Transportation最新文献

With the rapid development of autonomous driving technology and the sharing economy, autonomous driving has significant potential to offer a broader range of travel choices for travelers. To explore different commuters’ autonomous vehicles—related behavioral decisions and choice preference, this study designed a personalized travel experience survey and established travel choice models incorporating individual perceptions and attitudes for two groups. It was found that commuters’ perceptions of autonomous vehicles were significantly improved by travel experience. Travel time is the most concerned factor in travel mode choice for private car commuters, while travel cost is the most important factor for public transport commuters. Therefore, enhancing operational efficiency and reducing the energy consumption of autonomous vehicles could effectively encourage commuters to adopt new travel modes. Improving travelers’ travel experiences and positive attitudes towards using autonomous vehicles is conducive to the adoption of private autonomous vehicles by private car commuters and the choice of shared autonomous vehicles by public transport users. By promoting people’s acceptance of ride-sharing and awareness of its benefits through user experience, publicity, and guidance, a substantial increase in the adoption of shared autonomous vehicles can be achieved among both commuter groups. Suitable thresholds for crucial factors, including travel time and cost, perception, and attitudes towards ride-sharing, were determined for both groups to facilitate their mode transfer among traditional travel modes and autonomous vehicles. The research findings can provide a reference for anticipating travel demand and guiding the formulation of transport policies for future transportation systems.

Conventional methods to understand urban transportation mode choice primarily revolve around assessing the relation costs/benefits among the different mobility alternatives. However, emerging research has emphasized the significance of comprehending intricate social processes that shape decision-making in urban mobility. This study delves into the impact of social networks on aggregated travel behavior, using a comprehensive dataset encompassing multiple data sources such as Twitter/X messages, bicycle sharing system (BSS) and traffic counts, weather and socio-demographic information. Focusing specifically on the city of Madrid, Spain, the dataset covers an extensive period, capturing daily data from 2018 to 2021. To gain deeper insights into the underlying influences, a combination of panel regression models and a topic modeling approach were employed for analysis. The study’s findings highlight the significant impact of social media communication on transportation behavior, revealing a positive correlation between higher social media message volume and increased usage of public and sustainable transportation options like subways and BSS, while private car usage decreased. Although there is message salience, i.e., a sudden surge in tweet numbers leads to a temporary shift in behavior, the findings suggest that municipalities can effectively influence transportation behavior by strategically communicating messages related to sustainable transportation through social networks.

Global warming is a serious threat to humanity, and greenhouse gases are behind it. CO₂ is one of the main greenhouse gasses that cause global warming. The second most important reason behind CO₂ emission is the transport sector. Electric-powered Vehicles introduced by the automobile sector are regarded as the main alternative to cope with this issue. Despite their advantages, EV adoption rates vary by country, and the expected reductions in energy shortages and pollution are not fully achieved. We took the opportunity to assess the consumer EV adoption intention by using the Value-based technology adoption model. We integrated Environmental awareness (EA) and Self-identification expressiveness (SIE) as new factors in this model to assess the role of EA and SIE in EV adoption intentions. We have collected the response of 704 EV users from China and applied the SEM-ANN dual-stage hybrid model to test proposed hypotheses and rank the variables according to their importance. Study findings revealed that Environmental awareness is a significant predictor of EV adoption but is not the most important factor. Study results also revealed that the perceived benefits of EV adoption and perceived sacrifices for its adoption have a significant impact on the perceived value of EV, and this value leads to the adoption intentions. PV is revealed as a significant mediator in our proposed model. We conclude that people need to educate about environmental issues and the benefits of using EVs to achieve the CO₂ reduction and EV sale target. The study has several theoretical and practical implications for the government and the electric vehicle manufacturing industry.

