Future Transportation

Yaoundé, the capital of Cameroon, is one of the cities in the country most affected by road traffic crashes. Despite the measures taken by authorities, the human factor remains a major cause of these crashes. This study aimed to evaluate the measures taken to reduce the risk-taking behaviors of collective taxi drivers in Yaoundé. A survey of 144 collective taxi drivers was conducted to gather information on their driving habits, adherence to, and perceived effects of safety regulations. The study revealed the following prevalence of risky driving behaviors among collective taxi drivers: 41.33% for impaired driving; 67% for speeding, 62% for disobeying traffic lights, 68.86% for distraction; and 67% for risky maneuvering on the road. Significant associations were found between risk perceptions and involvement in risky driving behaviors. Associations were also established between the frequency of police inspections and involvement in risky behaviors, between the participation in training programs on safety issues and using poorly maintained vehicles, and between the frequency of awareness campaigns and poor maneuvering on the road. To address these issues, it is essential to strengthen preventive measures on risk factors, raise awareness on a large scale and on a regular basis, and strictly enforce the existing regulations. Full article

This paper proposes the development of a smart traffic light prototype based on vehicular traffic flow measurement in the stretch between two avenues in the city of Limeira, SP, Brazil, focusing on the stretch towards UNICAMP’s School of Technology. To this end, we initially developed a Python code using the OpenCV library in order to detect and count vehicles. With the counting in operation, programming logic was inserted, aiming at preparing traffic light timers based on vehicular traffic. Finally, the traffic lights were added to display video via a code change to show the ongoing color changes, also obtaining a code for identifying vehicles and flow, in addition to the virtual traffic light system itself in the system. Vehicle counting accuracy was 75% for large vehicles, 90% for passenger cars, and 100% for motorcycles. The simulation of a smart traffic light implementation worked satisfactorily according to the post-processing of the video recorded for validation. Full article

This article investigates viable solutions to implement an Urban Air Mobility network in Milan, Italy, and analyzes its influence on the airspace capacity. The network comprises eight vertiports for passenger transport among two main airports in the area and the city using electric vertical take-off and landing aircraft (eVTOLs). A Fast-Time Simulation (FTS) model with the software AirTOp (Air Traffic Optimization) allowed the evaluation of the ideal capacity of the network by varying two configurations, which differ from each other in terms of the number of Final Approach and Takeoff areas (FATOs). The results show how it is possible to reach high hourly capacities (in the order of one hundred), thus allowing the use of the service for about 4% of the total passengers passing through the two airports during the reference day chosen for this study. However, the results are ideal due to the strong idealism of the system, which overlooks several factors, and they should be considered as the maximum limit that can be obtained. Despite this, the method presented in this article can also be adapted for other urban areas with high population densities. In addition, the use of a simulation tool of this type allows, in addition to a numerical analysis, a qualitative analysis of the network behavior in terms of traffic, thus highlighting the criticalities of the proposed systems. Full article

This paper explores the management of digitalization projects within the railway industry. It aims to increase and understand the opportunities presented by digitalization and automation in rail operations. Employing a scoping review methodology, this research investigates the execution of European Rail Traffic Management System (ERTMS), remote train control (RTC), and automatic train operation (ATO) projects spanning from 2005 to 2023, with a particular emphasis on metro automation, the remote control of freight and passenger trains, fully automated trains, and highly assisted driving. The refined selection process yielded 30 papers. The analysis of the retrieved papers identified managerial issues, with stakeholder management, change management, and organizational management emerging as recurring themes. Despite the increasing trend in publications, the limited representation managerial issues in ERTMS, RTC, and ATO projects in scientific research persists, with implications for the industry’s advancement. This research sheds light on the critical intersection of change management and digitalization within the railway industry by showing the impact of ERTMS, RTC, and ATO on organizational and scope dynamics. The need for human-centered systems is highlighted, showing the necessity of involving every echelon of the organization in the change management process. These findings provide insights for practitioners, researchers, and policymakers, emphasizing the need for understanding and addressing managerial aspects for successful and sustainable digitalization implementations. Full article

Capturing the value infrastructure investments add to the residential market is a longstanding policy to defray their expense. Unfortunately, estimates of the added value of infrastructure, generally, and estimates of the added value of walkability, specifically, are scarce. Novel, multiscale models free independent variables to manifest simultaneously at different scales of analysis to greatly improve specifications to precisely estimate walkability valuation. Results from analysis of years of transactions within walking distance of heavy rail stations suggest that walkability adds value available for capture locally, not systemically. Stakeholders confront myriad problems to replicate the accessibility characteristics shown to add value given the distinct cluster where walkability adds value available for capture in a heavy rail system. Full article

