Future Transportation最新文献

{"title":"A Meso-Scale Petri Net Model to Simulate a Massive Evacuation along the Highway System","authors":"Hamzeh Qabaja, Mujahid I. Ashqer, M. Bikdash, Huthaifa I. Ashqar","doi":"10.3390/futuretransp3010019","DOIUrl":"https://doi.org/10.3390/futuretransp3010019","url":null,"abstract":"Natural disasters may require that the residents of the affected area be evacuated immediately using a potentially damaged infrastructure. In this paper, we developed a mesoscopic simulation modeling approach for modeling traffic flow over a large geographic area and involving many people and vehicles. This study proposed a novel model, namely, Colored Deterministic and Stochastic Petri Net (CDSPN), which can mesoscopically provide an individual vehicular traffic dynamic. Each vehicle has a unique identifier, speed, distance to go, assigned target, and a specific route. It also proposed a method to automatically construct a Petri net model that represents the evacuation of Guilford County (GC), North Carolina, from standard Geographic Information Systems (GIS) shapefiles. We showed that this model could successfully simulate the dynamics of hundreds of thousands of vehicles moving on the highway system towards pre-specified safe targets such as medical facilities, exit points, or designated shelters. The vehicles are assumed to obey traffic laws, and the model reflects the complexities of the actual highway systems. The developed software can be used to analyze in reasonable detail the evacuation process, such as identifying bottlenecks and estimating efficiency and the time needed. An explicit list of 18 assumptions is stated and discussed. The Petri net for GC evacuation is reasonably massive, consisting of 35,476 places and 43,540 transitions with 531,595 colored tokens, where each token represents a vehicle in GC. We simulate the evacuation, develop statistics, and evaluate patterns of evaluation. We found that the evacuation took about 8.7 h.","PeriodicalId":238233,"journal":{"name":"Future Transportation","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114233140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysing the Potential of Performing Last-Mile Bicycle Deliveries: The Perspective of Brazilian Logistics Operators","authors":"C. D. O. L. Nascimento, L. Oliveira","doi":"10.3390/futuretransp3010018","DOIUrl":"https://doi.org/10.3390/futuretransp3010018","url":null,"abstract":"Knowledge about the perception of stakeholders regarding the effectiveness of last-mile bicycle deliveries is essential to promote solutions at a local and national level. However, their use is an incipient solution in the Brazilian context. This paper aims to analyse the potential of performing last-mile bicycle deliveries according to the perspective of Brazilian logistics operators. First, the variables that affect the decision of logistic operators to adopt bicycles were captured using the theory of planned behaviour. Later, the intention of behaviour was measured by estimating an ordered logistic regression. The results showed that environmental awareness, public policies and weather conditions negatively influence the intention of logistics operators to perform last-mile bicycle deliveries in Brazil. However, these variables are more cultural than operational, and could be changed by awareness of the importance of performing last-mile bicycle deliveries to promote sustainable cities. Additionally, the findings could encourage the development of sustainable freight policies from private companies to achieve sustainable future transportation.","PeriodicalId":238233,"journal":{"name":"Future Transportation","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131144170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Self-Organized Neural Network Method to Identify Crash Hotspots","authors":"Esmaiel Karimi, F. Haghighi, Abbas Sheykhfard, M. Azmoodeh, Khaled Shaaban","doi":"10.3390/futuretransp3010017","DOIUrl":"https://doi.org/10.3390/futuretransp3010017","url":null,"abstract":"Crash hotspot identification (HSID) is an essential component of traffic management authorities’ efforts to improve safety and allocate limited resources. This paper presents a method for identifying hotspots using self-organizing maps (SOM). The SOM method was used to identify high-risk areas based on five commonly used HSID methods: crash frequency, equivalent property damage only, crash rate, empirical Bayes, and the societal risk-based method. Crashes on a major road in Iran were examined using the proposed method. Based on these criteria, high-risk locations were grouped into six clusters, which provided appropriate criteria for each location depending on the importance of the cluster. The findings show that the identification of crash hotspots tends to focus on areas with more crashes and deaths, demonstrating that the research methodology was appropriate.","PeriodicalId":238233,"journal":{"name":"Future Transportation","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126522766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Pandemic