A lack of charging opportunities is cited as one of the main barriers to the adoption of plug-in battery electric vehicles (BEVs). Charging opportunities are even more limited for the millions of households across Europe without the space to charge a vehicle at home, but research has not previously targeted these households. This study aims to fill this gap by assessing whether and how such residential parking constraints shape norms, attitudes and perceived behavioural control over charging, and thus intentions to adopt a BEV. Data from a nationally representative survey of car drivers in the UK without a private driveway or garage captures the perspective of these individuals who have different characteristics from early adopters of BEVs. The results show that personal norms around the environmental benefits of BEVs and positive attitudes towards BEV technology have the greatest influence on intentions to adopt, whilst social norms and perceived behavioural control over charging are less influential. The results also show that high income men are most likely to hold positive social norms that boost their intentions to adopt BEVs, whilst geographical context affects both social norms and perceived behavioural control over charging. In summary, the psychological approach applied shows that a more inclusive transition to BEVs is best supported by policies that first focus on emphasising their environmental benefits and that they are fun and economical to drive, and then look to increase social expectations and awareness of BEVs and charging infrastructure.

This paper deals with the foundations of current and past mobility cultures, identifies emerging trends and main drivers that contribute to the shaping of the future European mobility cultures, and focuses on the role of communication. The methodology adopted to better understand this complex concept involved 3 major steps: first a literature exploration, then a foresight involving strategic application of forward-looking approaches in shaping and informing public policy decisions which needed, and finally backcasting exercise to mainly build future scenarios. During these steps, we aimed to identify, involve and create a community of high level experts and thinkers in various fields: philosophy, psychology, sociology, geography, urbanism, architecture, economics, poetry, art. This involvement led to 29 scientific discussions of 3 types: 15 Talks with 16 experts, 5 Explorative Conversations with 11 experts and 9 Generative Dialogues with 11 experts. We have also organized 3 focus groups and 5 workshops to deepen our thinking on specific topics and involve a larger group of experts: Mobility values, Imagining future scenarios on mobility cultures, Public interest definition, Design a roadmap and outline feasible strategies. A survey of European citizens was carried out to involve them in an open consultation of the vision. Experts and thinkers were interviewed to stimulate discussion on how they understand mobility cultures and what drives it, to identify trends in mobility cultures and how they perceive mobility’s future. The idea was also to confront different or conflicting ideas and to identify the nuances and uncertainties, particularly with regard to the trends and future mobility cultures. As a result, we developed a vision not only of current and past mobility cultures, but especially of the expected and likely mobility future. We created 4 (extreme) political and societal scenarios for the mobility future and named them according to Greek divinities: Hercules, Themis, Hermes, and Gaia. The final results are a combination of several elements from different scenarios. The most desired future mobility clearly tends towards the Themis and Gaia cultural values of equity and well-being, while the Hermes cultural value of efficiency is perceived as driving the most likely future. This mismatch between expected and desired futures clearly expresses tensions between elements of mobility cultures. This gap points to a direction for future European mobility policy, away from efficiency and towards alternative values of sufficiency, care, and justice. Although we intended to cover the whole of Europe, Western Europe has remained relatively over-represented.

Insufficient parking has emerged as a critical global transportation concern, particularly in central business districts, leading to congestion in urban transport networks with significant social, economic, and environmental implications. In Debre Markos city, the demand for taxis and travel is swiftly rising due to population growth. However, existing road facilities are inadequate, reducing road capacity, mobility, and exacerbating traffic congestion. On-street parking, encompassing parking occupancy, double parking, differences in peak hours between restaurant activity and passing traffic, lack of driver discipline, and the reduced maneuverability of older vehicles, all contribute to narrowing the available road width, thus impeding traffic flow. This study aims to bridge this knowledge gap by investigating the traffic congestion caused by on-street parking and its impacts on traffic flow. Study results indicate that on-street parking significantly reduces road capacity by 24.1% due to legal parking activities and an additional 25.89% due to illegal double parking. Removing on-street parking could enhance road capacity by 49.9% and reduce travel time by 36%. Additionally, the model reveals a strong relationship between on-street parking and the delay of vehicle movement toward parking locations, with each increase in parking occupancy decreasing average travel speed by 0.03 km/h. This study emphasizes the necessity for proactive policies to address parking issues and uphold urban street service levels amid increasing traffic demands. Local authorities can use the model as a guide for implementing parking prohibition policies, including utilizing dead-end roads for short-term parking, enhance enforcement of parking regulations, integrate parking management with urban planning, and implementing parking management measures to alleviate congestion.

