Sustainable Transport Modes Research Articles

Evaluating the cost-emissions trade-offs of a modal shift in intermodal and synchromodal transportation planning

Abstract Accepted by: Aris Syntetos Intermodal transportation planning combines road with more sustainable transportation modes to encourage a modal shift. To evaluate the impact of a modal shift on transportation cost and emissions, we propose an intermodal transportation planning model to provide transparency in the cost-emissions trade-off. The model incorporates minimum load requirements, time windows, freight consolidation and stochastic travel times to generate alternative transportation options. It also includes order consolidation to facilitate the utilization of transportation modes that would otherwise be infeasible due to, for instance, minimum load requirements. We also propose a synchromodal planning tool to evaluate re-planning and re-consolidation options in response to disruptions. We numerically illustrate the working of our model using a representative network setting and quantify the trade-offs concerning costs and emissions by evaluating different transportation route options.

Flight quotas outperform focused mitigation strategies in reducing the carbon footprint of academic travel

The carbon footprint of academia has become a prominent concern and a burgeoning research area, with a notable focus on greenhouse gas emissions (GHG) from research-related travels. Mitigation strategies often promote alternatives, such as developing virtual communication or adopting sustainable transportation modes for short distances. While more ambitious strategies involving the transformation of research practices are increasingly discussed, these mitigation solutions are rarely subjected to rigorous quantitative assessments or meaningful comparisons. This study analyzes a unique database of about 130 000 travel segments by car, train and plane in 159 research entities across a wide array of disciplines in France. We investigate the patterns and associated carbon footprint of these research travels and explore a diversity of mitigation options. Our analysis shows that air travel overwhelmingly outweighs the carbon footprint of research travel, representing more than 96% of GHG emissions. Intercontinental flights are infrequent (less than 10% of all plane trips) but dominate GHG travel emissions, accounting for over 64% of total emissions. In contrast, domestic and continental flights are the most common but their mitigation potential by modal shift to train is limited (e.g. less than 15% for trips under 1000 km). Similar reductions can be achieved by targeting a small subset of travels, for example by modulating the frequency of conference attendance. The greatest and possibly most robust mitigation potential lies in combining modal shift with moderating air mileage (e.g. reducing travelled distance or number of flights). Strategies focusing on electrification or modal shifts for cars, proposed in official guidelines, are found to have negligible impact. In the absence of low-carbon alternatives for long-haul flights, we contend that only comprehensive strategies and policies which include moderating air travel distance or frequency can achieve a robust significant reduction in the GHG emissions from academic travel.

Fair and efficient ride-scheduling: a preference-driven approach

ABSTRACT Smart mobility and, in particular, automated ridesharing platforms promise efficient, safe, and sustainable modes of transportation in urban settings. To make such platforms acceptable to the end-users, it is key to capture their preferences not in a static manner (by determining a fixed route and schedule for the vehicle) but in a dynamic manner by giving the riders the chance to get involved in the routing process of an upcoming journey. To that end, this work provides a toolbox of multiagent methods that enable different forms of active preference-awareness in ridesharing services. We capture riders’ preferences (as end-users of a ridesharing service), preserve their privacy by avoiding expecting them to share preferences with other riders, and show the efficacy of the presented ridesharing algorithms using agent-based simulation and illustrating their utilitarian and fairness properties.