Implications for Carsharing: An Italian Context","authors":"Zahra Shams Esfandabadi, Meisam Ranjbari, S. Scagnelli","doi":"10.3390/futuretransp3010016","DOIUrl":"https://doi.org/10.3390/futuretransp3010016","url":null,"abstract":"Carsharing, as an innovative mobility option, can potentially support the urban transition towards a more sustainable mobility system and achieving sustainable development goals. This short communication aims at providing the status of carsharing services in Italy, with a focus on Turin, before and after the COVID-19 pandemic. In this regard, an overview of the role of carsharing in urban traffic is provided. Then, carsharing services in Italy before and after the pandemic are mapped. Accordingly, the implications of the pandemic outbreak for carsharing services are discussed. The provided insights confirm that although carsharing services have been affected by the pandemic, even after returning to normal life, the usage of carsharing is still far below its pre-pandemic level in Italy. Finally, to support sustainable mobility and incentivize using shared mobility services, a research agenda for further research is proposed, targeting the research gaps regarding (i) the factors leading to lower usage of carsharing after the pandemic, (ii) potential solutions and policies to support carsharing services return to their pre-pandemic level and exceeding it, and (iii) examining the impact of provided supports by governments during the pandemic, such as bonuses for purchasing bikes and scooters, on the adoption of carsharing services for the post-pandemic era.","PeriodicalId":238233,"journal":{"name":"Future Transportation","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124450808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of Aggregate Urban Mobility Patterns of Nonregular Travellers from Mobile Phone Data","authors":"Manon Seppecher, L. Leclercq, Angelo Furno, Thamara Vieira da Rocha, J. André, Jérôme Boutang","doi":"10.3390/futuretransp3010015","DOIUrl":"https://doi.org/10.3390/futuretransp3010015","url":null,"abstract":"Over the last two decades, mobile phone data have appeared to be a promising data source for mobility analysis. The structure, abundance, and accessibility of call detail records (CDRs) make them particularly suitable for such use. However, their exploitation is often limited to estimating origin–destination matrices of a restricted part of the population: regular travellers. Although these studies provide valuable information for policymakers, their scope remains limited to this subpopulation analysis. In the present work, we develop a collective mobility reconstruction method adapted to nonregular travellers. The method relies on the notion of the detour ratio, which makes it robust to the lack of mobile phone data as well as its application to large instances (large and dense telecommunication networks). It is used to conduct a longitudinal analysis of the macroscopic mobility patterns in Santiago de Cali, Colombia, thanks to call detail data shared by communication provider CLARO as part of a research project conducted by Citepa, Paris, the Green City Big Data Project.","PeriodicalId":238233,"journal":{"name":"Future Transportation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126522008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing Urban Travel Behavior Components in Tehran, Iran","authors":"H. Alizadeh, Ayyoob Sharifi","doi":"10.3390/futuretransp3010014","DOIUrl":"https://doi.org/10.3390/futuretransp3010014","url":null,"abstract":" This research is an attempt to explore the nature and characteristics of urban travel behavior in the metropolitan area of the Iranian capital, Tehran. To this end, using the perspectives of 822 participants via a questionnaire survey, we assessed six major Travel Behavior Components (TBCs)—namely, travel mode, travel time, travel destination, travel frequency, travel choice, and travel purpose—from the lens of five different sociodemographic characteristics—that is, gender, age, family structure, and educational and occupational groups. Using SPSS-26, MAXQDA, and Structural Equation Model (SEM) via AMOS software, we analyzed priorities and preferences related to TBCs across different social groups and explored the impact of preferences of different social groups on TBCs in the Tehran metropolitan area. The results indicate that firstly, the tendency to travel by private transport has the highest share among all groups compared with other modes of travel. Secondly, we identified four major challenges affecting urban travel behavior in Tehran: lacking diverse options for urban traveling, old vehicles and infrastructure, traffic congestion, and unequal access to travel facilities in the city. Finally, we found that sociodemographic characteristics have a relatively strong and significant impact on TBCs. The study highlights the role of sociodemographic characteristics in travel behavior transformations and gives more insights into the travel behavior preferences of urban residents. Such insights would be