Case Studies on Transport Policy最新文献

This study examined the long-term impacts of the COVID-19 pandemic on mobility patterns in Indonesia, focusing on the transition from pre-pandemic norms to the endemic phase. Using quantitative methods and retrospective data analysis, we explored changes in travel behaviour, including mode choice, trip frequency, and travel time. We identified travel behaviour in three phases: pre-pandemic, pandemic (March 2020 to the end of January 2022), and transition to endemic (the data collection period: July – August 2022). Our investigation of the shifts in travel behaviour across these periods enabled us to distinguish between temporary fluctuations and enduring, potentially long-term changes in behaviour. The empirical investigation revealed significant alterations in trip frequency that persisted during the endemic phase, suggesting that these changes in mobility are likely to continue. Factors influencing these shifts include socioeconomic characteristics, work modalities, and attitudes toward health protocols. This study contributes to the understanding of pandemic-induced travel behaviour transformations and provides insights for policymakers and transportation planners to adapt to these changes in the Southeast Asian context.

Over the last two decades and a half, the Ethiopian government has been involved in extensive road construction as part of successive road development plans that have significantly increased road network coverage. However, the tendencies that worsen congestion show no signs of abating. As a result, drivers and passengers waste time in long traffic lines, rendering modern travel unreliable and increasing travel costs due to delays. To curb the problem, the remedies proposed by practitioners or researchers are mostly centred on the supply side. This study aims to determine drivers’ willingness to pay (WTP) (from the demand side) for a hypothetical congestion reduction project. A stated preference survey was utilised on the population identified in nine segments in Addis Ababa’s Kolfe Keraniyo sub-city. The data was gathered from 1012 respondents using a survey questionnaire based on the contingent valuation method (CVM). Tobit and Heckman two-step selection models were used to estimate factors determining WTP for congestion reduction. Accordingly, the analysis showed that the average amount of willingness to pay by drivers was estimated to be birr 2.7 ($0.05) per km. Education, marital status, income, segment use, and trip frequency significantly determined the outcome equation, while age, gender, income, occupation, work experience, and regularity and frequency of segment use were found to determine the decision to participate in WTP to accept congestion pricing. Identifying the willingness to pay and the desired price can assist the Addis Ababa City Administration in establishing a baseline for any future congestion reduction strategy based on congestion pricing.

In response to the imperatives outlined in SDGs 7, 11, and 13 and the Paris Agreement, folks increasingly focus on transportation to mitigate climate change. Uganda’s capital, Kampala, lacks ratified passenger land transportation plans. This study employs the KLAP-TIMES model, a bottom-up engineering framework, to examine Kampala commuters’ behaviors using three scenarios. Leveraging TIMES-VEDA, the study explores a baseline scenario (BAU) without time travel financial (TTF) limitations or distinctive Value of Travel Time (VTT) levels but with model permissions for competition among dissimilar trip modes, technologies, and fuels, a Kampala Accessibility and Priority Options (KAPO) Scenario with specific VTT levels under TTF limitations, and the Kampala Sustainable scenario (KSS), with a 50% carbon emissions bargain in the system by 2060, contingent upon the persistence of VTT and TTF over the planning horizon. The study utilizes the VTT purposively to measure infrastructure investments as a policy shock on travel time. By exogenously inputting travel demand, the model elucidates the endogenous preferences of individual commuters among various trip modes, including Boda-boda, Kampala sedans, and mass rapid transit (MRT) with an electrified Metro at its core, for both short—and long-distance journeys. The findings reveal significant shifts in consumer behavior, particularly in the Kampala Sustainable scenario, where commuters prefer the electrified Kampala Metro for both short—and long-distance travel, signaling a notable departure from traditional Kampala sedan usage. The study suggests prioritizing the value of travel time (VTT) alongside a carbon reduction trajectory (KSS) is a strategic route for sustainable mobility in Kampala. The study provides valuable insight to policymakers, aiding them in formulating and enacting transportation policies that effectively support Kampala’s sustainability objectives.