The Willingness to Purchase Electric Vehicles: A Comprehensive Review

This paper aims to comprehensively investigate the multifaceted factors influencing consumers’ willingness to purchase electric vehicles (EVs), providing a deeper understanding of the drivers behind EV adoption. The study draws on various scholarly sources to examine the intricate relationships among multiple determinants, including environmental concern, performance expectations, effort expectancy, charging point networks, charging time, price, operational costs, incentives, and attitude toward EVs. These factors are analyzed within a conceptual framework, highlighting the pivotal role of attitude as a mediating variable. The review reveals that environmental concern, driven by awareness of the ecological impact of conventional vehicles, motivates individuals to opt for EVs as a more sustainable mode of transportation. Performance expectations, such as energy efficiency and emission reduction, significantly influence consumer preferences. Effort expectancy, indicating the ease of using EV technology, plays a critical role in adoption decisions. Charging infrastructure, both availability and accessibility, is a crucial facilitator of EV adoption, emphasizing the importance of robust charging networks. Concerns about charging time underscore the need for faster and more convenient recharging methods. Price remains a barrier, with high initial costs, although operational cost advantages make EVs economically appealing. Depending on the region, government incentives have varying effectiveness in reducing financial barriers to EV adoption. Attitude toward EVs, acting as a mediating variable, highlights the importance of positive perceptions in shaping consumer intentions. This study offers a comprehensive review of the interplay of factors influencing EV adoption, providing a holistic view of consumer decision-making in the EV market. It emphasizes the need for further empirical research to validate and extend the proposed model. It offers valuable insights for policymakers, manufacturers, and researchers in promoting sustainable transportation solutions and accelerating EV adoption in response to environmental concerns.

Spatial Distribution and the Sustainability of Student Mobility of Top Universities in Bandung, Indonesia

As leading higher education institutions, top universities generate significant daily traffic. In addition, its high education quality often attracts youth to migrate and live closer to the university complex. The development of novel policies that support sustainable transport mode usage will become a role model and provide public benefits to the environment. Yet, there is little knowledge and limited research on university student mobility. This study aims to identify the significance of the daily trip distribution generated by top university students and identify the sustainability of its transportation modes by taking Bandung, Indonesia, as a case study. Responses from 383 students at 4 top universities were collected and then analysed using comparative analysis. The analysis reveals that 66,48 % of the students live in an area less than a 5 Km radius, yet, still depend on non-sustainable transport modes. This finding carries important policy implications to encourage more sustainable transport mode usage within this 5 Km area.

Charting a sustainable course: how normative factors shape intentions for Autonomous Rapid Transit commuting

With the continuous advancement of technology, transportation methods have undergone significant transformation, giving rise to innovative solutions like Autonomous Rapid Transit (ART). ART systems are designed to utilize hydrogen energy, serving as an efficient and eco-friendly power source. This not only addresses issues related to traffic congestion but also presents a promising solution to environmental challenges. However, the success of implementing such technologies to mitigate these challenges relies heavily on the support and acceptance of potential users. This study aims to explore the intention of users to adopt ART as a mode of transportation in the context of Sibu, Sarawak, Malaysia. This study conducted a comprehensive survey involving 350 respondents and employed Partial Least Squares Structural Equation Modelling (PLS-SEM) to analyse the data. The findings of this study reveal that several critical factors significantly influence the behavioural intention to use ART for commuting. Specifically, subjective norms, perceived behavioural control, and individual attitudes have a significant impact on the intention to embrace ART as a sustainable mode of transportation. However, the study also finds that personal norms do not exhibit a significant relationship with behavioural intention. This insight underscores the pivotal role of societal influences compared to individually internalized values in shaping user decision-making with regard to the adoption of ART for commuting. It is imperative for policymakers to take into account the perspectives and considerations of users when formulating policies related to the introduction and promotion of new public transportation modes where private transportation has traditionally been prevalent.

How far are cities from the x-minute city vision? Examining current local travel behavior and land use patterns in Montreal, Canada

In the past three years the 15-minute city planning concept has captured the attention of policy makers and the public worldwide. Some regions have included it in their planning goals and others modified it to 30 min to make it more attainable in their local context. The goal of this research is to measure whether the 15- or 30-minute city goals align with current travel behaviour and land use patterns in the North American context using Montreal, Canada as the case study. In doing so, we look at which destinations are cultivating local travel patterns consistent with the 15- and 30-minute city concepts and identify any unique qualities of these areas using the 2018 Montreal origin-destination travel diaries. Our bivariate analysis finds very few destinations in Montreal where a high number of trips and high percentage of trips are ending using a sustainable mode of transport and below the 15- or 30-minute travel time threshold. We further investigate the land use patterns that align with the 15- and 30-minute city to recommend realistic planning goals and policy interventions that match the North American context. The findings from this research can be of interest to transport professionals and policy makers trying to implement the 15- or 30- minute city concepts to their regions.

