Future Transportation

The various social, political, environmental, and economical mega-trends together with the rapid rise of digitalization are shaping cities worldwide including the way that citizens and products move within the urban environment. New mobility services are popping up which are showing the path toward more on-demand and personalized mobility patterns. The transformation of the urban mobility environment though constitutes a great challenge for policy-makers, as little is known about the impact of these trends on the city’s current mobility environment while the assessment of the future state of a mobility system can be considered a quite complex process taken its multi-parametric and multi-dimensional nature. This paper aims to simplify this process by presenting a coherent multi-actor consequence analysis framework as a tool for assessing future mobility scenarios which was developed in the framework of the H2020 SPROUT. This paper presents in detail the main components of this framework together with the list of key performance indicators used for assessing the performance in terms of sustainability of future mobility scenarios as well as indicative results from its use by the city of Padua. Full article

To support worker and driver safety, this study conducted a comprehensive literature review to identify methods of enhancing TMA visibility, improving work zone configurations, and ensuring worker safety. To increase TMA recognition, this study observed that the use of a 6-to-8-inch wide yellow and black inverted ‘V’ pattern of retroreflective chevron markings, sloped at a 45-degree angle downward in both directions from the upper center of a rear panel is effective in alerting drivers to work zones. This study also recommends applying amber and white warning LEDs, which flash in an asynchronous pattern at a 1 Hz frequency and are mounted against a solid-colored background for a 360-degree view visible at least 1500 feet from the work zone. In addition, a work zone vehicle configuration consisting of a lead, buffer, and advance warning truck with a buffer space between 100 and 150 ft is suggested to reduce the risk of lateral intrusions and TMA roll-ahead. In parallel, workers should wear high-visibility vests noticeable at a minimum distance of 1000 feet and headwear with at least 10 square inches of retroreflective material. Some intelligent transport systems are also suggested to enhance TMA recognition and potentially minimize work zone fatalities. Application of the recommended guidelines will potentially improve current practices and significantly reduce the occurrence of TMA crashes in construction and maintenance work zones. Full article

In this paper we assess the transit quality of service (QoS) from a user’s standpoint, using smart data. A number of bus lines with different characteristics, operating in the Metropolitan Area of Athens, were chosen as a case study. The data used were gathered by an Automatic Passenger Counting (APC) system. APC technologies provide exact temporalized passenger counting along the line for each service, thus assisting to better understand causalities of delays and avoid operational problems. By employing archived APC data from buses running on crosstown routes between 15 January 2019 and 15 April 2019 we conducted a statistical analysis to explore occupancies and assess QoS, including under a social distancing scenario. The passenger distribution along the stops, the bus’s occupancy level, the stops that are maximum occupancy points and their rate of occurrence and, lastly, the passenger’s average trip length during the day and the week are examined. Full article

Wyoming has one of the highest fatality rates and lowest enforcement rates in the U.S. Thus, this study was conducted to see if there is any link between various citation types on the equivalent property damage only (EPDO) crashes, while taking into account interaction terms between various crashes and citation characteristics. To achieve the objective, we disaggregated the citations data into their related types, while aggregating the crash dataset across each segment through the Eastern direction of the interstate 80 in Wyoming. The results highlighted that there are important relations between types of crashes and related citations. For instance, it was found that there are (1) significant interaction terms between driving-too-fast-for-condition citations and underride crashes, (2) total number of commercial citations and commercial motor vehicle (CMV) crashes, and (3) between seatbelt citations and seatbelt-related crashes, highlighting, possibly, that the performance of the highway patrol was adjusted based on the specific roadway concerns, or there is indeed a significant link between related citation and crash types. While conducting the model with no interaction term, the results of comparison highlighted that the model erroneously highlight positive associations between citation types and the EPDO crashes. This is one of the earliest studies that considered disaggregated citation data and aggregated them with the crash data to highlight the important relationship between the citations and crashes. Full article

