Future Transportation

This article investigates if the impact of weather conditions on mode choice (walking, riding a bike, driving a car, and using public transport) differs across spatial areas. For this purpose, a survey-based data set with more than 500,000 trips in Germany was enriched with weather conditions prevailing at the closest weather station to the point of departure at the moment of the start of the trip. In addition, the points of departure of each trip were classified into seven different spatial areas. The analysis relied on separate multinomial logit models carried out for each spatial area with mode choice as the dependent variable. The independent variables consisted of non-weather-related factors such as sex, age, car availability, level of education, etc., and various weather-related variables such as air temperature, amount of precipitation, and wind speed. The results show that weather conditions have a rather marginal impact on mode choice, with the exception of riding a bike, which constitutes the mode of transport that is most affected by weather conditions in all spatial areas. However, the impacts tend to be smaller in densely populated urban metropolises than in peripheral, rural areas. In particular, precipitation and wind speed do not appear to affect cyclists in metropolitan areas as much as in peripheral, rural regions. Full article

Climate change has a detrimental impact on permafrost soil in cold regions, resulting in the thawing of permafrost and causing instability and security issues in infrastructure, as well as settlement problems in pavement engineering. To address these challenges, concrete pipe pile foundations have emerged as a viable solution for reinforcing the subgrade and mitigating settlement in isolated permafrost areas. However, the effectiveness of these foundations depends greatly on the mechanical properties of the interface between the permafrost soil and the pipe, which are strongly influenced by varying thawing conditions. While previous studies have primarily focused on the interface under frozen conditions, this paper specifically investigates the interface under thawing conditions. In this study, direct shear tests were conducted to examine the damage characteristics and shear mechanical properties of the soil-pile interface with a water content of 26% at temperatures of −3 °C, −2 °C, −1 °C, −0.5 °C, and 8 °C. The influence of different degrees of melting on the stress–strain characteristics of the soil-pile interface was also analyzed. The findings reveal that as the temperature increases, the shear strength of the interface decreases. The shear stress-displacement curve of the soil-pile interface in the thawing state exhibits a strain-softening trend and can be divided into three stages: the pre-peak shear stress growth stage, the post-peak shear stress steep drop stage, and the post-peak shear stress reconstruction stage. In contrast, the stress curve in the thawed state demonstrates a strain-hardening trend. The study further highlights that violent phase changes in the ice crystal structure have a significant impact on the peak freezing strength and residual freezing strength at the soil-pile interface, with these strengths decreasing as the temperature rises. Additionally, the cohesion and internal friction angle at the soil-pile interface decrease with increasing temperature. It can be concluded that the mechanical strength of the soil-pile interface, crucial for subgrade reinforcement in permafrost areas within transportation engineering, is greatly influenced by temperature-induced changes in the ice crystal structure. Full article

Connected and Automated Vehicles (CAVs) offer the potential to improve roadway capacity and safety. Thus, improving road infrastructure condition could be prioritized to eliminate further degradation of the transportation infrastructure. In order to foster the adoption of CAVs, incentives can be used; but there is a need to identify what type of incentive would be most effective. To identify effective incentive types, this study uses electric vehicles (EV) and hybrid vehicles as a surrogate to CAVs because of the similarities in obstacles faced for wider adoption. This study then provides some recommendations by examining incentives offered in 15 different countries and by reviewing the literature on the effectiveness of incentive types. Full article

Shared autonomous vehicles (SAVs) aspire to change not only vehicles but also the way people and goods move in urban areas. However, the promotion of such services, that is, whether travelers are willing to share their trips with other service users, is still a challenge. This study aims to examine the contributory factors that influence the willingness of individuals to use shared autonomous vehicles by simultaneously identifying the differences in terms of preferences with conventional competitive transport modes, namely, private cars and public transport. A stated preference experiment combined with perception ratings was designed and conducted in Athens, Greece. Based on the collected responses, a multinomial logit model was estimated. The results show that the flexibility of SAVs and, particularly, the possibility of performing door-to-door trips has a serious added value that travelers are willing to pay. Compared with public transport, additional waiting time does not increase the disutility. Furthermore, people who belong to high-education and -income groups expressed a higher willingness to use SAVs and socialize while traveling. The familiarity of each potential user with technology is a necessary precondition. Lastly, it is confirmed that environmentally conscious people are more positive about using these new services. Full article

