Transportation最新文献

{"title":"Freight-transit tour synthesis entropy-based formulation: sharing infrastructure for buses and trucks","authors":"Diana P. Moreno-Palacio, Carlos A. Gonzalez-Calderon, Hector Lopez-Ospina, Jhan Kevin Gil-Marin, John Jairo Posada-Henao","doi":"10.1007/s11116-024-10499-0","DOIUrl":"https://doi.org/10.1007/s11116-024-10499-0","url":null,"abstract":"<p>The freight system’s complexity and significant impact on urban areas necessitate carefully considering sustainable transportation options. The proposed freight transit tour synthesis (FTTS) model, using fuzzy logic and entropy maximization, analyzes freight and transit systems as a multiclass category, exploring scenarios where buses and trucks share infrastructure. The experiments demonstrate that capacity and maximum cost significantly influence the solutions obtained using fuzzy parameters, with ε-values indicating the best solution. Results may vary depending on available data, highlighting the need to explore solutions for different capacity levels if exceeded. The impact of the maximum cost constraint on tour flows is significant, emphasizing the importance of considering cost in optimizing tour flows. The model’s robustness is evident across various subjective value of time (SVT) scenarios. The application of the FTTS model offers a novel approach to estimating tour flows, incorporating traffic counts and fuzzy parameters for immediate, relevant results. The model's multiclass formulation accurately represents real-world traffic conditions, considering congestion in traffic assignments. Overall, the FTTS model holds promise for optimizing tour flows and shared infrastructure between freight and transit systems, aiding decision-makers in urban transportation planning and resource allocation, ultimately leading to improved traffic management and infrastructure usage efficiency.</p>","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"72 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141251799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Self-loop analysis based on dockless bike-sharing system via bike mobility chain: empirical evidence from Shanghai","authors":"Yancun Song, Li Zhang, Kang Luo, Chenyan Wang, Chengcheng Yu, Yonggang Shen, Qing Yu","doi":"10.1007/s11116-024-10500-w","DOIUrl":"https://doi.org/10.1007/s11116-024-10500-w","url":null,"abstract":"<p>Self-loop is a unique phenomenon observed in the daily operations of bike-sharing systems, characterized by bike returning to its original starting point after several trips within the bike mobility chain. The bike mobility chain concept involves forming new bike chains with a minimal fleet size. By understanding self-loop behavior, we can optimize fleet management and reduce operational costs. This study specifically investigates the self-loop behavior within the bike mobility chain while considering potential demand, using the case of the dockless bike-sharing system in Shanghai, China. An advanced multiply censored Tobit model is utilized to incorporate potential demand into origin–destination (O–D) data and reconstruct the bike mobility chain. The formation mechanisms of self-loop chains based on the land use and geographic location are analyzed. Our model achieved an R² of 0.871, significantly outperforming the baseline model. The results indicate that 76% of the bike chains can form self-loops within a 2-week period. Campus areas exhibit the highest self-loop rates, while suburban campuses can sustain operations with minimal or no scheduling required. This study not only reveals the back-and-forth behavior but also provides insights for scheduling and deployment strategies to enhance the environmental sustainability of bike-sharing systems.</p>","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"102 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141251699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of relocations on distances traveled for commuting and grocery shopping: structural equation models of panel data","authors":"Katja Schimohr, Eva Heinen, Joachim Scheiner","doi":"10.1007/s11116-024-10498-1","DOIUrl":"https://doi.org/10.1007/s11116-024-10498-1","url":null,"abstract":"<p>Residential relocations open a window of opportunity to decrease distances to work and other important daily destinations, such as grocery stores. This study investigates changes in trip distances after residential relocation, using data from a panel survey of 435 movers in Germany. We estimate two structural equation models for changes in commute and shopping trip distance. These models additionally allow us to draw insights into the relationships between spatial structure, travel attitudes, satisfaction with the accessibility of the workplace or shopping facilities, and housing preferences in residential location search. We find that there is a weak indication of an association between residential location choice and changes in trip distances. However, the analysis suggests that especially long trip distances are shortened through relocation. While residents in urban areas travel on average shorter distances, both for working and grocery shopping, only the shopping distance decreases after a move to a more urban location. A preference for urban structures leads to an increase in urbanity after relocation only in the model for grocery shopping trips. Even though long trips before relocation lead to dissatisfaction with the commute, we do not observe a direct effect of dissatisfaction with trips or reasons for moving on trip distances after a move.