Heavy-duty trucks (HDTs) are responsible for considerable fuel consumption and greenhouse gas emissions (GHG) in the road transportation sector due to their heavier weight, and significantly more miles travelled in comparison with other vehicles. Regarding the climate change mitigation policies, HDTs need to become zero-emission vehicles. One of the technological solutions in this sector is the battery electric truck (BET). This paper includes a systematic review on relevant studies in the field of BETs, including the following: (1) the technical, stakeholder, and customer aspects in terms of charging solutions to give a comprehensive insight into their technological advantages and disadvantages; (2) the total cost of ownership (TCO) for BETs and diesel trucks; and (3) a CO₂ life cycle assessment (LCA) from different technologies. Moreover, the result is formulated in the form of SWOT analysis to describe the strengths, weaknesses, opportunities, and threats of different charging technologies. Moreover, the different calculation methods of the total cost of ownership for the heavy-duty battery trucks and diesel trucks are compared. In addition, the CO₂ LCA is analyzed, and the different estimation methods of the CO₂ released in the environment are compared, which includes the CO₂ emissions during mobility operations and during the different manufacturing processes. Full article

This study examines the relationship between travel modes and the attitudes of residents and travelers around mass transit stations. The importance of this study was emphasized by considering that the attitudes toward residence could affect future travel and relocation considerations. In particular, the outbreak of COVID-19 may have a significant effect on their relationship. To investigate the direct and indirect effects before and during the COVID-19 pandemic, a moderated mediation model was used to test the hypothesis of this study by three-step approach analysis. The attitude toward residence was defined to test the hypothesis of the mediator, and the walking distance to the nearest mass transit station was employed to identify the level of the moderator. The results indicated that the attitude toward residence mediated the relationship between the attitude toward travel mode and travel mode behavior. The sensitivity of COVID-19 accurately reflects the various effects on travel mode. Moreover, multi-group analyses show that walking distance moderators have a direct effect on attitudes toward travel mode and travel mode behavior as well as the attitude toward residence. Full article

Over the last several decades, transportation scientists have made substantial progress in identifying and tackling transport-related problems by elaborating sophisticated policy instruments. Originally, the policy instruments were developed and designed to tackle inefficiencies caused by conventional (human-driven) vehicles. However, questions remain regarding transportation policies, especially pricing instruments, in the future. With the advent of fully autonomous vehicles (driverless or self-driving cars), many of potentially disruptive changes to our transportation system are projected to occur. This gives rise to the question of how to adapt the existing, well established, policy instruments to make them applicable to a world of self-driving cars. The present paper utilizes one of the most widely deployed, most important (in terms of tax revenue), and most effective (in terms of carbon dioxide mitigation) current price-based policy instruments in the transport sector (i.e., the energy tax) to show how one of the most innovative features associated with fully autonomous vehicles (i.e., driverless vehicle relocation) affects the optimal design of a transportation tax. We adopt a microeconomics optimization framework and analytically derive the optimal energy tax under the assumption that driverless vehicle relocation is possible. Our main finding is that in a world of self-driving cars, the energy tax (likewise, a second-best miles tax) as a price-based policy instrument becomes more difficult to evaluate. With the capability of fully autonomous vehicles to relocate without passengers inside, the (analytical) expression for the optimal energy tax becomes more complex, and its (numerical) determination becomes more difficult since the feature of driverless vehicle repositioning imposes counteracting welfare effects as a response to a tax change. Policymakers and researches are encouraged to take on the challenge of increasing complexity to tackle transport-related inefficiencies in the era of self-driving cars. Full article

