Future Transp., Volume 4, Issue 3 (September 2024) – 22 articles

Lane management strategies are vital for solving traffic congestion and improving transportation efficiency in metropolitan corridors. These corridors, which facilitate economic and social interactions by connecting major urban areas, face significant challenges such as congestion, environmental concerns, and the need for sustainable growth. Effective lane management involves techniques such as HOV lanes, HOT lanes, reversible lanes, and dynamic toll pricing, which have been implemented worldwide. This study addresses the questions ‘What are the benefits and limitations of lane management strategies in metropolitan corridors?’ and ‘When should decision-makers consider implementing lane management strategies in a metropolitan corridor?’ This paper aims to evaluate lane management strategies to increase the multimodal efficiency of metropolitan corridors. A systematic literature review of case studies reveals that while these strategies significantly reduce congestion and emissions, they also face road safety, compliance, and public resistance issues. In addition, gaps in existing research on metropolitan corridors and lane management will be identified, and areas for future research are proposed. The impacts of new societal trends and evolving urban planning concepts are examined. The study highlights the need for adaptive planning and innovative solutions. Full article

International research attention on evacuation issues has increased significantly following the human and natural disasters at the turn of the century, such as 9/11, Hurricane Katrina, Cyclones Idai and Kenneth, the Black Saturday forest fires and tsunamis in Japan. The main problem concerning when a disaster can occur involves studying the risk reduction. Risk, following all the theoretical and experimental studies, is determined by the product of three components: occurrence, vulnerability and exposure. Vulnerability can be improved over time through major infrastructure actions, but absolute security cannot be achieved. When the event will occur with certainty, only exposure remains to reduce the risk to people before the effect hits them. Exposure can be improved, under fixed conditions of occurrence and vulnerability, by improving evacuation. The main problem in terms of evacuating the population from an area is the available transport system, which must be used to its fullest. So, if the system is well managed, the evacuation improves (shorter times), meaning the exposure is reduced, and therefore, the risk is reduced. A key factor in the analysis of transport systems under emergency conditions is the behavior of the user, and therefore, the study of demand. This work identifies the main research lines that are useful for studying demand under exposure-related risk conditions. The classification of demand models that simulate evacuation conditions in relation to the effect on the transportation system is summarized. The contribution proposes a model for updating choice in relation to emergency conditions and utility. The contribution of emerging ICTs to actualization is formally introduced into the models. Intelligent technologies make it possible to improve user decisions, reducing exposure and therefore risk. The proposed model moves within the two approaches of the literature: it is an inter-period dynamic model with the probability expressed within the discrete choice theory; furthermore, it is a sequential dynamic model with the probability dependent on the previous choices. The contribution presents an example of application of the model, developing a transition matrix considering the case of choice updating under two extreme conditions. Full article

The transition of the vehicle fleet to incorporate AV will be a long and complex process. AVs will gradually form a larger and larger share of the fleet mix, offering opportunities and challenges for improved efficiency and safety. At any given point during this transition a portion of the AV fleet will be consuming roadway capacity while deadheading, which means operating without passengers. Should these unoccupied vehicles simply utilize the shortest paths to their next destination, they will contribute to congestion for the rest of the roadway users without providing any benefit to human passengers. There is an opportunity to develop routing strategies for deadheading AVs that mitigate or eliminate their contribution to congestion while still serving the mobility needs of AV owners or passengers. Some of the AV fleet will be privately owned, while some will be part of a shared AV fleet. In the former, some AVs will be owned by households that are lower-income and benefit from the ability to have fewer vehicles to serve the mobility needs of the household. In these cases, it is especially important that deadheading AVs can meet household mobility needs while also limiting the contribution to roadway congestion. The aim of this study is to develop and evaluate routing strategies for deadheading autonomous vehicles (AVs) that balance the reduction of roadway congestion and the mobility needs of households. By proposing and testing a bi-objective program, this study seeks to identify effective methodologies for routing unoccupied AVs in a manner that mitigates their negative impact on traffic while still fulfilling essential transportation requirements of the household. Three strategies are proposed to deploy AV deadheading methodology to route deadheading vehicles on longer paths, reducing congestion for occupied vehicles, while still meeting the trip-making needs of households. Case studies on two transportation networks are presented alongside their practical implications and computational requirements. Full article