This review paper examines the appropriateness of a hyperloop line between Mumbai and Pune in India, examining, in particular, its potential economic implications and impact on people. This assessment builds on an earlier in-depth examination by the authors of the key urban and transport planning, technical, environmental, economic and human factors surrounding the hyperloop technology. The current detailed analysis of hyperloop’s expected implications in the Mumbai to Pune corridor is based upon use of a wide variety of existing indicative data from many sources, which are sufficient to provide a very broad “first-step” reality testing of hyperloop’s suitability to India. It could be argued that this is precisely the kind of analysis that should have been conducted, or at least made public, prior to committing to hyperloop in India. The paper highlights many negatives concerning hyperloop’s construction and operation, including a very high capital cost compared to other needed urban transport infrastructure projects in India, a potential lack of patronage due to a range of factors and its potentially exclusive upper income patronage cohort. It is concluded that rather than making a costly mistake, India should address current urban mobility challenges and needs such as bus rapid transit (BRT) and metros in its innumerable cities, whose construction costs are vastly lower than the expected cost of a single hyperloop line. Technology, such as the hyperloop, would need time to mature and gain operational experience. Should any corridor be found suitable, there would still need to be a thorough, detailed benefit–cost analysis together with a dedicated examination of the technology’s broader urban planning implications and less tangible factors. Setting aside the ultimate worthiness of hyperloops, India would need to at least achieve certain preconditions before proposing or pursuing such systems in the country. Full article

Climate protection goals in transportation can only be achieved with a worldwide change in mobility behavior that is supported by technological progress and changes in vehicle concepts. One contribution to reducing greenhouse gas emissions may be using small and light electric vehicles (LEVs) instead of cars. LEVs have a favorable ratio of vehicle weight to payload and the efficiency of electric drives contributes to environmental sustainability. As with full-sized electrically powered cars, emissions from combustion processes are eliminated. Going beyond that, the traction batteries in LEVs can be considerably smaller, thereby reducing the consumption of critical raw materials and lowering production-related greenhouse gas emissions. Against this background, we present the results of a study which aimed to determine what proportion of current passenger car trips in Germany could, in theoretical terms, be covered by LEVs. Our estimation of the substitution potential of LEVs for car trips is based on the 2017 Mobility in Germany (MiD) survey, a national household travel survey (NHTS) containing the data of 960,619 trips. Many different types of vehicles, ranging from e-scooters, cargo bikes, and pedelecs to three- and four-wheeled light electric vehicles, are considered. The results show that up to 76% of car trips and 50% of car mileage could theoretically be substituted by LEVs. The results are further analyzed to determine for which trip purposes and age groups the greatest substitution potential exists. Based on the results, we discuss ways for supporting the realization of this potential as well as factors that determine whether the theoretically calculated potential can be realized. Full article

Mobility management is a regulatory framework designed to streamline systematic mobility and mitigate energy, environmental and economic impacts. In this work, we propose a flexible methodology for evaluating the sustainability of home-to-work travel, providing a comprehensive and detailed ex post cost–benefit assessment. Specifically, we analyzed the effectiveness of the shuttle service operating in the ENEA “Casaccia” Research Centre in pre-pandemic times. Initially, we conducted an online survey to collect data with the aim of characterizing the travel behavior of the staff and reconstructing the multi-modal individual mobility patterns. Over 70% of the recipients, which amounted to about 950 individuals, completed the survey. Subsequently, we studied two alternative scenarios—with and without the shuttle service—comparing their total mileage, energy consumption, and pollutant emissions and performing an economic analysis. Our findings suggest that operating the service has a significant impact on air pollutants and greenhouse gas emissions, with reductions of 97% for volatile organic compounds, 72% for particulate matter, and 60% for carbon dioxide. Moreover, the cost–benefit analysis reveals that both users and the community reaped benefits from the provision of the collective service. These benefits are estimated to be almost EUR 1.35 M per year. Full article