Towards Sustainable Transport in the Moroccan Context: The Key Determinants of Electric Cars Adoption Intention

In recent years, many countries have actively promoted sustainable mobility as part of their efforts to decarbonize transportation through automotive electrification. Therefore, identifying the factors that influence individuals’ interest in using electric cars (ECs) is crucial for guiding public opinion toward choosing this sustainable mode of transportation. Consequently, the present study mobilized the theory of planned behavior and the technology acceptance model to interpret the various factors influencing the intention to adopt ECs in a developing country. Following the developed model, data were collected from individuals using cars in Morocco through an online questionnaire. Data analysis using structural equation modeling revealed a positive influence of relative advantage on both the perceived ease of use and green perceived usefulness. Furthermore, the perceived ease of use, green perceived usefulness, environmental concern, and social influence positively affected attitudes toward using ECs. Similarly, these results confirmed that green perceived usefulness and individual attitudes positively enhance ECs adoption intention. These findings contribute to the literature related to ECs adoption and offer guidance to policymakers on promoting ECs adoption in developing countries.

Toward the Enhancement of Rail Sustainability: Demonstration of a Holistic Approach to Obstacle Detection in Operational Railway Environments

Rail transport plays a crucial role in promoting sustainability and reducing the environmental impact of transport. Ongoing efforts to improve the sustainability of rail transport through technological advancements and operational improvements are further enhancing its reputation as a sustainable mode of transport. Autonomous obstacle detection in railways is a critical aspect of railway safety and operation. While the widespread deployment of autonomous obstacle detection systems is still under consideration, the ongoing advancements in technology and infrastructure are paving the way for their full implementation. The SMART2 project developed a holistic obstacle detection (OD) system consisting of three sub-systems: long-range on-board, trackside (TS), and Unmanned Aerial Vehicle (UAV)-based OD sub-systems. All three sub-systems are integrated into a holistic OD system via interfaces to a central Decision Support System (DSS) that analyzes the inputs of all three sub-systems and makes decision about locations of possible hazardous obstacles with respect to trains. A holistic approach to autonomous obstacle detection for railways increases the detection area, including areas behind a curve, a slope, tunnels, and other elements blocking the train’s view on the rail tracks, in addition to providing long-range straight rail track OD. This paper presents a demonstration of the SMART2 holistic OD performed during the operational cargo haul with in-service trains. This paper defines the demonstration setup and scenario and shows the performance of the developed holistic OD system in a real environment.

Spatial Analysis of Bike-Sharing Ridership for Sustainable Transportation in Houston, Texas

This study aims to analyze bike-sharing information and related urban factors to promote bike-sharing utilization in Houston, Texas. The research was initiated with a descriptive analysis, where the hourly and daily variations in bike demand are investigated, thereby revealing the time-related patterns of bike tours. The models included data on socio-demographics, public transportation availability, land use patterns, tree canopy coverage, bike routes, and job density within 0.25-mile and 0.5-mile buffer zones around each bike-sharing station. Stepwise regression was utilized to examine the effects of urban factors on bike-sharing ridership, and the explanatory power of the model was enhanced by selecting meaningful variables. The analysis found that tree canopy coverage was a significant factor in influencing bike-sharing ridership. Expansion of tree coverage can help make biking a sustainable mode of transportation. These findings have the potential to guide the development of practical policies that aim to promote sustainable urban mobility through bike-sharing programs.