Assessing road safety performance in various regions of a country is crucial for improving overall road safety conditions and reducing the global mortality rate. This study employs the data-envelopment-analysis-based Malmquist productivity index (DEA-MPI) to comprehensively assess the progress of road safety performance in different regions of Morocco over time. Using a dataset spanning from 2014 to 2022, which contains data on road accidents, fatalities, injuries, the number of vehicles, and road traffic, this article evaluates the efficiency evolution across Morocco’s twelve regions. The study results show that the improvement of Morocco’s road safety performance during the studied period is unsatisfying and far from reaching the objectives of the current road safety strategy, which aims to reduce the number of fatalities by 50% by 2026. Moreover, the Malmquist productivity index (MPI) approach, which decomposes total factor productivity change into efficiency and technical changes, revealed that neither component shows a consistent trend throughout the studied period. This indicates that performance progress over time is insufficient and falls short of expectations, underscoring the immediate need for both technical and managerial improvements to address the current road safety challenges effectively. Full article

With an increasing adoption of battery-electric bus (BEB) fleets, developing a reliable charging schedule is vital to a successful migration from their fossil fuel counterparts. In this paper, a simulated annealing (SA) implementation is developed for a charge scheduling framework for a fixed-schedule fleet of BEBs that utilizes a proportional battery dynamics model, accounts for multiple charger types, allows partial charging, and further considers the total energy consumed by the schedule as well as peak power use. Two generation mechanisms are implemented for the SA algorithm, denoted as the “quick” and “heuristic” implementations, respectively. The model validity is demonstrated by utilizing a set of routes sampled from the Utah Transit Authority (UTA) and comparing the results against two other models: the BPAP and the Qin-Modified. The results presented show that both SA techniques offer a means of generating operationally feasible schedules quickly while minimizing the cost of operation and considering battery health. Full article

The swap-body vehicle routing problem (SBVRP) represents a specialized extension of the traditional vehicle routing problem (VRP), incorporating additional practical complexities. Effective fuel consumption management and the scheduling of multiple vehicle trips are pivotal strategies for reducing costs and ensuring the sustainability of distribution systems. In response to the acceleration of urbanization, the rising demand for logistics, and the deteriorating living environment, we introduce an SBVRP considering fuel consumption and multiple trips to enable greener, cheaper, and more efficient delivery methods. To tackle the SBVRP, we propose a hybrid multi-population genetic algorithm enhanced with local search techniques to explore various areas of the search space. Computational experiments demonstrate the efficiency of the proposed method and the effectiveness of its components. The algorithm developed in this study provides an optimized solution to the VRP, focusing on achieving environmentally friendly, sustainable, and cost-effective transportation by reducing energy consumption and promoting the rational use of resources. Full article

Despite significant research efforts into wrong-way driving crashes, the fatality rate in the United States remains persistently high year after year. However, few studies have concentrated on how the driver’s familiarity with the road affects wrong-way driving. This study aims to examine if there is a difference in contributing factors to fatal wrong-way driving crashes by local and non-local drivers by utilizing Fatality Analysis Reporting System (FARS) data from 2016 to 2020. Descriptive statistics were first used to give insight into the data, and then the association rule mining method was applied to help uncover the hidden connections between contributing factors to wrong-way driving crashes for both local and non-local drivers. The findings indicated that several factors, including intoxicated drivers, an urban environment, and late-night hours from 12 A.M. to 6 A.M., play a significant role in causing local wrong-way driving crashes. On the other hand, non-lighted conditions in a rural setting significantly contributed to fatal wrong-way driving crashes by non-local drivers. Full article

