include a user-friendly mobile application for seamless ride matching, dynamic routing algorithms to optimize trip efficiency, and incentive structures to encourage participation and retention. Through a combination of quantitative analysis and qualitative feedback, the efficacy of the carpooling project is evaluated. Metrics such as reduction in vehicle miles traveled, greenhouse gas emissions, and user satisfaction levels are assessed to gauge its impact on urban transportation sustainability. The findings of this research contribute to the growing body of knowledge on sustainable transportation solutions and provide insights for policymakers, urban planners, and transportation stakeholders seeking to promote carpooling initiatives. Ultimately, the project aims to foster a culture of shared mobility and pave the way for more efficient and sustainable urban transportation systems. IndexTerms – HTML, CSS, Javascript. Bootsrap, MySQL, Python.

A method to assist designers in optimizing the exterior styling of vehicles based on key features

Aiming to assist the design and management personnel of automotive products to make correct judgments and give optimization solutions for the design of exterior styling, and to solve the defects of the traditional method which relies too much on experience and personal ability, a neural network-based key feature analysis and optimization method of styling is proposed. Firstly, the user attributes are analyzed and quantified, and the weighted optimization of user evaluation data is completed based on the multidimensional Gaussian distribution function to construct a more objective car styling evaluation dataset. Secondly, a particle swarm algorithm is proposed to optimize the prediction model of radial basis function neural network (PSO-RBFNN) which deeply analyzes the mapping relationship between different car perspectives and users’ perceptual preferences. The identification of styling components is completed with the annotation of feature points, and a parametric expression method of styling feature data with multi-viewpoint weight optimization is proposed. Third, the model interpretation is based on the embedded feature selection method to discover the key feature points affecting user perception, and the key common features of styling are obtained through the coupling relationship analysis of feature points. Finally, the optimal distribution range of key features is given based on statistical analysis, and the application process is shown by an example of optimization to verify the feasibility of the theory. Compared with the traditional methods, PSO-RBFNN has better prediction accuracy. Meanwhile, the modeling optimization method based on key features has the great advantages of objective accuracy and high efficiency compared with the traditional theory.

Agent-based decision-support model for bus route redesign in networks of small cities and towns: case study of Agder, Norway

Small cities and towns often struggle to provide high-quality public transport services to daily commuters. This is reflected in the modal split, where the share of car users dominates. Such a problem requires a modern solution, where transport planners can verify the impact of potential transport network improvements on the travel behavior of the residents before the changes are actually deployed. This study aims to demonstrate the usefulness of employing an agent-based simulation tool in the decision process for redesigning an express service regional bus route connecting a network of small cities and towns. The model was initially developed as a Mobility as a Service simulation solution for suburban areas of European metropolises. The model is adapted and applied to a case study for the region of Agder, Norway, simulating the impact of nine different scenarios on the patronage of a specific bus route. The simulation model proposes to upgrade the classic agent structure to a persona profile designed specifically for the case study. The main objective of this research is to identify the scenario that maximizes patronage while minimizing total route travel time and additional costs. The results suggest that the proposed model can be successfully adapted from suburban metropolitan areas to the realities of the considered case study, and potentially other similar regions. Specifically, out of the nine proposed scenarios, the model identified four promising ones. One of the four scenarios also fits the cost constraints imposed by the transport provider. The model provides a solid approach for analyzing complex transport systems that are practically impossible to consider in detail if the analysis is done without computer support. Thus, the results can be used as a decision support system for public transport planning and operations in networks of small cities and towns.

The effect of psychology factors and environmental concerns on mass rapid transit usage intention among private vehicle users in Klang Valley, Malaysia

Abstract Since its introduction in 2016, Malaysia has made improvements to the mass rapid transit (MRT) system; however, the current year’s usage figures are below expectations and do not meet target levels. Thus, the purpose of this study is to look at the elements that influence the behavioural intentions of private vehicle users to use the MRT in Malaysia. In this study, A total of 403 respondents who are private vehicle users from the Klang Valley were involved and the Pearson correlation test was used to investigate the relationship between the factors that potentially influence the behavioural intention to use MRT among private vehicle users. Next, the factors influencing private car users’ behavioral intention to utilize MRT were also investigated using the multiple linear regression method. The findings of Pearson’s correlation analysis show that all factors namely environmental concerns, perceived behavioural control, attitudes, subjective norms, and behavioural intention have a positive and significant relationship among those factors. Furthermore, the multiple linear regression model demonstrated that drivers of private vehicles are significantly influenced by attitude, subjective norms, and environmental concerns to switch to MRT as a mode of transportation.

Does abdominal protrusion in pregnant women affect abdominal injury severity in motor vehicle collisions? A nationwide database study.