Bicycle Infrastructure Design Principles in Urban Bikeability Indices: A Systematic Review

Bicycling is a sustainable form of micromobility and offers numerous health and environmental benefits. Scientific studies investigating bikeability have grown substantially, especially over the past decade. This paper presents a systematic literature review of the developed urban bikeability indices (BIs). The paper provides insight into the scientific literature on bikeability as a tool to measure bicycle environment friendliness; more importantly, the paper seeks to know if the BIs consider bicycle infrastructure design principles. Data extraction included identifying the geographical location, essential indicators, sample size and distribution, data source, the unit of analysis, measurement scale, methods used to weigh indicators, and identification of studies using bicycle design principles in BIs. The database search yielded 1649 research articles using different keywords and combinations, while 15 studies satisfied the inclusion criteria. The studies were found to be conducted in various geographical locations. The unit of analysis for developing the index varied across studies, from street segments or bicycle lanes to zones within the city or even the entire city. The most commonly utilized method in developing urban BIs was a scoring and weighting system to weigh the indicators. The weighting methods include an equal weight system, survey-based and literature review-based methods, expert surveys, the analytic hierarchy process, and a weighted linear combination model. The essential criterion is bicycle infrastructure, such as bike lanes, routes, and bicycle paths as 14 studies considered it for the construction of the BIs. The review findings suggest a lack of consideration of all five bicycle infrastructure design principles, as only three studies considered them all, while others only included a subset. Safety and comfort are the most commonly considered principles, while coherence is the least considered principles in the BIs. It is crucial to consider all five bicycle infrastructure design principles to create a bicycle-friendly environment and attract more people to this sustainable mode of transportation.

Investigating the influence mechanism of goal‐framing theory on urban residents' green travel behavior

AbstractThis study aims to explore the influence mechanism of goal‐framing theory on green travel behavior (GTB), thereby supporting the promotion of sustainable transportation modes to mitigate environmental degradation and resource waste, in alignment with the “dual carbon” targets. Based on the GTB data of 334 Chinese residents, we use goal‐framing theory to analyze residents' subjective environmental concerns and the external media's driving mechanism on their choice of green travel through a structural equation modeling (SEM). At the same time, the mediating effect of goal frames is tested through mediation testing. The results show that: 1. indirectly encouraged by media persuasion influencing their normative and hedonic goals; 2. encouraged by normative and hedonic goals partially mediating the relationship between environmental concerns and GTB; and 3. surprisingly, not very affected by influencing their gain goals. The implications of this research provide actionable insights for interventions, messaging strategies, transportation industry practices, environmental policy development, and theoretical advancements. For future research, it is essential to delve into regional variations and to more thoroughly account for the influence of external factors on GTB.

Unraveling the relation between cycling accidents and built environment typologies: Capturing spatial heterogeneity through a latent class discrete outcome model

Today, cities seek to transition to more sustainable transportation modes. Cycling is critical in this shift, promoting a more beneficial lifestyle for most. However, cyclists are exposed to many hazardous circumstances or environments, resulting in accidents, injuries, and even death. Transport authorities must understand why accidents occur, to reduce the risk of those who cycle.This study applies a new modeling framework to analyze cycling accident severities. We employ a latent class discrete outcome model, where classes are derived from a Gaussian–Bernoulli mixture, applied to data from Berlin, and augmented with volunteered geographic information. We jointly estimate model components, combining machine learning and econometric approaches, allowing for more intricate and flexible representations while maintaining interpretability.Results show the potential of our approach. Risk factors are indexed depending on where accidents occurred and their contribution. We can discover complex relations between specific built environments and accident characteristics and uncover differences in the impact of certain accident factors on one environment typology but not others. Using multiple data sources also proves helpful as an additional layer of knowledge, providing unique value to understand and model cycling accidents. Another critical aspect of our approach is the potential for simulation, where locations can be examined through simulated accident features to understand the inherent risk of various locations.These findings highlight the ability to capture heterogeneity in accidents and their relation to the built environment. Capturing such relations allows for more direct countermeasures to risky situations or policies to be designed, simulated, and targeted.