The study on individual mobility patterns supports our better understanding of spatiotemporal characteristics of people’s travel behavior and social activities. The mobile phone GPS data are advantageous due to the large size of their data coverage. This paper aims to identify individual activity anchor places and to analyze related patterns based on the GPS data collected from thousands of mobile phone users over four months in Greater Paris, France. We propose a method to refine the identification of home and secondary activities. Based on this, the mobility spatial characteristics are aggregated by applying a three-stage clustering method. As a consequence, the clusters of activity types, the daily mobility patterns (day types), and the user groups with similar daily mobility patterns are obtained stage by stage. This allows us to analyze the obtained clusters in a cascading maneuver by three different levels: activity level, day level, and individual level. Inversely, the mobility characteristics per user group are interpreted with respect to the interpretation of day types and then activity types. From the interpretable clusters, it is facilitated for us to find the daily mobility differences by user groups across weekdays and weekends, transport modes, as well as the mobility variability over the study period. Full article

Many transportation agencies have deployed pan–tilt–zoom (PTZ) closed-circuit television (CCTV) cameras to monitor roadway conditions and coordinate traffic incident management (TIM), particularly in urbanized areas. Pre-programmed “presets” provide the ability to rapidly position a camera on regions of highways. However, camera views occasionally develop systematic deviations from their original presets due to a variety of factors, such as camera change-outs, routine maintenance, drive belt slippage, bracket movements, and even minor vehicle crashes into the camera support structures. Scheduled manual calibration is one way to systematically eliminate these positioning problems, but it is more desirable to develop automated techniques to detect and alert agencies of potential drift. This is particularly useful for agencies with large camera networks, often numbering in the 1000’s. This paper proposes a methodology using the mean Structured Similarity Index Measure (SSIM) to compare images for a current observation to a stored original image with identical PTZ coordinates. Analyzing images using the mean SSIM generates a single value, which is then aggregated every week to generate potential drift alerts. This methodology was applied to 2200 images from 49 cameras over a 12-month period, which generated less than 30 alerts that required manual validation to determine the confirmed drift detection rate. Approximately 57% of those alerts were confirmed to be camera drift. This paper concludes with the limitations of the methodology and future research opportunities to possibly increase alert accuracy in an active deployment. Full article

This paper investigates a practical last-mile delivery scenario where a fleet of trucks replenishes autonomous mobile parcel lockers (AMPLs) in an urban setting. The lockers move along specified paths within restricted zones to reach customers’ locations. Ensuring seamless coordination between trucks and AMPLs requires the identification of suitable locations to exchange empty or loaded modular lockers. We first introduce a mixed-integer linear programming (MILP) formulation for the investigated problem. The proposed formulation establishes the basis for optimizing meeting point selection and routing decisions. Additionally, the study introduces a cluster-based simulated annealing (CSA) algorithm tailored for addressing larger-scale instances of the studied problem. The CSA algorithm incorporates the K-means clustering method with specialized operators rooted in an extensive neighborhood search, aiming to improve the effectiveness of solution discovery. We generated a new set of benchmark instances to assess the MILP formulation’s efficiency and the proposed metaheuristic algorithm and conducted comprehensive numerical experiments. Full article

Despite the growing adoption of Mobility as a Service (MaaS) in urban transportation systems, standard monitoring methods for evaluating its impact and effectiveness still need to be developed. This study proposes a quantitative state of MaaS analysis based on mobility market indicators and macroeconomic metrics to generate a MaaS Status Index (MSI). The intention is to introduce a standardised quantitative methodology for systematically assessing and comparing the state of MaaS in urban mobility systems. The MSI aims to quantitatively capture the economic, social, technological, and infrastructural conditions relevant to MaaS implementation. The methodology includes four steps: identifying relevant mobility markets, defining mobility market metrics, integrating macroeconomic metrics, and deriving the MSI formula. We apply the MSI methodology to the Austrian mobility market as a case study, demonstrating its practicality in assessing MaaS readiness and highlighting specific challenges and opportunities within the Austrian mobility system. The analysis covers the present (2017–2022) and the projected future (2023–2028). The findings indicate that the proposed MSI is an effective tool for evaluating the readiness of MaaS implementation. Full article

Urban pollution awareness is a subject of widespread debate, particularly regarding the role of future urban transportation. In recent years, local policymakers and private operators have implemented various measures to address the negative impacts of transportation, including promoting micro-shared mobility services. Our research investigates the factors influencing citizens’ decisions to use these services, focusing on e-bike sharing and e-scooter sharing. We collected data on individual mobility patterns in Italian cities and administered hypothetical choice tasks to examine revealed and stated preferences. Our findings highlight the most influential factors guiding users’ decisions and identify the preferred sharing option between e-bikes and e-scooters. The implications of our results could provide valuable insights for local regulators and shared mobility operators in designing effective and sustainable future transportation policies. Full article