In this study, we aimed to evaluate the performance of various machine learning (ML) classifiers to predict mode choice of movement-challenged persons (MCPs) based on data collected through a questionnaire survey of 384 respondents in Dhaka, Bangladesh. The mode choice set consisted of CNG-driven auto-rickshaw, bus, walking, motorized rickshaw, and non-motorized rickshaw, which was found as the most prominent mode used by MCPs. Age, sex, income, travel time, and supporting instrument (as an indicator of the level of disability) utilized by MCPs were explored as predictive variables. Results from the different split ratios with 10-fold cross-validation were compared to evaluate model outcomes. A split ratio of 60% demonstrates the optimum accuracy. It was found that Multi-nominal Logistic Regression (MNL), K-Nearest Neighbors (KNN), and Linear Discriminant Analysis (LDA) show higher accuracy for the split ratio of 60%. Overfitting of bus and walking as a travel mode was found as a source of classification error. Travel time was identified as the most important factor influencing the selection of walking, CNG, and rickshaw for MNL, KNN, and LDA. LDA and KNN depict the supporting instrument as a more important factor in mode choice than MNL. The selection of rickshaw as a mode follows a relatively normal probability distribution, while probability distribution is negatively skewed for the other three modes. Full article

The increasing need for dynamic in-flight adjustments of a trajectory allows the airport, air traffic control and the airline a high degree of flexibility in terms of in-flight execution. This concept enables numerous optimisation options to jointly meet the requirements of sustainable air transport to increase economic and ecological efficiency, as well as safety. One promising measure is to control the aircraft arrival rate to prevent over-demand in the approach sector around the airport. In so-called Long-Range Air Traffic Management, the arrival time of long-haul flights, in particular, is already controlled many hours before arrival. However, the control options and their effects on arrival time and fuel burn are heavily dependent on flight performance and the (hardly predictable) influence of the weather. In this study, we optimize the arrival time of 26 long-haul flights in the Asia-Pacific region with arrival at Changi Airport within a peak hour considering the arrival rate of medium-haul and short-haul flights. This control is done by speed adjustments and by choosing alternative routes. For the first time, we model each long-haul flight and its control options individually in real weather conditions. We found that speed adjustments should start three to four hours before arriving at the approach sector to maximize the fuel-saving potential of small deviations from the optimal cruising speed, considering the predictability of the arrival time under real weather conditions. Allowing the aircraft to additionally choose an alternative lateral route, different from the filed flight plan, both maximizes the potential for harmonization of the number of aircraft in the approach sector and minimizes the total fuel burn. Unlike speed adjustments, alternative routes changes are effective even during the last hour of the cruise phase. Full article

Having been widely acknowledged as enabling access to education, employment, leisure and social activities, transport choices are also the cause of many challenges cities face. Recognising that change is needed, planners and policymakers are considering alternative methods of planning and delivering transport. Mobility as a Service (or MaaS) is one such idea that has gained traction with academics and professionals alike. Hailed as the answer to integrating complex transport systems, MaaS has yet to be implemented at scale in urban transport systems due in part to the lack of an agreed conceptual definition, the top-down approach to implementing what is meant to be a more personalised method of accessing transport, and the lack of local promoters (in comparison to global corporations and lobbyists). This article reflects on the current barriers to defining MaaS, considers how a novel public engagement approach could be used to create local definitions that support citizen engagement, and suggests a route forward for future research. Full article

Despite fast technological advances, the worldwide adoption of electric vehicles (EVs) is still hampered mainly by charging time, efficiency, and lifespan. Lithium-ion batteries have become the primary source for EVs because of their high energy density and long lifetime. Currently, several methods intend to determine the health of lithium-ion batteries fast-charging protocols. Filling a gap in the literature, a clear classification of charging protocols is presented and investigated here. This paper categorizes fast-charging protocols into the power management protocol, which depends on a controllable current, voltage, and cell temperature, and the material aspects charging protocol, which is based on material physical modification and chemical structures of the lithium-ion battery. In addition, each of the charging protocols is further subdivided into more detailed methodologies and aspects. A full evaluation and comparison of the latest studies is proposed according to the underlying parameterization effort, the battery cell used, efficiency, cycle life, charging time, and increase in surface temperature of the battery. The pros and cons of each protocol are scrutinized to reveal possible research tracks concerning EV fast-charging protocols. Full article