Measuring and visualising 15-min-areas for fair CO2 budget distribution

The “MyFairShare” project develops fair CO2 mobility budgets for individuals. Here, “fairness” mainly depends on the people’s location as everyone should be able to access all destinations necessary to perform everyday tasks. Therefore, a basic understanding about the accessibility of facilities to visit within an area is needed, regarding all activities that must be performed. Given this, the amount of emitted CO2 is computed, assuming the use of sustainable modes while regarding reasonable ranges, i.e. a travel time of 15 min. In order to achieve this, a software system for computing this metric has been developed. It is based on open source applications and uses data that—besides public transport data in GTFS format—is freely available throughout Europe. This paper describes the method and presents the results of applying it to the project’s five Living Labs Berlin, Jelgava, London, Sarpsborg, and Vienna. The results show that besides population density, the possibility to use sustainable modes of transport highly depend on the land use mix, i.e. the allocation of facilities daily activities may be performed at in the vicinity of places of inhabitancy.

Smart Cities and Sustainable Urban Mobility: An Analysis of Urban Indicators of Marau/RS

The increasing problems related to urban mobility in Brazilian municipalities, caused mainly by uncontrolled urbanization and constant growth in the automotive vehicle fleet, is directly related to the difficulties presented in the public management of Brazilian cities, mainly with regard to urban planning. The objective of this article is to analyze users’ satisfaction of the urban mobility system in a small municipality, as well as the condition of the city's physical characteristics, mainly identifying those that interfere with urban mobility, checking the most used modes in each sector of the city of Marau/RS and the mobility situation by age group and income, finding existing problems in each of the modes. To this end, a documentary survey was carried out on the object of study, a physical survey of the characteristics of the municipality, and a questionnaire with 84 respondents. The results obtained reveal the use of private cars as the main means of daily transport, correlated with low incentives and accessibility to sustainable modes of transport.

Evincing the social and economic impact of inland waterways transportation in the development of the Port Harcourt metropolis

Road traffic congestion has been decreased by using water transportation. The impact of inland waterways transportation on the socio-economic growth of Port Harcourt Metropolis was investigated in this essay. The study adopted a quantitative research approach using a cross-sectional survey design and employed a multi-stage sampling technique. The first stage involves identifying the locations of the jetties and navigable routes available in the metropolis. The second stage involves the listing of the jetties and navigable routes found within the study area which nine (9) jetties and navigable routes were identified. The third stage involves purposively selecting six (6) jetties out of the nine (9) jetties listed. The selected jetties and navigable routes include (Bonny/Bille/Nembe, Marine Base, Abonnema Wharf, Maccoba, Iwofe, and Akpos). The six (6) jetties were selected because of their frequent usage by commuters. The fourth stage involves randomly selecting 200 commuters who are using these jetties and navigable routes for sampling. Using a random sample technique, a structured questionnaire was designed and distributed to the commuters to acquire data for the study. Descriptive statistics (tables and charts) and inferential statistics were used to analyse the data set. Other sources of data for the study include direct observation and photographs to characterise the study area and inland waterways transportation development in the metropolis. The reason the study chose to focus on the commuters and boat operators is because the commuters and operators are individuals who commonly use inland waterways transportation systems. The study found that lack of funds, poor river basin dredging and canalisation, insufficient security and infrastructure, a lack of safety devices, and inadequate training of boat operators and drivers are among the issues and obstacles. Therefore, the study recommends that the government should support efforts to enhance boat service operations for sustainable modes of transportation to promote their use by more people and ease traffic on the roads.

ANALISIS PENGARUH E-WOM, BRAND IMAGE DAN TRUST TERHADAP PURCHASE INTENTION ECO-FRIENDLY TRANSPORT DI SURAKARTA

This research aims to test the analysis of the influence of E-Wom, brand image, and trust on purchase intention for eco-friendly transport in Surakarta. Participants in this research who utilise environmentally sustainable modes of transportation in Surakarta. The sample used was users of eco-friendly transport products aged 17 and over, and 309 respondents were domiciled in the Surakarta area. PLS 3.0 analysis was utilised by the researchers to conduct a quantitative examination of the research data. Trust significantly and positively influences the purchase intention of eco-friendly transport users; the brand image variable significantly and positively influences the purchase intention of eco-friendly transport users; e-wom positively and significantly influences the brand image of eco-friendly transport users; and trust significantly and positively influences the purchase intention of eco-friendly transport users.