The innovative trend of “as a service” due to digital development and the rise of issues such as air pollution and traffic congestion led to the emergence of Mobility as a Service (MaaS) in the transportation sector. Companies and governments are experimenting to create a sustainable and efficient transportation future with MaaS. However, MaaS realization and business success from MaaS are still in their growing phase, making this study particularly relevant and timely. This study aims to identify the attributes of users’ selection of integrated mobility app services and the MaaS attributes that affect the behavioral intention to use through the mediation of perceived usefulness and perceived ease of use. This study marked four selection attributes—habit-congruence, information accuracy, relative advantage on efficiency, and IT system quality—for the integrated mobility app service, and 315 actual users of integrated mobility apps in Republic of Korea were sampled and analyzed. In terms of influence, information accuracy, relative advantage on efficiency, and habit-congruence significantly impacted perceived usefulness, in which habit-congruence had the most significant impact on perceived ease of use. In addition, habit-congruence and information accuracy were found to positively affect the behavioral intention to use, mediated by perceived usefulness and perceived ease. We also found that IT system quality was not a user selection attribute where this study was conducted. By providing empirical findings, this study can give management guidelines to companies and researchers in developing integrated mobility app service strategies to increase the number of users and maintain long-term customer relationships. Full article

This work investigates the risk to Vulnerable Road Users (VRUs) from a novel light rail vehicle using the pedestrian impact scenario outlined in CEN/TR 17420. At a 20 km/h impact speed, a maximum head impact criterion (HIC₁₅) value of 15.9 was obtained for a 50th-percentile anthropometric test device (ATD), with this value increasing to 120.2 at 30 km/h impact speed. Both results are within the CEN/TR 17420 prescribed limit of 1000. In both cases, the vehicle does not fully comply with CEN/TR 17420 recommendations due to insufficient lateral displacement of the ATD post-impact. A vehicle front-end design—which would be exempt from the CEN/TR 17420 impact testing—was designed and tested to the same framework. Despite being formally exempt from testing, the design also did not fully comply with CEN/TR 17420 lateral displacement requirements. Critical evaluation of the CEN/TR 17420 framework is presented, leading to recommendations about how updated frameworks should take a pragmatic approach in how they define VRUs, and the measurement criteria used for assessing VRU risk in collisions. Discussions are presented considering whether alternative frameworks, such as the Bus Safety Standard, should be applicable to assess the safety of the novel light rail vehicle. Full article

This paper reports on a study investigating transportation professionals’ perceptions of AI’s equity impacts in the transportation sector, focusing on demographic variations in views. A survey conducted among U.S. transportation professionals examined their attitudes toward AI’s potential to influence transportation equity and ethics. The findings reveal insights based on gender, employment sector, educational background, and AI knowledge level, with notable differences in confidence towards AI’s ability to reduce bias and engage communities. This research highlights a commonly held opinion that there is a limited understanding of AI ethics within the transportation community, emphasizing the need for ongoing education and adaptation to AI technologies. This study contributes valuable perspectives to the discourse on AI, equity, and ethics in transportation, offering a foundation for future policy and strategy development. Full article

Increasing environmental and economic pressures have led to numerous innovations in the logistics sector, including integrated people and freight transport (IPFT). Despite growing attention from practitioners and researchers, IPFT lacks extensive research coverage. This study aims to bridge this gap by presenting a general framework and making several key contributions. It identifies, researches, and explains relevant terminologies, such as cargo hitching, freight on transit (FoT), urban co-modality, crowd-shipping (CS), occasional drivers (OD), crowdsourced delivery among friends, and share-a-ride, illustrating the interaction of IPFT with different systems like the sharing economy and co-modality. Furthermore, it classifies IPFT-related studies at strategic, tactical, and operational decision levels, detailing those that address uncertainty. The study also analyzes the opportunities and challenges associated with IPFT, highlighting social, economic, and environmental benefits and examining challenges from a PESTEL (political, economic, social, technological, environmental, and legal) perspective. Additionally, it discusses practical applications of IPFT and offers recommendations for future research and development, aiming to guide practitioners and researchers in addressing existing challenges and leveraging opportunities. This comprehensive framework aims to significantly advance the understanding and implementation of IPFT in the logistics sector. Full article

In the realm of traffic signal operations, the Signal Timing Manual second edition (STM2) serves as a foundational guide for professionals engaged in multimodal signal retiming projects. However, it is acknowledged that the STM2 has its limitations, and real-world conditions often necessitate adaptations in the established procedures. Considering this context, this research endeavors to bridge this gap by conducting a comprehensive survey aimed at traffic signal professionals. This study presents the findings of a comprehensive survey conducted among traffic signal professionals to explore the methodologies, challenges, and practices involved in multimodal signal retiming projects. The survey aimed to obtain detailed insights into the current state of signal retiming, the types of data and tools utilized, and the adaptations necessary to address the complexities of multimodal urban transportation networks. The survey highlights and summarizes responses from 36 professionals across North America, providing insight into both the common strategies and unique challenges faced by those responsible for optimizing signal timings in diverse and dynamic urban environments. The survey results reveal a reliance on diverse tools and data types for signal optimization, highlighting the complexities of accommodating different transportation needs. The findings underscore the importance of tailored approaches and advanced technologies in enhancing signal retiming processes. The insights gained from this study will inform future strategies and enhance the effectiveness of signal retiming procedures in urban areas, thereby contributing to improved traffic management and multimodal transportation efficiency. Full article

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