This paper presents a comprehensive review of centrality measures and their usefulness in transportation networks in the face of climate change adaptation. The focus is on understanding the importance of transportation nodes in the event of extreme weather events and climate-related disasters that may render them inoperable. The paper argues that if critical nodes can be identified, they can be better protected, while resources can be allocated to ensure their functioning in the event of such events. The paper assesses 17 centrality measures, including degree, closeness, betweenness, eigenvector, and Katz, and evaluates their usefulness and usability in transportation networks. The review highlights the need to reformulate these measures to take into account traffic- and transport-related parameters and variables. Without this reformulation, centrality measures only reveal node importance in a topological or structural way and fail to capture the true significance of the nodes in a transportation network. The reformulation enables the centrality measures to be properly applied in a transportation network and to expose the significance of their elements. This work has important implications for transportation planners and policy-makers in ensuring the resilience of critical transportation infrastructure in the face of climate-related disasters. Full article

One of the ways to address the modern traffic-related problems is to encourage people to use sustainable travel modes more regularly. Transportation planners need to find the factors that affect people’s opinions toward using these modes. In this study, we investigated these factors using a case study of a developing country by distributing an online survey among the students of four universities in Tehran. The number of complete responses received was 134 from SUT, 63 for UT, 31 from AUT, and 204 from IUST, summing up to 432 responses. A binomial logistic regression model was used to find the paramount factors affecting the selection of cycling and public transportation. Our model found five and four statistically significant factors affecting preferences toward using bicycle and public transport, respectively. Several novel outcomes resulted from our study. First, expressing prestige to others resulted in the reduction of the preference of students toward cycling by 80%. Second, while a high number of the respondents are not currently using bikes to commute, a noticeable number of them are amongst the ones that will cycle in their daily commutes in an ideal condition. Third, in Iran, a religious approach is present in the society, which results in lower rates of public transport usage among females. Finally, while long commuting distance is the main barrier to cycling, travel time plays a bigger role in the preferences toward using public transportation. In the end, some practical solutions are suggested to encourage the usage of these modes. They include providing safe bicycle lanes and more space in the public transportation systems. Full article

This paper presents a two-stage fuzzy-logic application based on the Mamdani inference method to classify the observed road traffic conditions. It was tested using real data extracted from the Padua–Venice motorway in Italy, which contains a dense monitoring network that provides continuous measurements of flow, occupancy, and speed. The data collected indicate that the traffic flow characteristics of the road network are highly perturbed in oversaturated conditions, suggesting that a fuzzy approach might be more convenient than a deterministic one. Furthermore, since drivers have a vague notion of the traffic state, the fuzzy method seems more appropriate than the deterministic one for providing drivers with qualitative information about current traffic conditions. In the proposed method, the traffic states are analysed for each road section by relating them to average speed values modelled with fuzzy rules. An application using real data was carried out in Simulink MATLAB. The empirical results show that the proposed study performs well in estimation and classification. Full article

Current urban mobility systems in Europe, characterized by high car mobility shares, have negative environmental and health impacts but struggle to mitigate these for fear of sacrificing accessibility. Ironically, before the car mobility transition (in the 1950s and 1960s in Western countries and the 1990s in Eastern Europe), most cities were accessible by walking, cycling, public transport, and by the few cars there were. Through a longitudinal case study of a medium-sized urban area in Clermont-Ferrand, France (1950–2022), this paper explores the potential to ‘de-transition’, i.e., to reverse the urban transition process towards ‘accessible, low-car cities’ by reshaping infrastructures to constrain car use whilst accommodating walking, cycling, and public transport. We answer the following questions: To what extent can cities reverse the urban car mobility transition? How could such a process be further encouraged? Our analysis adopts a social practices perspective and uses a mixed-methods approach by combining semi-structured interviews, a survey, and a document analysis. On the one hand, our findings highlight the difficulty of an urban modality shift to car alternatives: (1) the limited reach of public transformation networks (in Clermont-Ferrand, the tramline); (2) the fact that many feel unsafe or assume they need excellent health conditions to cycle, which is associated with leisure and sports; and (3) strong convictions concerning the usefulness of vehicle ownership, which is believed to maximise comfort. On the other hand, based on a historic analysis, we offer practical recommendations to de-transition to low-car urban areas: (1) the creation of an extensive regional tramway network; (2) the development of a full cycling network; and (3) the promotion of an extensive car-free city centre. Full article