Techno-Economic Sustainability Potential of Large-Scale Systems: Forecasting Intermodal Freight Transportation Volumes

The sustainability of large economies is one of the most important challenges in today’s world. As the world strives to create a greener and more efficient future, it becomes necessary to accurately analyze and forecast freight volumes. By developing a reliable freight transportation forecasting model, the authors will be able to gain valuable insights into the trends and patterns that determine the development of economic systems. This will enable informed decisions on resource allocation, infrastructure development, and environmental impact mitigation. Such a model takes into account various factors such as market demand, logistical capabilities, fuel consumption, and emissions. Understanding these dynamics allows us to optimize supply chains, reduce waste, minimize our carbon footprint, and, ultimately, create more sustainable economic systems. The ability to accurately forecast freight volumes not only benefits businesses by enabling better planning and cost optimization but also contributes to the overall sustainable development goals of society. It can identify opportunities to shift to more sustainable modes of transportation, such as rail or water, and reduce dependence on carbon-intensive modes, such as road or air. In conclusion, the development and implementation of a robust freight forecasting model is critical to the sustainability of large-scale economic systems. Thus, by utilizing data and making informed decisions based on these forecasts, it is possible to work toward a more sustainable future for future generations.

The environmental experience during daylight and dark conditions: a conceptual model for pedestrians and cyclists / La experiencia ambiental en condiciones de luz diurna y oscuridad: Un modelo conceptual para peatones y ciclistas

Walking and cycling are considered sustainable transport modes, promoted as a means to reduce car traffic. In the scientific literature, they have mostly been investigated separately, but should be considered jointly to enable a modal shift. Both daytime and dark conditions need to be studied, to improve understanding of how environmental features are affected by temporal variation. A conceptual model is introduced to advance understanding of the significance of different environmental factors for walking/cycling, and serves as the basis for the design of an empirical study. A between-subject design was used, comparing two pedestrian/cycle paths located in two mid-sized Swedish cities during daytime and after dark. Pedestrians ( n = 90) and cyclists ( n = 74) responded to questionnaires assessing environmental parameters hypothesized to be of importance for walking and cycling. Three-factor ANOVAs indicated differences between the two locations (perceived stimuli), between pedestrians and cyclists (environmental appraisal, affective response, behavioural intention) and between daytime and dark conditions (visual accessibility, restorative potential). The conceptual model helps identify the importance of various environmental features.

Exploring Computing Paradigms for Electric Vehicles: From Cloud to Edge Intelligence, Challenges and Future Directions

Electric vehicles are widely adopted globally as a sustainable mode of transportation. With the increased availability of onboard computation and communication capabilities, vehicles are moving towards automated driving and intelligent transportation systems. The adaption of technologies such as IoT, edge intelligence, 5G, and blockchain in vehicle architecture has increased possibilities towards efficient and sustainable transportation systems. In this article, we present a comprehensive study and analysis of the edge computing paradigm, explaining elements of edge AI. Furthermore, we discussed the edge intelligence approach for deploying AI algorithms and models on edge devices, which are typically resource-constrained devices located at the edge of the network. It mentions the advantages of edge intelligence and its use cases in smart electric vehicles. It also discusses challenges and opportunities and provides in-depth analysis for optimizing computation for edge intelligence. Finally, it sheds some light on the research roadmap on AI for edge and AI on edge by dividing efforts into topology, content, service segments, model adaptation, framework design, and processor acceleration, all of which stand to gain advantages from AI technologies. Investigating the incorporation of important technologies, issues, opportunities, and Roadmap in this study will be a valuable resource for the community engaged in research on edge intelligence in electric vehicles.