White topping is a popular road rehabilitation technique that uses Portland cement concrete overlay on top of any existing bituminous pavement. However, this often results in additional cost and carbon emission escalations which complicates market useability of the product. The current study aims at comparing carbon emission and manufacturing cost of concrete topping mixes with three different fibre types. The study optimises the benefits and promotes the use of effective materials in sustainable road rehabilitation. Samples with polyolefin-twisted (F2) fibres indicated least carbon emission escalation while the sample with polypropylene (F3) exhibited least cost escalation with 0.75% and 7.17% from the control sample respectively. A multi-objective genetic optimisation study was conducted to identify the mix designs with least carbon emission and production cost escalations. Sensitivity analysis illustrated that transport distance is a critical contributing factor for production cost while carbon emission is highly sensitive to emission factors for transport and cement production. These results indicate the importance of considering locally available materials and clean energy for production processes. Future research can be focused on exploring the long-term environmental and economic benefits including the durability characteristics to benchmark the sustainable benefits of using waste fibre materials in the mix. Full article

COVID-19 pandemic impacted the behaviour of travellers. While worldwide, overall emissions decreased during the lockdown, shared mobility options may be perceived as less safe in a post-pandemic reality, leading to increased emissions due to expanded individual transportation. In particular, intercity trips entail numerous environmental impacts, such as emissions. The main objective of this paper is to assess how intercity corridors’ emissions vary when travel behaviour of the population changes following a pandemic. Based on a macroscopic modelling framework, the methodology consisted of three main phases: data collection, traffic modelling and emission modelling. Different scenarios related to the impact of the pandemic were developed, and their impacts were analysed using several key performance indicators related to CO₂ NO_x emissions and travel time. Findings suggest that reducing the average number of occupants per vehicle reduces emissions, which do not increase linearly with the number of vehicles. Compared with the baseline scenario (occupancy rate of 1.30), the most extreme scenario (occupancy rate of 1.00) may result in an increase in both CO₂ and NO_x emissions by approximately 30%. These results highlight the importance of making public transport and carpooling not only safe but also safe as perceived by users. Full article

Wyoming has one of the highest fatality rates, and a significantly lower rate of seatbelt use in the United States. Thus, this study was conducted with the objective to investigate contributory factors to the choice of drivers’ seatbelt use. Various environmental factors and drivers’ characteristics were considered as it is expected that they account for unseen factors that impact drivers’ choice of buckling up. Although the mixed model has been used extensively for studying the impacts of seatbelt use on the severity of crashes, not many studies have been conducted regarding factors contributing to the choice of seatbelt use itself. In this study, the standard logit model is extended to the mixed model to account for heterogeneity across drivers’ observations. In addition, the standard mixed model was extended to incorporate the random parameters’ heterogeneity in taste based on the means of other observed variables. The results highlighted that moving from the standard logit model to the mixed model, considering heterogeneity in tastes, results in a gain in the model fit, and also an adjustment for the model’s parameters’ estimates. The findings indicated that some of factors impacting the choice of wearing seatbelt include gender, road classification, weather condition, vehicle types, time of driving, vehicle registration and day of the week. Those factors are mainly related to unobserved factors impacting the drivers’ behaviors. For instance, drivers with particular characteristics are expected to own particular vehicle types or drive their vehicles under a particular weather condition. Full article

The way in which people choose to travel has changed throughout history and adaptations have taken place in order to provide the most convenient, efficient and cost-effective method(s) of transport possible. This research explores two trends—technological and socio-economic change—by discussing the effects of their application in the renewed drive to promote car clubs in Greater London through the introduction of new technologies and innovative ways in which a car can be used and hired, thus helping to generate new insights for car sharing. A mixed methods approach was used, combining secondary data analysis obtained from a car club member survey of 5898 people with in-depth, semi-structured interviews. Our findings show that there is an opportunity to utilise car clubs as a tool for facilitating a step change away from private vehicle ownership in the city. In addition, the results suggest that car club operators are seeking to deliver a mode of transport that is able to compete with private car ownership. In terms of policy implications, such findings would suggest that compromise is necessary, and an operator/authority partnership would offer the most effective way of delivering car clubs in a manner that benefits all Londoners. Full article