</p>","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"91 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141236022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Everything has changed: the impacts of the COVID-19 pandemic on the transit market in Montréal, Canada","authors":"Thiago Carvalho, Ahmed El-Geneidy","doi":"10.1007/s11116-024-10497-2","DOIUrl":"https://doi.org/10.1007/s11116-024-10497-2","url":null,"abstract":"<p>The COVID-19 pandemic has significantly impacted the transit market leading to ridership loss and service cuts. Most of the post-pandemic transit market literature has focused on how to attract those who stopped using transit services, however little attention has been given to how rider profiles have changed. To address this gap, we examine 2019 and 2022 data regarding transit commuters from Montréal, Canada. We apply factor and k-means cluster analyses to derive market segments at both points in time considering satisfaction levels, telecommuting rates, and frequency of transit use. We build upon these analyses to report on overall and mode group-level changes in the transit market. Our market segmentation reveals that captive, captive-by-choice, and choice riders still exist in the current public transit market. However, the share of these groups in the market has changed. The proportion of captive and choice riders has increased while captive-by-choice riders have shrunk in size. Moreover, the post-pandemic market has become mostly composed of infrequent riders and higher rates of telecommuting. We further explore these trends by commute mode (i.e., bus only, metro only, and bus and metro users). The findings from this research can be of interest to practitioners and policymakers as they shed light on the evolution of the perceptions and behaviours of segments of transit riders from before to after pandemic.</p>","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"98 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141177503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In-stream mobility and speed estimation of mobile devices from mobile network data","authors":"Rémy Scholler, Oumaïma Alaoui-Ismaïli, Denis Renaud, Jean-François Couchot, Eric Ballot","doi":"10.1007/s11116-024-10494-5","DOIUrl":"https://doi.org/10.1007/s11116-024-10494-5","url":null,"abstract":"<p>The cellular network is now nearly an almost ubiquitous and real-time sensor with coverage anywhere and anytime for any device. Mobile network data is a rich source for official statistics, such as human mobility. However, unlike GPS tracks, each mobile device in this data is described without precise knowledge of its spatial characteristics. Furthermore, there is no information about the device’s mobility status (i.e., whether it is moving or not) or speed which are important for behavioral analysis. Common mobility and speed estimations rely on precise location and do not consider privacy leakage risk. In this work, we propose two probabilistic approaches that estimate respectively devices’ mobility and devices’ speed from cellular data and connection likelihood maps for each network cell. Every estimation is computed in a short time and with a short history of data (for speed and for mobility). This constraint may be helpful with the most stringent legal frameworks for mobile operators including the combination of ePrivacy Directive and General Data Protection Regulation (GDPR) in Europe. The proposed approaches are the first we are aware of that allows for both mobility and speed estimation in this context. We experimented on two datasets, obtained from a mobile network operator’s signaling data and the associated GPS tracks of many consenting users. Our speed estimations are over 20% more accurate than common ones based on mobile sites and we provide confidence intervals for each estimation. Mainly due to mobile network uncertainty, our approach for speed estimation are relatively inaccurate at low speeds and the movement detection could remain unclear. However our approach for mobility estimation fills this gap.