The urban majority in Africa do a great deal of walking, yet we do not fully understand the lived realities of the so-called captive walkers, who have no option but to walk. This study explores the everyday lived accounts of urban residents as they navigate the walking environment in two low-income neighbourhoods in Accra, Ghana’s capital. The study adopted a qualitative approach drawing on 2 focus group discussions, 60 interviews with residents in the Dome and Accra Newtown neighbourhoods in Accra, and 10 institutional interviews. The findings show that residents viewed walking as a means of enhancing social relations, health, and spatial awareness. Lived accounts show that walking is stressful and dangerous because of the design and behavioral barriers in the walking environment. While highlighting the value of community-level responses to walking barriers, this paper calls for a more nuanced understanding of the everyday lived experiences of walking, reconsidering walkability challenges as intricately linked to, not separate from, urban development challenges and engaging captive walker perspectives as the basis for driving equitable and inclusive principles in the agenda for sustainable urban mobilities in Africa and Global South generally.

To mitigate climate change and safeguard energy security, it is necessary to limit car dependence, reduce car weights, and shift to alternative car powertrains. This study therefore looked into the real-world specific energy consumption and (hbox {CO}_{{2}}) emissions of cars in the Netherlands. Next, it analyzed how sociodemographic and built environment variables influence energy-relevant car type choices with a multilevel discrete choice modeling framework. At a first stage, this framework considered the number of cars owned. Conditional on that decision, it simultaneously considered choices between different car fuel types and weight categories. The results showed that small, lower-income households with few male or older members in non-green (urban) environments were more likely to own light (efficient) vehicles. Remote households had a preference for light and diesel vehicles. In contrast, households with private parking tended to own heavy and electric vehicles. Finally, owning multiple cars was correlated with both non-urban living and heavy car preferences. The combined effect was a mild preference for energy efficient vehicles in urban areas. Previous studies that omitted vehicle energy efficiency thus slightly underestimated urban planning’s environmental impact. However, our results indicate that the built environment has a greater effect on travel energy use through the number of cars owned than through car specific energy consumption. The bias in the official vehicle energy data was also much larger than the total influence of the built environment on car specific energy consumption.

The radiation model is widely used in traffic demand forecasting. However, when applying the radiation model in the aviation field, it overestimates short-distance travel demand, does not consider flight capacity constraints, and cannot respond well to large-scale disruptions such as COVID-19. Based on the principle of the radiation model, this paper modifies the radiation model using the adjacency matrix of the airline network, along with the total passenger inflow and outflow for each city, flight capacity, and effective distance. The modified radiation model’s performance is verified using the 2018 and 2020 Chinese air passenger flow datasets under normal conditions and large-scale disruptions. The study compared the performance of the modified radiation model with the original radiation model and the opportunity priority selection model on an airline network that includes major cities. The results indicate that the modified radiation model is superior to the original radiation model and opportunity priority selection model in modeling airline networks. Additionally, the passenger travel distances provided by the modified radiation model are more accurate. The modified radiation model can better estimate air traffic demand in airline networks and withstand significant disruptions to airline network traffic.

Household travel surveys collect core datasets for modelling passenger travel demand. However, the decline in survey completion rate has become a concern in recent years. Among all components, the travel diaries are the most challenging part of CAWI travel surveys and suffer significant dropouts of participation. Therefore, an investigation is necessary to understand the influential factors contributing to participation dropouts while reporting their travel dairies and subsequent non-response bias on data quality. This study utilizes binary logit models to capture the relationship between respondents’ drop-off behaviours while filling out travel diaries, their socioeconomic characteristics and different travel diary designs. The study also develops a generalizable analysis framework to measure the impact of non-response bias on data quality. The analysis framework incorporates a trip generation model with microsimulation and bootstrapping techniques. The results show that a diary design with stable repetitions is preferred by respondents and results in less non-response bias in the final dataset. This study also proposes recommendations for future travel surveys.