Some pregnant women avoid vehicle driving owing to the risk of contact between their protruding abdomen and steering wheel. This study was performed to determine whether abdominal protrusion in late-term pregnant car users affects the occurrence and severity of abdominal injuries in motor vehicle collisions using a national crash database. The National Automotive Sampling System/Crashworthiness Data System was used to analyse maternal background, collision characteristics, outcome and Abbreviated Injury Scale (AIS) scores for the body regions of all persons involved in the collision. Comparison of pregnant and non-pregnant women in the driver's seat showed no significant differences in the rate of AIS scores of ≥2 (2+) for abdominal injuries and female outcomes. Comparison of use of the driver's seat and front passenger's seat by pregnant women showed no significant difference in rate of AIS 2+ injuries or in maternal and fetal outcomes. Comparison of pregnant women with a gestational age of ≤27 and >27 weeks in the driver's seat showed no significant differences in rate of AIS 2+ injuries or in maternal and fetal outcomes. Based on the data from relatively low-speed frontal collisions, obstetrician/gynaecologists should advise pregnant women that they do not need to change their preferred car seat from the driver's seat to another seat because of fear of contact between their protruding abdomen and the vehicle interior.

Investigating the Key Factors Affecting Public Transport Ridership in Developing Countries through Structural Equation Modeling

Every country requires efficient public transportation to reduce the reliance on motor vehicles, decrease harmful emissions and noise pollution, and, most importantly, provide accessible transportation for urban populations with limited resources. Yet, several challenges hinder the efficiency of the public transportation system, affecting factors like daily ridership, infrastructure, revenue, and operations. Therefore, this research investigated barriers and their impact on the daily ridership of rail transit services, especially in densely populated areas characterized by high automobile usage, inadequate pedestrian facilities, and limited connectivity to other transportation modes. To accomplish this goal, a self-administered questionnaire was developed, and a survey was conducted to collect responses from commuters at various public transport hubs. Structural equation modeling (SEM) was used to analyze data gathered from a sample of 1000 participants. The findings from the SEM model indicated a positive correlation between Instrumental Attractiveness (IA) and Facility Design and Operation (FDO) with daily travel. Conversely, Service and Information (SI) along with Environmental Comfort (EC) exhibited a negative correlation with daily travel. Private sector employees without personal vehicles and a monthly income below fifty thousand exhibited a strong preference for public transport. Individuals with higher incomes who owned vehicles showed lower preferences towards public transport usage. The main contributors to low ridership in public transport included poor connectivity with metro and feeder buses, lack of availability of discount tickets, insufficient seating at stations, and inadequate route map information. Gasoline prices have a notable impact on daily ridership too, as higher fuel prices tend to attract more travelers to use public transport. The ridership data demonstrate a positive trend in response to increased gasoline prices. The findings from this study are useful for transportation engineers, practitioners, planners, and policymakers.

EXPLORING USER-PRODUCT INTERACTION IN CAR MODIFICATION PRACTICES

This study delves into the dynamic interaction between the creative activity of car modification and the qualitative aspects of modified car ownership and usage. The study aims to explore experiences and meaning generated in and through the material reproduction of cars. Employing a grounded theory approach, the research investigates car modification communities in Istanbul, Turkey. The findings are structured into two main sections: The Driver, which focuses on car owners' experiences derived from in-depth qualitative interviews, and The Car, which explores the material aspects of cars through the analysis of modifications. The study revealed that car modification transcends mere material reproduction. Rather, it unveils a complex interplay where cars are shaped by their owners, while simultaneously shaping their owners in diverse ways. By altering the materiality of their cars, individuals not only forge material relationships but also cultivate new amalgamations of sensual and social relations and experiences. Through altering the materiality of their cars, car owners tailor the experience of driving and give a concrete form to their social and personal identities.

A Performance Analysis of a Two Way Stop Control (TWSC) Intersection under Mixed Traffic Conditions

Intersections are road traffic infrastructure on highways installed to help settle directional movement that could result in conflict while vehicular trips are made. Evaluation of the challenges faced by different automobile users at the Araromi junction (A three Leg at-grade Intersection) located in Akure is the main objective of this paper. To achieve this objective, traffic flow data were collected on the spot by video recording and then the data were manually counted. While, the highway Capacity manual 2010 methodology was adopted to analyse The entry flow rates, Potential Capacities, Movement Capacities, Movement Control Delay, Approach Intersection Control and 95th Percentile Quene Length of the intersection. Findings shows that an average entry flow rate of 357 pc/h occurs for all the legs of the intersection, the North bound left turning movement of the intersection was not within the allowable limit, the average potential capacity by lane for the intersection is 445 pc/h, and the average movement capacity by lane 473 Pc/h, the various legs of the intersection has a level of service of ‘A’ and ‘C’ except the left turning minor street movement that has an ‘F’ LOS. Due to the influence of high traffic flow around the intersection, the analysis of the real-time traffic flow results reveals the need to diverge the high right turning movement into other route to cater for low left turning movement causing delay and poor LOS and a need to introduce Signal on the intersection in other to improve on her functionality.