Intersection safety has been traditionally evaluated using three to five years of crash data. Recent literature suggests that connected vehicle (CV)-derived hard braking (HB) events can provide a surrogate for crashes with only a few weeks or months of data collection. This study used CV trajectories to derive HB events. Then, the HB events were normalized as the ratio of HB events to sampled CV trajectories. The normalized HB ratios were evaluated and compared at 435 signalized intersections, roundabouts, and all-way stops in Indiana. The analysis showed that signalized intersections and roundabouts had the highest counts of HB events, and all-way stops had the highest HB ratios. Through movements at signalized intersections showed the lowest HB ratios, whereas left turns at all-way stops had the highest ratios. A density analysis of the geospatial occurrence of HB events concluded that they tend to occur closest to the intersection center at all-way stops, but are more evenly distributed at signalized intersections. Additionally, a speed analysis indicated that HB events at signalized intersection through movements tend to occur at higher speeds, roughly between 26 and 36 MPH, perhaps due to the driver reaction during the onset of yellow. The findings presented in this study provide transportation agencies with insights on the occurrence of normalized HB ratios at three different intersection types. The data provided in this paper provide a framework for agencies to use HB ratios to screen different types of intersections for further evaluation. Full article

Urban transport has evolved based on three main visions: automobility, multimodality, and accessibility. The first dominates North American cities; the second, European; the third, significantly discussed in the literature, is still in the early stages of practical development, with a few limited examples. Each of the first two visions has an aligned planning paradigm to support aspirational goals and future directions. But implementation has been disappointing, owing to the appearance of anomalies; that is, unanticipated and unexplained mismatches between the vision and the paradigms that refuse to be resolved. The attempts are self-defeating, and result, for example, in congestion and road accidents. A review of the literature with some new insights can shed light on the problems and the anomalies of these two visions. For the third vision, a new paradigm has been proposed based on accessibility and polycentric and multi-timed cities, promising new insights and breakthroughs in the way of thinking about transport and cities. Some practical examples of accessibility cities are presented with a focus on people, places, land use changes, telecommunications, transportation demand management (TDM), and public and non-motorized transport. Some minor anomalies are discussed. In conclusion, enhancing accessibility in cities is crucial for creating more inclusive and sustainable urban environments that are less dependent on cars, but this vision and this paradigm still require further development to be accepted and implemented. Full article

The rise in population density, vehicle ownership, and urban development has significantly influenced travel demand and altered travel patterns, leading to traffic congestion in rapidly growing urban centers such as Accra, Ghana. The traditional approach of expanding roadways to accommodate rising traffic is no longer environmentally sustainable. Instead, the emphasis has shifted toward travel demand management (TDM) strategies as a more sustainable solution. This study aimed to investigate a range of TDM strategies that can be adopted in Accra to improve traffic flow through the lenses of everyday road users. The study employed a questionnaire survey and a stratified sampling technique to gather data from 615 respondents for relative importance index (RII) ranking and Chi-square statistical analysis. The findings revealed that the topmost preferred strategies were mass transit improvements, walking and cycling improvements, and alternative work schedules. Notably, mass transit improvements emerged as the most preferred strategy. Conversely, strategies like efficient parking pricing, congestion pricing, and higher fuel and road taxes for private vehicles ranked lowest, garnering minimal preference. The study also revealed a statistically significant correlation between variables such as age, education level, marital status, income level, and mode of transportation and all the selected TDM preferences. However, no significant relationship was found between gender or car ownership and any of the selected TDM preferences. The study provides valuable insights into road users’ preferences for TDM strategies that can aid in planning future urban mobility systems to proactively manage travel demand, alleviate congestion, and promote sustainable transportation options for the city’s residents. Full article