effective for city policymakers and planners to enhance the quality of urban transportation. ","PeriodicalId":238233,"journal":{"name":"Future Transportation","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125764440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of the Impact of Advertising in Promoting Sustainable Mobility and Multimodality in the Urban Transport System","authors":"Margarita Išoraitė, A. Jarašūnienė, Kristina Samašonok","doi":"10.3390/futuretransp3010013","DOIUrl":"https://doi.org/10.3390/futuretransp3010013","url":null,"abstract":"Advertising can influence and change consumers’ attitudes, habits, and behaviour and can therefore be a way to promote sustainable mobility and multimodality in urban transport systems. This paper focuses on the following questions: what is the impact of advertising on consumer behaviour in the context of sustainable mobility and multimodal decision making in urban transport systems? This paper assesses the impact of advertising on consumer behaviour in the context of the scientific literature, and discusses the methods and effectiveness of advertising in promoting sustainable mobility and multimodality in urban transport systems. Thus, this study examines the role of advertising and its impact on consumer behaviour, and provides a framework for the use of advertising to promote sustainable mobility and multimodality in urban transport systems. The study involved 396 inhabitants of major Lithuanian cities. Analytical descriptive, quantitative, and statistical research methods were applied. A quantitative research strategy was used to better understand the expression of advertising and its impact on the development of sustainable mobility and multimodality in urban transport. The results show that advertisements promoting sustainable mobility do not have a significant impact and only a small proportion of respondents associate advertisements with the development of sustainable mobility and multimodality in urban transport. This provides an opportunity to improve the information system of advertisements by exploiting the originality, text, content, and idea of the advertisement, which the study found to be one of the most influential factors in changing consumers’ attitudes and encouraging them to make travel decisions based on the principles of sustainable mobility and multimodality. In addition, television, the internet (including e-mail advertising), radio, and outdoor billboards can be among the most effective means of providing information in anticipation of the development of sustainable mobility and multimodality in urban transport. The results of the study will therefore have long-term value for the scientific debate on the impact of advertising on the promotion of sustainable mobility and multimodality in urban transport, and a practical relevance for providing guidelines for the development of sustainable mobility and multimodality in urban transport in the information advertising system.","PeriodicalId":238233,"journal":{"name":"Future Transportation","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121101743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Benefits of Shared-Fleet Horizontal Logistics Collaborations: A Case Study of Patient Service Vehicles Collecting Pathology Samples in a Public Sector Healthcare Setting","authors":"Matthew Grote, T. Cherrett, Andrew Oakey, A. Martinez-Sykora, Ismail Aydemir","doi":"10.3390/futuretransp3010011","DOIUrl":"https://doi.org/10.3390/futuretransp3010011","url":null,"abstract":"Road-based logistics suffer from inefficiencies due to less-than-full load vehicle movements. Consolidating loads through shared-fleet collaborations (also known as freight pooling) can reduce such inefficiencies, and thereby reduce costs, vehicle-kilometres (vkm), and related emissions and congestion. Utilising a significant historical dataset of vehicle movements, the potential cost savings and environmental benefits of a shared-fleet operation involving collaboration between two public sector organisations, integrating both static (fixed-schedule) and dynamic (client-specific) demand within a healthcare setting, were quantified. A Sample Collection Service (SCS; transporting pathology samples from doctors’ surgeries to centralised laboratories for analysis) shared spare capacity in vehicles operated by a Patient Transport Service (PTS; transporting eligible non-emergency patients to/from routine hospital appointments) as an alternative to engaging an external courier company. Results suggested that a shared-fleet collaboration servicing 78 surgeries, alongside normal patient loads in an average of 24 PTS vehicles/day, produced reductions of 16%, 13% and 12% in costs, vkm and carbon dioxide emissions, respectively. Decision-makers within public sector organisations that operate own-account vehicle fleets could pursue policies that actively seek out opportunities to deploy shared-fleet solutions to improve vehicle utilisation and therefore reduce public sector spending and the detrimental effects of road