Transport sector models help provide strategic information for the future development of the transportation sector. Such long-term scenarios are typically challenged by uncertainties. Moreover, certain trends, such as the transition to zero-emission transportation systems and modal shifts, as well as connected, shared and autonomous vehicles, are already apparent today. Therefore, this paper investigates the impact of these trends on greenhouse gas emissions, as well as their implementation in transport sector modeling thus far. The investigations are structured into the four main parts of transport sector greenhouse gas emission calculation: activity, modal share, energy intensity and fuel carbon intensity. Our analysis of the related effects reveals their importance to the transportation sector of the future. Current models and scenarios widely consider trends such as the modal shift and electrification. However, other trends such as the sharing economy and automated driving are not commonly regarded in the context of transport sector modeling. The coupling of the different types of models and collaboration among researchers from the different fields is recommended for filling this gap. Full article

Nowadays, authorities of large cities in the world implement bus rapid transit (BRT) services to alleviate traffic problems caused by the significant development of urban areas. Therefore, a controller is required to control and dispatche buses in such BRT systems.. However, controllers are facing new challenges due to the inherent uncertainties of passenger parameters such as arrival times, demands, alighting fraction as well as running time of vehicles between stops. Such uncertainties may significantly increase the operational cost and the inefficiencies of BRT services. In this paper, we focus on the controller’s perspective and propose a stochastic mixed-integer nonlinear programming (MINLP) model for BRT scheduling to find the optimal departure time of buses under uncertainty. The objective function of the model consists of passenger waiting and traveling time and aims to minimize total time related to passengers at any stop. From the modeling perspective, we propose a new method to generate scenarios for the proposed stochastic MINLP model. Furthermore, from the computational point of view, we implement an outer approximation algorithm to solve the proposed stochastic MINLP model and demonstrate the merits of the proposed solution method in the numerical results. This paper accurately reflect the complexity of BRT scheduling problem and is the first study, to the best of our knowledge, that presents and solves a mixed-integer nonlinear programming model for BRT scheduling. Full article

Micromobility is an increasingly attractive option, particularly over short distances. Walking, biking, and other modes of transport, such as e-scooters, are gaining popularity. Furthermore, a trend is emerging to introduce appealing items onto the market that incorporate new/more sustainable materials to improve wellbeing. Significant research questions concern the understanding of emerging research needs and the environmental, social, and economic effects of sustainability in the micromobility transport system, specifically because of developing and implementing new products, boosting the safety and comfort of ergonomic personal mobility devices (PMDs), and assuring security and privacy while digitalization arises. Such research topics can raise policymakers’ and the public’s awareness while providing impactful information for decision-makers. This paper provides a literature review of the most recent research on micromobility-related topics. It uses scientific databases, a keywords list, and defined inclusion criteria to select data, analyze content, and perform a bibliometric analysis. The findings highlight the significance of using Life Cycle Assessment (LCA) tools together with other methodologies to aid in the evaluation of urban complexity. Finally, using a life cycle thinking (LCT) approach, we propose a framework for comprehensively integrating identified research needs. Full article

Transportation is one of the main enablers of development. It connects communities, allows the trade of goods among territories, and provides equitable access to public services. However, it is also one of the main causes of climate change, impacting directly and indirectly on human health. This raises the need for transportation infrastructure to be more sustainable so that it can enable more sustainable development. This paper investigates how sustainability in the transport sector can be conceptualized, assessed, and implemented. Definitions are proposed, indicators identified, existing methods reviewed, and three case studies presented. The Sustainable Asset Valuation (SAVi) method and resulting integrated simulation models are used to assess the multidimensional outcomes of conventional and sustainable transport investments. The cases of roads, public bicycle-sharing and bus rapid transport systems are discussed. These investments are assessed using an integrated cost–benefit analysis that goes beyond traditional assessments, considering the benefits and avoided costs of the externalities of a project in the social, environmental, and economic dimensions. The use of the method led to the conclusion that including externalities in a cost–benefit analysis is meaningful and can be relevant for assessing the economic viability of transport infrastructure projects. Full article