Spatiotemporal evolutions and reasons of land-use carbon emissions in counties, Shaanxi Province, China

Global warming caused by factors such as the expansion of construction land poses a major threat to the sustainable development of China. As an important component of China's low-carbon development strategy, there is a relative lack of analysis of the spatial and temporal evolution of land-use carbon emissions and the influencing factors at county-level. In this study, we employed Emission-Factor Approach to estimate carbon emissions from land use in 107 counties, Shaanxi province, China. Our findings revealed construction land were the primary contributors to carbon emissions, showing a substantial increase from 2000 to 2020. There was positive spatial autocorrelation in carbon emissions among counties, forming distinct aggregation patterns around the City of Xi'an and both the southern and northern regions of Shaanxi. By utilizing the Spatial Durbin Error Model (SDEM), demographic factors emerged as key drivers of carbon emissions, indicating the significance of addressing population concentration to curb emissions. Furthermore, promoting coordinated development and adjusting the economic structure in different counties can mitigate both population concentration and carbon emissions. Emphasizing industrial development and investments can also effectively suppress carbon emissions. Additionally, managing transportation-related emissions can be achieved by enhancing public transportation services and regulating private car usage.

Designing an optimal multi-energy system with fast charging and hydrogen refueling station under uncertainties

As the demand for battery-powered and hydrogen-based electric vehicles continues to rise, the need for integrated charging and refueling systems with energy systems becomes more critical. Therefore, it is crucial to consider the stations serving diverse vehicle users during the system design process. This paper presents an optimal sizing strategy for a multi-energy system that covers clean energy sources and two energy storage technologies under the presence of a fast-charging station and a hydrogen refueling station for various types of car users. For the considered system, the optimal sizing problem aims to minimize the loss of power supply probability (LPSP) and annualized total life cycle cost (TLCC) through a two-stage stochastic programming-based multi-objective optimization approach. Using a scenario-based approach, the study considers the uncertainties associated with renewables, homeowner’s vehicle demands, and energy demands from homes and stations. Different cases are produced to evaluate the impacts of the different stations with the availability of various electric vehicle profiles under different levels of reliability. The TLCC decreases if LPSP increases in each case. Also, the cost of installing a fast charging station is significantly lower than that of a hydrogen refueling station for all LPSP limits. Moreover, the overall cost of the system design is at its lowest when homeowners’ vehicles provide vehicle-to-grid services. It is worth noting that when the station loads which come from the customers’ vehicle increase by 10%, the TLCC increases by 1.19%. Additionally, the revenue from hydrogen refueling station is approximately 70% less than the fast charging station.

Automatic Vehicle Fueling System using PLC Controlled Robotic Arm - A Simulation Design.

The objective of this research is to simulate an automatic fuelling system using a PLC LogixPro simulation. The system includes the "FASS" concept, which is Fast, Accurate, Safe and Simple, to allow car users to have an efficient fuel filling system. The design concept consists of three processes - identification of the vehicle, payment, and filling with the fuel. The first process identifies the presence of the car by the in-floor weight sensors. The weight sensor identifies the car, locks it in position, and activates the payment system. The second process activates the payment system. After payment is completed, the fuel cap will be opened to enable the system to start filling the fuel. If the payment doesn't go through the car will be released, manual operation will be initialized, and the entire system will be reset. A timer is included in the payment section to process the payment. In the third process, the filling arm is extended to the car, the fuel cap is opened, the fuel pump is inserted into the tank, and fuel is directed into the tank. Once the tank is full, filling is stopped, the pump is ejected, the fuel cap is closed, and the arm returned back to its position. Thus, an automatic vehicle fuelling system is created to overcome the problems of poor safety and longer waiting time during peak hours. The fuel cap is activated and deactivated by pressure and the sensor filler is stopped by a level sensor. The pump insert is activated and deactivated by a photosensor.