The increasing demand at maritime traffic nodes in multi-modal transport emerges as a critical factor for the country’s economy. Consequently, terminal operators should focus on proper strategies and policies to satisfy the increasing demand. This paper exploits the integration of Information Communications Technology systems into physical infrastructures and offers an in-depth study of operations and performance optimisation for a maritime terminal. The case study is the Messina-Tremestieri port (Sicily, South Italy), characterised by a high flow of cars and freight vehicles. This port is in the comprehensive Trans-European Transport Network, and it links Sicily Island with Italy, offering high-frequency services. About 30% of the goods by Ro-Ro services pass through this port: so, it makes sense to use it as a case study. The arrivals distribution, the terminal capacity and the supply offered by the shipping companies are considered input, and terminal efficiency is evaluated through indicators such as the saturation of the yard area and the average vessel load factor. Besides, the study offers two viable solutions to the emerging port saturation. First, a tactical policy (with no infrastructural costs) includes the introduction of flexible time windows. Alternatively, the introduction of additional vessel services has been evaluated during peak hours. Benefits have been simulated by comparing the total number of vehicles served in current and simulated scenarios.

The FMCG (Fast-Moving Consumer Goods) sector is the fourth largest sector in India, significantly contributing to the economy by driving the growth of gross domestic product (GDP) and enhancing employment opportunities. In India, most of the transportation of FMCG goods is dependent on road freight transport only hence the vehicle fill rate is gaining importance day by day. The vehicle fill rate is adversely influenced by various constraints including weight & load limits, variability in truck carrying capacity, etc. that further influence the performance of road freight transport, resulting in high transportation costs. Various strategies are required to overcome the constraints which will help optimize transportation costs for the FMCG sector in India. This study identified 32 solutions with Fuzzy TOPSIS (Fuzzy Technique for Order Preference by Similarity to Ideal Solution) employed for ranking of the solutions. Transport policy is identified as one of the top solutions, which plays a vital role in improving vehicle fill rate in the long run. Implementation of the solutions according to the need and rank may help the decision-makers and policymakers to achieve enhanced performance in road transport, compete globally, and contribute to the economy as well as the environment.

Introduction

Introducing new public transit systems impacts the surrounding built environment, and changes in the built environment can affect travel behavior. Prior research has yet to thoroughly conduct a comprehensive exploration of the influence of new investments in public modes of transit, particularly streetcars, on motor vehicle crashes occurring on adjoining streets, considering other related factors. In particular, the difference between short-term and mid-term impacts of streetcars considering initial break-in periods has yet to be thoroughly conducted. This study focuses on the short-term and mid-term effects of the streetcar on total, injury, and pedestrian-involved vehicle crash rates on the adjacent street, considering traffic volume, traffic speeds, and traffic conflicts (transit ridership, pedestrian volume, and traffic policy).

Data & Method

This paper used the Utah Department of Transportation’s (UDOT) crash count, annual average daily traffic (AADT), iPeMS data, Utah Transit Authority’s (UTA) ridership, manually calculated pedestrian volume from Google Street View, and conducted interviews with UDOT’s experts. In the method, we used three quasi-experimental research designs: (1) before-after without a control group, (2) interrupted time series, and (3) before-after with a control group. In addition, to identify the cause of this impact, we examined multiple dimensions, including traffic volume, traffic speeds, transit ridership, pedestrian volume, and adjustments in traffic policy changes.

Results

As a result, the establishment of the S-Line streetcar eventually led to a significant decrease in total (short: 11 %, mid: −15 %), injury (short: −9%, mid: −41 %), and pedestrian-involved (short: −25 %, mid: −43 %) crash rates on the adjacent street, especially after the streetcar was fully established (3 years after). In particular, injury and pedestrian-involved crash rates decreased significantly. Also, we found that increased drivers’ awareness and vitality of the street due to the increased transit ridership (short: 43 %, mid: 50 %), increased pedestrian volume (short: 35 %, mid: 75 %), and improvement of traffic signal on the adjacent street can be the main causes.

Practical Applications

The outcomes of this study are considered to help establish short-term and mid-term traffic policies that consider public transit improvements such as streetcars.