logistics.","PeriodicalId":238233,"journal":{"name":"Future Transportation","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126107075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Secure Traffic Police Remote Sensing Approach via a Deep Learning-Based Low-Altitude Vehicle Speed Detector through UAVs in Smart Cites: Algorithm, Implementation and Evaluation","authors":"A. Moshayedi, A. Roy, Alireza Taravet, Liefa Liao, Jianqing Wu, Mehdi Gheisari","doi":"10.3390/futuretransp3010012","DOIUrl":"https://doi.org/10.3390/futuretransp3010012","url":null,"abstract":"Nowadays, the unmanned aerial vehicle (UAV) has a wide application in transportation. For instance, by leveraging it, we are able to perform accurate and real-time vehicle speed detection in an IoT-based smart city. Although numerous vehicle speed estimation methods exist, most of them lack real-time detection in different situations and scenarios. To fill the gap, this paper introduces a novel low-altitude vehicle speed detector system using UAVs for remote sensing applications of smart cities, forging to increase traffic safety and security. To this aim, (1) we have found the best possible Raspberry PI’s field of view (FOV) camera in indoor and outdoor scenarios by changing its height and degree. Then, (2) Mobile Net-SSD deep learning model parameters have been embedded in the PI4B processor of a physical car at different speeds. Finally, we implemented it in a real environment at the JXUST university intersection by changing the height (0.7 to 3 m) and the camera angle on the UAV. Specifically, this paper proposed an intelligent speed control system without the presence of real police that has been implemented on the edge node with the configuration of a PI4B and an Intel Neural Computing 2, along with the PI camera, which is armed with a Mobile Net-SSD deep learning model for the smart detection of vehicles and their speeds. The main purpose of this article is to propose the use of drones as a tool to detect the speeds of vehicles, especially in areas where it is not easy to access or install a fixed camera, in the context of future smart city traffic management and control. The experimental results have proven the superior performance of the proposed low-altitude UAV system rather than current studies for detecting and estimating the vehicles’ speeds in highly dynamic situations and different speeds. As the results showed, our solution is highly effective on crowded roads, such as junctions near schools, hospitals, and with unsteady vehicles from the speed level point of view.","PeriodicalId":238233,"journal":{"name":"Future Transportation","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129936071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Calibration of the Microsimulation Traffic Model Using Different Neural Network Applications","authors":"Irena Ištoka Otković, T. Tollazzi, M. Šraml, D. Varevac","doi":"10.3390/futuretransp3010010","DOIUrl":"https://doi.org/10.3390/futuretransp3010010","url":null,"abstract":"The efficacy of the application of traffic models depends on a successful process of model calibration. Microsimulation models have a significant number of input parameters that can be optimized in the calibration process. This paper presents the optimization of input parameters that are difficult to measure or unmeasurable in real traffic conditions and includes parameters of the driver’s behavior and parameters of Wiedemann’s psychophysical car-following model. Using neural networks, models were generated for predicting travel time and queue parameters and were used in the model calibration procedure. This paper presents the results of a comparison of five different applications of neural networks in calibrating the microsimulation model. The VISSIM microsimulation traffic model was selected for calibration and field measurements were carried out on two roundabouts in a local urban transport network. The applicability of neural networks in the process of calibrating the microsimulation models was confirmed by comparison of the modelled and measured data of traffic indicators in real traffic conditions. Methods of calibration were validated with two sets of new measured data at the same intersection where the calibration of the model was carried out. The third validation was made at the intersection in a different location. The selection of the optimal calibration methodology is based on the model accuracy between the simulated and measured data of traveling time, as well as queue parameters. The microsimulation model provides access to the raw data of observed traffic parameters for each vehicle in the simulation. The dataset of the calibrated model simulation results of all travel times of the selected traffic flow was compared with the dataset of the measured field data to determine whether the data are statistically significantly different or not.","PeriodicalId":238233,"journal":{"name":"Future Transportation","volume":"21 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131922587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}