Previously, we estimated the net change in energy use from ridehail services in Austin Texas. This estimate was based, in part, on assumptions regarding the number of rides involving two pooled parties and the distance drivers commuted into their service area to begin their driving day. The recent release of a year’s worth of Uber ridehail rides provided to California agencies, as well as recent surveys of driver commute behavior and the previous mode replaced by ridehail services, have enabled more accurate estimates of the net change in energy use from ridehail services statewide and in five regional markets. We find that the net reduction in energy use from more-efficient vehicles and pooled rides does not offset the additional increase in commute and between-ride deadhead kilometers and replacing more efficient modes with ridehail services. The net result is a 96% increase in statewide energy use (ranging from a 75% to a 123% increase in each region). Full article

(1) Introduction: Transportation logistics play a pivotal role in facilitating both individual mobility and supply chain operations on a global scale. However, conventional transportation systems have contributed significantly to urban congestion and environmental degradation. In response to these challenges, there is growing momentum to investigate the potential of renewable energy to power electric vehicles (EVs) and flying automobiles, aiming to reduce fossil fuel dependence and carbon emissions. (2) Objectives: By analyzing key drivers and opportunities for integrating flying vehicles into existing infrastructure through dynamic modeling, this study seeks to accelerate the transition to sustainable transportation. (3) Methodology: A mixed-method approach, combining literature review and causal loop diagram analysis, is employed to understand the factors influencing EV and flying car adoption. (4) Results: Findings highlight the significant potential of renewable energy in reducing emissions and reliance on fossil fuels through widespread EV and flying vehicle adoption. The major drivers and challenges in infrastructure, safety, and airspace management are also identified. In addition, this research emphasizes the importance of sustainable transportation in addressing urban congestion, pollution, and energy security. (5) Conclusions: By leveraging renewable energy and embracing technological advancements, a low-carbon future for transportation can be achieved, benefiting both the environment and society. Full article

The electrification of transport is a step towards the transition to efficient, cleaner, and low-carbon mobility, as it decreases negative environmental effects and greenhouse gas emissions. In many countries, the adoption and the deployment of electric vehicles was based on a combination of policy measures and incentives. To promote the uptake of electrification, it is important to understand consumers’ opinions about electric vehicles. The aim of the present research is to investigate the factors influencing EV purchase decisions in a city of Greece. The analysis of this paper was based on the data collected using a structured questionnaire, addressed to the active population of Thessaloniki, the second largest city in Greece. A small percentage of the respondents own an electric vehicle. Appropriate statistical analysis identified correlations between the intention to purchase an electric vehicle and a number of critical factors. Full article

This paper examined the accuracy of six installed LiDAR sensors at six different signalized intersections in Trois-Rivières City, Quebec, Canada. At each intersection, the crucial leading and following movements that cause vehicle–vehicle (V2V) and vehicle–pedestrian (V2P) conflicts were identified, and the LiDAR results were compared to crash reports recorded by police, insurance companies, and other reliable resources. Furthermore, the intersection crash rates were calculated based on the daily entering vehicle traffic and the frequency of crashes at each intersection. Convolutional Neural Networks (CNNs) were utilized over 970,000 V2V and V2P conflicts based on the post encroachment time (PET) and time-to-collision (TTC) safety assessment measures. Bayesian models were used to assess the relationships between different intersection characteristics and the occurrence of conflicts, providing insights into the factors influencing V2V and V2P conflict occurrences. Additionally, a developed image-processing algorithm was utilized to examine the conflicts’ trajectories. The intersections’ crash rates indicated that safety considerations should be implemented at intersections #3, #6, #4, #1, #5, and #2, respectively. Additionally, intersections #6, #4, and #3 were the intersections with the highest rates of vehicle–pedestrian conflicts. Analysis revealed the intricate nature of vehicle and pedestrian interactions, demonstrating the potential of LiDAR sensors in discerning conflict-prone areas at intersections. Full article