A Price Too High: Injury and Assault among Delivery Gig Workers in New York City

The occupational health burden and mechanisms that link gig work to health are understudied. We described injury and assault prevalence among food delivery gig workers in New York City (NYC) and assessed the effect of job dependence on injury and assault through work-related mechanisms and across transportation modes (electric bike and moped versus car). Data were collected through a 2022 survey commissioned by the NYC Department of Consumer and Worker Protection among delivery gig workers between October and December 2021 in NYC. We used modified Poisson regression models to estimate the adjusted prevalence rate ratio associations between job dependence and injury and assault. Of 1650 respondents, 66.9% reported that food delivery gig work was their main or only job (i.e., fully dependent). About 21.9% and 20.8% of respondents reported being injured and assaulted, respectively. Injury and assault were more than twice as prevalent among two-wheeled drivers, in comparison to car users. Fully dependent respondents had a 1.61 (95% confidence interval (CI) 1.20, 2.16) and a 1.36 (95% CI 1.03, 1.80) times greater prevalence of injury and assault, respectively, than partially dependent respondents after adjusting for age, sex, race and ethnicity, language, employment length, transportation mode, and weekly work hours. These findings suggest that fully dependent food delivery gig workers, especially two-wheeled riders, are highly vulnerable to the negative consequences of working conditions under algorithmic management by the platforms. Improvements to food delivery gig worker health and safety are urgently needed, and company narratives surrounding worker autonomy and flexibility need to be revisited.

THE INFLUENCE OF SERVICE QUALITY AND COMPANY IMAGE ON CONSUMER SATISFACTION AT CARRO INDONESIA.ID HARAPAN INDAH BEKASI BRANCH

The era of progress and development has made four-wheeled vehicles, or cars, a basic necessity for the middle to upper-class society. This is evident from the increasing purchase of used cars every year. The number of car users continues to rise, resulting in various complex issues. One of the main issues is the worsening traffic congestion, leading to an increase in road accidents. The automotive service industry continues to evolve, providing adequate facilities. When these services are delivered effectively, they are used to enhance customer satisfaction. A quantitative approach is employed, and it has a cause-and-effect relationship design for the specific variables. The research findings are as follows: service quality has a positive and significant impact on customer satisfaction, with low significance (0.000 < 0.05). Similarly, the company image has a positive and significant effect on customer satisfaction, with low significance (0.004 < 0.05). Furthermore, there is a positive and significant simultaneous impact of the variables on customer satisfaction, as evidenced by the high F-value (191.345 > 3.136) and low significance level (0.000 > 0.05). In conclusion, the null hypothesis (H0) is rejected, and the alternative hypothesis (Ha) is accepted, indicating that service quality and company image significantly influence customer satisfaction. Keywords: Service Quality, Corporate Image, and Customer Satisfaction

Policy dialogue: Key factors for the success of transit-oriented development infrastructure 3.0 in big cities in Indonesia

This research aims to determine the factors driving the success of four large cities in Indonesia in implementing Transit-Oriented Development (TOD) infrastructure policies beyond the eight TOD 3.0 Principles. Only a few studies like this have been conducted. The research uses qualitative methods and is supported by in-depth interviews with stakeholders, community leaders, community groups, and service users. The research findings reveal six themes: policy dialogue, organizational structure and coordination, changes in community habits, resources, dissemination and communication, and transportation and connectivity services. The characteristics of the community in the study area that prioritize deliberation are important determinants in policy dialogue and are involved in determining policy formulation. The city government has established a comprehensive organizational and coordination structure for the village and sub-district levels. The Government controls infrastructure development activities, establishes a chain of command and coordination, and encourages people to change their private car usage habits. The city government combines all this with the principle of deliberation and conveys important information to the public. The research highlights the differences in TOD implementation in Indonesia compared to other countries. Specifically, the existence of policy dialogue and the direct involvement of community members influence the level of program policy formulation and are crucial in controlling urban infrastructure development.

Examining Congestion Pricing Scheme Effectiveness Using the Travel Time Congestion Index

This study investigated the effectiveness of congestion pricing (CP) using the travel time congestion index (TTCI), a congestion assessment tool, in Hyderabad, India. Initially, a set of hypothetical mode choice scenarios under the CP scheme were designed to collect car users’ perceptions based on a stated preference (SP) experiment. Based on the SP survey data, discrete travel behavior models were developed to estimate the probable modal trade-off among cars, two-wheelers, and public buses under the generated CP scenarios. Using the existing traffic, geometric, and land-use data from the most congested corridors of the study city, TTCI values were estimated for the base and future conditions, followed by commuter volume estimation for the different conditions using vehicle occupancy factors. Further, the commuter volume derived from modal trade-off under CP scenarios was converted into traffic volume for the identified congested corridors. Finally, the TTCI values were re-estimated using the final traffic volume and compared across worst, best-worst (intermediate), and best case CP scenarios for the base and future years. An annual average growth of 5% in traffic volume was considered. The results show a significant improvement in TTCI values across all identified corridors under CP implementation, indicating its effectiveness toward congestion alleviation. Such demonstration of CP effectiveness could play a major role in making CP a successful travel demand management measure for cities burdened with congestion.