The deployment of autonomous shuttles (ASs) holds health and safety benefits for people with and without disabilities. Transportation is critical in helping people with disabilities (PWDs) access health care, services, and jobs, but the current transportation system has not afforded them ubiquitous access. To understand the acceptance of ASs, we (1) quantified PWDs’ (N = 42) perceptions before and after riding in an AS (Level 4) and (2) developed a model of facilitators and barriers from 143 participants. For Objective 1, after riding in the AS, PWDs (n = 42) expressed increased Intention to Use (p < 0.001) and Acceptance (p < 0.001), and decreased Perceived Barriers (p < 0.001), compared with baseline. For Objective 2, four multiple linear regression models were conducted to predict the outcomes for Intention to Use, Perceived Barriers, Well-being, and Acceptance among all participants (N = 143). The results indicated that optimism and ease of use negatively predicted Perceived Barriers and positively predicted Intention to Use, Well-being, and Acceptance. Driving status (i.e., active driver) negatively predicted Intention to Use, Well-being, and Acceptance. Predictors of user Acceptance included optimism, perceived ease of use, driver status, and race/ethnicity—with 30.7% of the variance in Acceptance explained. We also recommended deployment strategies to project stakeholders. Full article

In recent years, the maintenance of multicomponent systems has been discussed in many papers. The aim of these studies is to use the maintenance duration of one component for the maintenance of other components to minimize the total maintenance cost of the system. The complexity of the maintenance of this kind of system is due to its structure and its large number of components. The present paper suggests a grouped maintenance policy for multicomponent systems in a finite planning horizon based on the systemic inspection feedback data. The system considered is periodically inspected. Then, the collected data are triply censored (left, right, and interval censored). The proposed grouped maintenance strategy starts by clustering the components into g clusters according to their degradation model. Then, an expectation minimization algorithm is applied to correct the censorship in the data and to associate a Weibull distribution with each cluster. The proposed grouped maintenance strategy begins by specifying an individual maintenance plan for each cluster by identifying an optimal replacement path. Then, this step is followed by finding an optimal grouping strategy using a genetic algorithm. The aim is to identify a point in time when the components can be maintained simultaneously. To illustrate the proposed strategy, the grouped maintenance policy is applied to the feedback data of the road markings of French National Road 4 (NR4) connecting Paris and Strasbourg. Full article

The COVID-19 pandemic caused a significant shift towards teleworking, resulting in changes in travel patterns. The relationship between teleworking and individual travel behavior is crucial for transportation planning and policymaking. Thereby, this article investigates the relationships between teleworking, COVID-19, and mobility patterns in Brazil during two different periods of the COVID-19 pandemic. Given the exceptional nature of recent events, it is crucial to conduct studies related to teleworking during the pandemic crisis to contribute relevant information and evidence to the literature on this phenomenon. Such research has the potential to provide new insights and perspectives that enhance our understanding of the challenges and opportunities associated with teleworking. Two different approaches were used in the methodological procedure. The first approach used exploratory analysis to study public aggregated data related to the beginning of the pandemic, followed by a cluster analysis and a multinomial logit model. The second approach, relative to a longer relaxation period of sanitary/health measures, collected disaggregated self-reported data using an online survey, which were analyzed through non-parametric tests. The results show a strong relationship between the teleworking regime and the frequency of trips, especially for work purposes. It also highlights the influence of economic development and the region of Brazil in the kind of work regime. The continuation of studies, such as this one, in current periods is important for analyzing possible impacts, such as the reduction in congestion, vehicle emissions, and to enable the use of teleworking as a demand management policy. Full article

Autonomous vehicles (AVs) have generated excitement for the future of transportation. Public transit agencies and companies (i.e., Uber) have begun developing shared autonomous transportation services. Most AV surveys focus on public opinion of perceived benefits and concerns of AVs but are not directly tied to field implementation of AVs. Experience and exposure to new technology affect adults’ perceptions and level of technology acceptance. As such, the Autonomous RideShare Services Survey (ARSSS) was developed to assess adults’ perceptions of AVs before and after being exposed to AVs. Face validity and content validity were established via focus groups and subject-matter experts (CVI = 0.95). Adults in the U.S. (N = 553) completed the ARSSS, and a subsample (N = 100) completed the survey again after two weeks. An exploratory and confirmatory factor analysis demonstrated that the ARSSS consists of three factors that can be used to reliably quantify users’ perceptions of AVs: (a) Intention to Use, Trust, and Safety (r = 0.85, p < 0.001, ICC = 0.99); (b) Potential Benefits (r = 0.70, p < 0.001, ICC = 0.97); and (c) Accessibility (r = 0.78, p < 0.001, ICC = 0.96) of AVs. These are key factors in predicting intention to use and acceptance of AVs. Results from the ARSSS may inform the acceptance among users of these AV technologies. Full article