Airport areas generate significant air pollution from both air and surface traffic. Policy makers often address this by considering single contributions, either from rubber-tired vehicles or aircraft, leading to an underestimation of the non-considered-mode’s impact. Similarly, literature on airport pollution often focuses on specific case studies, evaluating either surface or air traffic. Understanding the overlap of these contributions requires calculation of emissions from both traffic modes. This raises two research questions: which is the major contributor, and what mitigation measures can be applied? This paper addresses these questions through two Italian case studies. In the first, we estimated emissions from passenger cars, buses, and aircraft in a medium-sized airport representative of similar facilities across Italy and Europe, calculating emissions using COPERT for surface modes and ICAO methodologies for each LTO cycle. Results showed that aircraft emissions were significantly higher than those from surface vehicles. To address this, the second case study examined four mitigation measures at take-off and landing at another Italian airport, recalculating emissions via the same methodologies. The paper details the methodology process, presents results, and discusses the management of air-operations’ effects at urban airports within local mobility policies and practice, all within the research goal of advancing knowledge farther afield. Full article

This study explores the role of local authorities in achieving net zero emissions in the context of the climate crisis, with a particular focus on the freight transport sector. The study identifies the challenges of decarbonising urban freight transport and highlights the need for planning frameworks to facilitate this transition. The authors examine freight innovation ecosystems and the various actors involved in designing public policies that incentivise the creation or enhancement of these ecosystems. Through a systematic literature review, bibliometric analysis, and content analysis, this study identifies a lack of connection between the literature on these topics. However, it also highlights the potential for lessons to be learned from successful incentive frameworks in the four clusters identified. The authors propose a comprehensive incentives framework that includes both direct and indirect incentives aimed at the ecosystem and the public sector, respectively, as well as city conditions that can facilitate systemic change. Overall, this study provides valuable insights for policymakers and stakeholders seeking to promote sustainable transport and achieve net zero emissions. Full article

Digital technologies are essential tools that enable traceability in supply chains. In low-income countries, traceability represents a challenge due to the complicated structure of supply chains and the involvement of multiple stakeholders. This research developed a framework for a digital traceability system (TS), using the Ethiopian coffee supply chain as a case study. A literature review was conducted to gain an in-depth understanding of state-of-the-art digital traceability technologies. A logistics audit was conducted to map the coffee supply chain in Ethiopia and evaluate the implementation level of traceability technologies. Although the implementation of traceability technologies in the Ethiopian coffee supply chain is low, the results revealed that the usage of traceability technologies improves downstream of the supply chain. The traceability framework developed in this study ranges from a paper-based TS to a fully digitalised TS. The implementation of a TS in the coffee supply chain of Ethiopia is met with several challenges such as affordability, limited awareness, resistance of certain stakeholders, infrastructure limitations, restricted accessibility of some technologies and insufficient policy frameworks. Stakeholders from low-income countries can use the framework developed in this study to adopt a TS for their supply chains in line with their needs and current digitalisation levels. Full article

Advances and cost reductions in Light Detection and Ranging (LiDAR) sensor technology have allowed for their implementation in detecting vehicles, cyclists, and pedestrians at signalized intersections. Most LiDAR use cases have focused on safety analyses using its high-fidelity tracking capabilities. This study presents a methodology to transform LiDAR data into localized, verified, and linear-referenced trajectories to derive Purdue Probe Diagrams (PPDs). The following four performance measures are then derived from the PPDs: arrivals on green (AOG), split failures (SF), downstream blockage (DSB), and control delay level of service (LOS). Noise is filtered for each detected vehicle by iteratively projecting each sample’s future location and keeping the subsequent sample that is close enough to the estimated destination. Then, a far side is defined for the analyzed intersection’s movement to linear reference sampled trajectories and to remove those that do not cross through that point. The technique is demonstrated by using over one hour of LiDAR data at an intersection in Utah to derive PPDs. Signal performance is then estimated from these PPDs. The results are compared to those obtained from comparable PPDs derived from connected vehicle (CV) trajectory data. The generated PPDs from both data sources are similar, with relatively modest differences of 1% AOG and a 1.39 s/veh control delay. Practitioners can use the presented methodology to estimate trajectory-based traffic signal performance measures from their deployed LiDAR sensors. The paper concludes by recommending that unfiltered LiDAR data are used for deriving PPDs and extending the detection zones to cover the largest observed queues to improve performance estimation reliability. Full article