In the push for passenger transportation electrification, Plug-in Hybrid Electric Vehicles (PHEVs) serve as a suitable bridge towards sustainable transportation, especially in settings marked by rapid urbanization and socio-economic variations, such as India. Compared to conventional vehicles, PHEVs can offer distinct advantages, but Battery Electric Vehicles (BEVs) often overshadow their potential. Addressing the dearth of PHEV-specific research, this study investigates consumer attitudes and preferences for PHEVs in two Indian megacities: Delhi and Kolkata. Using a three-step method on attitudinal and stated preference data from 415 (Delhi) and 500 (Kolkata) car-owners, the study segmented consumers employing factor and cluster analyses, revealing dominant groups such as the ’actively concerned’, which merges consumers with technological enthusiasm and environmental awareness. Mixed logit models further unveil consumers’ willingness-to-pay (WTP) for various PHEV attributes. Notably, Delhi consumers exhibited 56 % more WTP for Advanced Vehicle Technology (AVT) options compared to their Kolkata counterparts. While Delhi consumers prioritized battery range, battery warranty, and recharging time, Kolkata consumers emphasized emission reduction. Sensitivity analysis revealed price as a dominant adoption barrier, suggesting subsidies could enhance PHEV uptake. This research highlights diverse PHEV preferences across Indian cities, underscoring the need for city-specific policy interventions.

Passenger and freight transport are central to the socio-economic development of countries and urban life. Their enormous consumption of fossil fuels is problematic. It is essential to improve the efficiency and sustainability of this industry, especially in road transport. This paper assesses the heavy goods vehicles (trucks), as a specific segment of road transport, in Morocco from an energy standpoint. For this purpose, a methodology called DMAIC (Define, Measure, Analyze, Improve, and Control) was adopted to systematically define problems, measure the current state, analyze data to identify inefficiencies, as well as implement and monitor improvements for sustainable performance in this sector. The findings show that Moroccan trucks have significant sustainability gaps, characterized, mainly, by high fossil fuel consumption resulting in high exhaust emissions. The promotion of alternative powertrains such as hybrid, electric and fuel cell vehicles offer promising opportunities to reduce oil consumption and greenhouse gas emissions. Although these alternative powertrains have the potential to improve operational performance over traditional diesel models in Morocco, several challenges need to be addressed for their widespread uptake.

Transport infrastructures serve as pathways to employment, amenities, and services, contributing to the economic development of societies and the broader landscape. Development projects are usually measured on economic metrics; however, they can have short-term and long-term impacts on wellbeing due to disruptions during construction and changes in accessibility after construction. This study investigates the impact of transport construction projects on the residents’ satisfaction with surrounding neighbourhoods. This study uses the longitudinal survey of Household Income and Labour Dynamics of Australia (HILDA) from 2002 to 2019 to monitor and model satisfaction with neighbourhoods for residents living in the vicinity of 11 major transport construction projects in Sydney, Australia. The variations in residents’ satisfaction with neighbourhoods are investigated at macro and micro levels. At the macro level, average satisfaction before during and after construction are compared against each other. At the micro level, two random effect ordered logit models are developed to explain satisfaction while controlling for residents’ sociodemographic attributes and major life events. Both highway and underground projects have been shown to improve overall satisfaction among all residents. However, during the construction phase for underground, satisfaction with neighbourhoods tends to decrease. The highway projects exhibit a positive effect on residents even during the construction phase, with a higher positive effect for permanent residents.

One of the significant sources of urban air particulate matter (PM_2.5 and PM₁₀) has been found to be vehicle exhaust emission. Vehicle restriction measures have been taken to alleviate particulate matter pollution in the world. Here, we quantified the impact of vehicle restriction measures on the PM_2.5 concentrations using the Weather Research and Forecasting model with Chemistry (WRF-Chem) in Kaifeng, China. This study set up three different scenarios to simulate the spatiotemporal changes of PM_2.5 concentrations in four seasons in 2020. They were no emission reduction (S0), the restriction of two tailing license plate numbers (S1), and the restriction of odd–even tailing numbers of license plates (S2), respectively. In general, the odd–even license plate restriction policy has proven to be more effective than restricting two specific license plate numbers. In scenario S1, the range of PM_2.5 concentrations reduction in Kaifeng City was between 0.2% and 1.28%. In scenario S2, the range of PM_2.5 concentrations reduction was between 0.98% and 14.42%. The results showed that the effectiveness of vehicle restriction measures varies from season to season, and the effect in summer and winter is better than that in spring and autumn. We suggest that it may be difficult to reduce the PM_2.5 concentrations to a great extent if simply reducing the traffic exhaust emissions through motor vehicle restrictions, on the contrary, would lead to the increase of O₃ concentration, bringing some other effects. This study can serve as a foundation for the rational development of motor vehicle control strategies and help advance the ongoing improvement of air quality.