Movement-specific vehicle classification and counting at traffic intersections is a crucial component of various traffic management activities. In this context, with recent advancements in computer-vision-based techniques, cameras have emerged as a reliable data source for extracting vehicular trajectories from traffic scenes. However, classifying these trajectories by movement type is quite challenging, as characteristics of motion trajectories obtained this way vary depending on camera calibrations. Although some existing methods have addressed such classification tasks with decent accuracies, the performance of these methods significantly relied on the manual specification of several regions of interest. In this study, we proposed an automated classification method for movement-specific classification (such as right-turn, left-turn and through movements) of vision-based vehicle trajectories. Our classification framework identifies different movement patterns observed in a traffic scene using an unsupervised hierarchical clustering technique. Thereafter, a similarity-based assignment strategy is adopted to assign incoming vehicle trajectories to identified movement groups. A new similarity measure was designed to overcome the inherent shortcomings of vision-based trajectories. Experimental results demonstrated the effectiveness of the proposed classification approach and its ability to adapt to different traffic scenarios without any manual intervention. Full article

Via the analysis of a set of parking and journey information for vehicles traveling to the parking site at the University of Brescia (Italy), we evaluated the possibility of managing the electric recharging of these vehicles, which are hypothesized to be electric. The paper investigates charging optimization techniques that can limit the charge power peaks and distribute the energy demand throughout the day. A cost assessment for an auxiliary system consisting of a photovoltaic energy source (PV) and battery stationary storage (BSS) is also carried out. Optimal power management at the station with PV and BSS is introduced, and the performance of two feedback controllers based on the optimized results is compared with that of a real-time management algorithm in the presence of randomness in charging requests and insolation. The results show that the BSS degradation cost plays a primary role in determining the strategy to adopt to minimize the operating expenditure of a charging station. Full article

Optimizing signal timing improves sustainability metrics (e.g., fuel consumption or “FC”). Historically, traffic agencies have retimed signal timing to improve mobility measures (e.g., delays). However, optimizing signals to reduce delays does not necessarily mitigate sustainability measures. Hence, this study introduces an approach that integrates a newly derived surrogate measure for FC, traffic microsimulation software, and a stochastic genetic algorithm. This approach optimizes signal timing to reduce the surrogate measure and reduce sustainability metrics. This study also evaluated the impact of heavy vehicles’ presence in a fleet on signal timing and FC savings. A 13-intersection arterial on Washington Street in the Chicago metro area served as a case study. Optimized signal timing delivered solutions that balanced both sustainability and mobility. The estimated excess FC savings ranged between 8 and 12% under moderate operating conditions, with no heavy vehicles, compared to the initial signal timing. The savings reached up to ~14% when many heavy vehicles existed on the side streets. Most of the improvements came without worsening traffic-mobility efficiency, which shows the possibility of a fair tradeoff between mobility and sustainability. All optimization scenarios showed that a slightly longer cycle length than the one implemented in the field is required to reduce FC. Full article

Traffic intersections throughout the United States combine fixed, semi-actuated, and fully actuated intersections. In the case of the semi-actuated and actuated intersections, uncertainties are considered in phase duration. These uncertainties are due to car waiting queues and pedestrian crossing. Intelligent transportation systems deployed in traffic infrastructure can communicate Signal and Phase Timing messages (SPaT) to vehicles approaching intersections. In the connected and automated vehicle ecosystem, the fuel savings potential has been explored. Prior studies have predominantly focused on fixed time control for the driver. However, in the case of actuated signals, there is a different and significant challenge due to the randomness caused by uncertainties. We have developed a predictive control using the SPaT information communicated from the actuated traffic intersections. The developed MPC-based algorithm was validated using model-based design platforms such as AMBER^®, Autonomie^®, MATLAB^®, and SIMULINK^®. It was observed that the proposed algorithm can save energy in a single phase, in multiple phase scenarios, and in compelled stopping at stop signs when employed considering communications. Full article