Fully autonomous vehicles, once legally and technically feasible and widely available, have numerous advantages compared to human-driven vehicles, from greater availability and shorter travel times to lower negative environmental emissions and fewer accidents. This, combined with a usage-based form of payment, can massively increase the usage rate of vehicles without the need for high initial investments. This study explores the determinants affecting the willingness to adopt Autonomous Mobility as a Service (AMaaS) in Germany. Utilizing a mobile cross-sectional survey via Pollfish, 400 complete responses of German speakers aged 18 years or older in Germany were collected to assess influential factors. The survey data were analyzed using binary logistic regression analysis. Age, possession of a driving license, and the quality of public transport were identified as significant predictors. Younger people and driving license holders showed a higher willingness to use AMaaS, while low-quality public transport reduced their willingness to use it. This study concludes that targeted strategies for AMaaS implementation should consider these key demographic and infrastructural factors to maximize market penetration and acceptance in Germany. Full article

Integrating autonomous vehicles (AVs) into public roads presents profound implications for pedestrian safety and the broader acceptance of this emerging technology. This work examines the complex interactions between AVs and pedestrians, a dynamic influenced by the variability of pedestrian behaviors and the absence of traditional communication mechanisms, such as eye contact and gestures, commonly relied upon in human-driven scenarios. Given the nascent stage of AV deployment, this research addresses the challenges of evaluating AV−pedestrian interactions amid safety concerns and technological limitations. We review and synthesize global research on pedestrian behavior in the context of AV technology to track changes in pedestrians’ acceptance over time and identify the factors driving these shifts. Additionally, this review incorporates insights from transportation authorities to highlight potential safety issues and the need for innovative communication strategies that ensure safe interactions between pedestrians and AVs. By analyzing these factors, the research aims to contribute to the development of guidelines and communication protocols that enhance pedestrian safety and facilitate the integration of AVs into urban environments. Full article

In this study, we consider the introduction of new mobility services and technologies into the megacity of Beijing, China, as per developed strategy and action plans, in order to investigate their potential contribution to sustainable mobility. This includes population relocation (decentralization), the construction of new rail lines, the introduction of shared bike services as a feeder to subway stations, the electrification of passenger vehicles and the adoption of automated and shared vehicles. The well-established, system dynamics-based MARS model is adapted to Beijing and further improved via the inclusion of these new services, technologies and policies. We find that decentralization can have a profound effect on overall sustainability if not considered in conjunction with other policies and that new rail lines and shared bikes may only have benefits in specific zones. Shared and automated vehicles could increase VKT by 60% and reduce active and public transport trips by a quarter. As such, nuanced integrated policy approaches will be required that are similar to those currently in place, such as imposed car shedding and taxi fleet control. Full article

This research germinates from the statement that cities need to solve the impacts caused by freight transport to improve their sustainability by implementing a set of city logistic measures. Urban freight distribution through environmentally friendly vehicle measures is one of the main sustainable actions being implemented worldwide, with a significant potential to reduce the congestion and pollution levels according to the assessment performed around the world. In this context, this paper aims to explore the use of railways for urban freight transport and then focuses on the potential of shifting from a road to railway system, which uses an advanced demand modelling framework specified and calibrated according to the results of surveys carried out in the study area. Subsequently, the potential benefits of introducing this urban freight transport through the metro system in Rome (Italy) are investigated, showing significant positive effects, both in terms of operational and external costs. Full article