</p>","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"45 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141165343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Who is inclined to buy an autonomous vehicle? Empirical evidence from California","authors":"Md. Mokhlesur Rahman, Jean-Claude Thill","doi":"10.1007/s11116-024-10490-9","DOIUrl":"https://doi.org/10.1007/s11116-024-10490-9","url":null,"abstract":"<p>This study aims to investigate people’s perceptions and opinions on Autonomous Vehicles (AVs) and the key factors that influence their Behavioral Intention (BI) to purchase and use AVs. Data were sourced from the 2019 California Vehicle Survey to explore the determinants of AV purchase. A Structural Equation Model (SEM) of stated intentions is estimated to validate a theoretical framework drawn on relevant bodies of literature. The descriptive statistics show that many people are already aware of AVs. Many people also think that traveling by AVs is enjoyable, safe, and effective, although some of them would miss the joy of driving and would not entrust a driverless AV to shuttle their children. Results from the SEM indicate that being working-age adults, having children, household income, per capita income, and educational attainment are attributes positively associated with AV purchase intention. Similarly, psychological factors (e.g., perceived enjoyment, usefulness, and safety), prior knowledge of AVs, and experience with emerging technologies (e.g., electric vehicles) significantly enhance BI to purchase AVs. This study finds that family structure and psychological factors are the most influential factors of AV purchase intention, and more so than the built environment, transportation, and other socioeconomic factors.</p>","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"17 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141159628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-purpose pickup and delivery problem for combined passenger and freight transport","authors":"Jonas Hatzenbühler, Erik Jenelius, Győző Gidófalvi, Oded Cats","doi":"10.1007/s11116-024-10482-9","DOIUrl":"https://doi.org/10.1007/s11116-024-10482-9","url":null,"abstract":"<p>Recent advances in the development of modular transport vehicles allow deploying multi-purpose vehicles, which enable alternate transport of different demand types. In this study, we propose a novel variant of the pickup and delivery problem, the multi-purpose pickup and delivery problem, where multi-purpose vehicles are assigned to serve a multi-commodity flow. We solve a series of use case scenarios using an exact optimization algorithm and an adaptive large neighborhood search algorithm. We compare the performance of a multi-purpose vehicle fleet to a mixed fleet of single-purpose vehicles. Depending on cost parameters, our findings suggest that in certain scenarios, the total costs can be reduced by an average of 13% when multi-purpose vehicles are deployed, while at the same time reducing total vehicle trip duration and total distance traveled by on average 33% and 16%, respectively. The required fleet size can be reduced by 35% on average when operating multi-purpose vehicles. The results can be used by practitioners and policymakers to determine if the combined service of passenger and freight demand flows with multi-purpose vehicles in a given system will yield benefits compared to existing transport operations.</p>","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"44 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141156611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An approach to assess the role of features in detection of transportation modes","authors":"Sajjad Sowlati, Rahim Ali Abbaspour, Alireza Chehreghan","doi":"10.1007/s11116-024-10492-7","DOIUrl":"https://doi.org/10.1007/s11116-024-10492-7","url":null,"abstract":"<p>One of the fundamental prerequisites for interpreting collected passive travel data to develop intelligent transportation systems is the detection of transportation modes. The literature has divided transportation mode detection into two parts: feature extraction and implementation of classification models. Selecting and employing influential features will help maximize the power of the classification model. Meanwhile, the interpretation and identification of influential features, which will be the focus of this study, have received less attention. Importantly, the influence of features varies depending on the nature of the input data and the choice of classification models. In many cases, the extracted features show interdependence, where their combined correlation significantly impacts specific outcomes. Consequently, evaluating the effectiveness of individual features in isolation may not produce accurate results, requiring the exploration of alternative methodologies. This study seeks to bridge these gaps through a comprehensive investigation. Three open-source datasets, Geolife, MTL Trajet 2017, and MTL Trajet 2016, were utilized to enhance reliability, validate the approach, and investigate the variability of influential features under various data collection conditions. Originally, various features were extracted and grouped for this purpose based on their kinematic, spatial, and contextual features. Then, three powerful classification models (Random Forest, LightGBM, and XGBoost) were utilized. A hybrid feature selection algorithm was employed to select a subset of features to