Case Studies on Transport Policy最新文献

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.

Distracted Driving Behavior is one of the leading factors responsible for road accidents. Using a case study of Pakistan, this study aimed to observe the effect of road type and conditions, trip timing, law enforcement, passenger type, and sociodemographic indicators on distracted driving behavior. The effect of driving experience on distracted driving behavior was also studied as a mediating variable. A questionnaire was prepared, and 501 responses were selected for this study. The PLS-SEM was employed to test the hypotheses of the study. The results showed that all the factors significantly influenced distracted driving behavior except passenger type. Trip timing had the strongest effect, suggesting drivers were more distracted during the daytime, possibly due to the ease of driving enabling environment, followed by significant effects of road type and conditions, age, and law enforcement. However, passenger presence did not significantly impact distracted driving in this study. The results indicate a need for suitable interventions with various stakeholders (policymakers, police, mental health experts, advocates, and community leaders) to raise awareness, change attitudes, and increase risk perception related to distracted driving behavior and its imperilments.

Marginalized communities usually experience inadequate public transport services in North America. Within these communities, buses play a vital role in everyday activity participation. Unfortunately, transport services that may advance equity by improving coverage and service for disadvantaged population groups and areas are often overlooked in transit planning since they usually underperform in ridership-based metrics.

To address this problem, the Toronto Transit Commission (TTC) introduced an equity service policy in 2019 to enhance bus services in vulnerable neighbourhoods known as Neighbourhood Improvement Areas (NIAs). This policy involves augmenting observed ridership counts for buses serving NIAs to improve or protect services for these communities. Although this proposed measure can improve bus services in NIAs, its current form might exclude other equity-deserving riders (EDRs) living outside NIAs, increasing their accessibility barriers.

Our study uses quantitative and spatial analytical methods to better understand the equity impacts of this service policy change. We propose moving from the aggregate neighbourhood-based approach using NIAs to a more comprehensive and disaggregated person-based approach. First, we create an alternate method that identifies EDRs at the bus stop level using a fusion of census and travel survey data. We then explore the differences in augmented ridership levels created by the two approaches and evaluate whether the augmented ridership levels are likely to result in meaningful service changes using existing TTC service standards.

We found that 2 out of 3 transit riders in Toronto are equity-deserving, with 72% residing outside NIAs. Our approach reveals increased ridership on routes with many EDRs, which receive minimal augmentation under the NIA-based method. Conversely, if all riders in NIAs are considered EDRs, our approach shows a 19% ridership overestimation equivalent to 35,245 users. Based on these results, we recommend creating a dedicated equity tool with an individual-centric focus, identifying areas with low transit service and high EDR percentages. This tool could then be integrated as an equity perspective into annual bus service planning.

The current study suggests a user satisfaction-based approach to prioritise attributes influencing walk accessibility to metro stations in Delhi, India. The target user group of the present study includes metro users who access the metro stations by walking. Responses from 466 such users are collected using smart tablets through face-to-face interviews. User satisfaction ratings towards twelve walk accessibility influencing attributes identified in the study are recorded on a six-point Likert-type ordinal rating scale. The study engages a comparative Multi-Attribute Decision Making (MADM) approach comprising three prominent techniques, viz., Relative to an Identified Distribution Integral Transformation (RIDIT), Grey Relational Analysis (GRA) and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for analysing the collected perception database and prioritising the attributes based on user satisfaction. The study outcomes identify ‘Extreme Weather Conditions’, ‘Illumination’, ‘Universal Design Considerations’ and ‘Safety and Security’ as the poorly performing attributes based on user perception and require immediate interventions. Spearman’s rank-order correlation analysis is performed to compare the attribute priority ranks derived from the three methods. The research findings can be useful to transportation planners, policymakers and enforcement officials in formulating and implementing strategies to allocate funds based on user-identified priorities for improving walk accessibility to metro stations.