analyze the variability of influential features across different classification models. The algorithm removed over half of the features with minimal or negative impact, thereby simplifying the process of classification identification. Since the features when combined in the form of a subset, would result in powerful identification, the influence of the features was analyzed within a set of features instead of analyzing each feature individually. Two approaches, “number of feature repetitions” and “Shapley Additive Explanations (SHAP) value,” were adopted to interpret the computation. After implementation, the “average velocity” with repetition in all datasets and classification models (nine repetitions) had the highest SHAP value, making it the most influential feature across all datasets and classification models. The “public stations indicator” was the most influential spatial feature with the highest SHAP value, appearing nine times, while “holiday” had the most repetitions among the contextual features.</p>","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"28 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140954281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling intermodal traveller behaviour in mega-city regions: simultaneous versus sequential estimation frameworks","authors":"Ning Huan, Stephane Hess, Toshiyuki Yamamoto, Enjian Yao","doi":"10.1007/s11116-024-10489-2","DOIUrl":"https://doi.org/10.1007/s11116-024-10489-2","url":null,"abstract":"<p>The sustained expansion of mega-city regions and the development of multimodal transport networks have catalysed intercity mobility, thereby restructuring regional travel demand patterns. This study aims to interpret the behaviour of intermodal travellers in a short-haul intercity context within mega-city regions. A comparative modelling framework, utilising both simultaneous and sequential estimation methods, is proposed based on stated preference survey data collected in the Beijing-Tianjin-Hebei region, China. The simultaneous estimation framework examines the integrated measurement of the perceived utility of multiple stages of travel using cross-nested logit models. In contrast, the sequential estimation framework systematically investigates the bidirectional interactions associated with the intercity mode decision and decisions related to access and egress modes in a stepwise manner. The latter quantifies the accessibility of transport hubs and destinations to assess the implicit cost of feeder trips in the intercity mode decision. It validates the sequential impact on feeder mode choice preferences. In addition to identifying behavioural determinants, the models’ relative performance is assessed regarding behaviour prediction accuracy for diverse groups of travellers categorised by travel purpose, fellow traveller, baggage size, and travel frequency. Statistically, the weighted prediction errors for access, intercity, and egress mode choices are 1.12%, 1.33%, and 0.89% under the simultaneous estimation framework. In contrast, under the sequential estimation framework, these errors are reduced to 0.81%, 0.63%, and 0.50%, respectively. The results suggest the superior applicability of the latter in interpreting intermodal mobility patterns.</p>","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"15 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140915070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid gradient-swarm intelligence to improve quality of solutions for origin–destination matrix adjustment problem","authors":"Mehrdad Gholami Shahbandi, Abbas Babazadeh","doi":"10.1007/s11116-024-10493-6","DOIUrl":"https://doi.org/10.1007/s11116-024-10493-6","url":null,"abstract":"<p>The high cost of conventional surveys has motivated researchers to develop methods for adjusting a prior Origin–destination (OD) matrix from easily available traffic counts. The gradient method is a mathematical programming approach widely used for the OD matrix adjustment problem (ODMAP). However, this method easily gets trapped in local optima due to the non-convexity of the problem. Moreover, validation of the gradient solutions against predefined target matrices shows the method has considerable difficulty with estimating the sum of the OD matrix elements. Particle swarm optimization (PSO) is a metaheuristic which is getting lots of attention for its global search ability, but is less accurate in local search. The proposed algorithm hybridizes PSO with the gradient method, considering that the combination of good local convergence properties and effective global search makes an excellent algorithm for the ODMAP. Comparison of the results for a small and a real-life network demonstrates that the hybrid algorithm provides higher convergence properties and achieves more accurate solutions than its constituent parts working alone.</p>","PeriodicalId":49419,"journal":{"name":"Transportation","volume":"223 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140915071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}