Multimodal Transportation最新文献

{"title":"Relationship between urban traffic crashes and temporal/meteorological conditions: understanding and predicting the effects","authors":"Xiao Tang,&nbsp;Zihan Liu,&nbsp;Zhenlin Wei","doi":"10.1016/j.multra.2024.100175","DOIUrl":"10.1016/j.multra.2024.100175","url":null,"abstract":"<div><div>Urban traffic accidents pose significant challenges to public safety and transportation management. Previous studies have revealed that temporal and meteorological factors are the key contributors to accident rate. Besides the inconsistent observations or lack of exploration in some aspects such as snowfall, fog, wind and daily temperatures, it has been shown that these factors are essentially entangled. Furthermore, existing methodologies of analysis or prediction have been limited to relative risk or traditional models. Hence, this study is centered on understanding the detailed correlations between temporal and meteorological factors and accident rate of two types of crashes – moving vehicle and fixed-object crashes using the traffic accident data from Dalian. Further, by incorporating a diverse set of the features, a prediction model leveraging the random forest algorithm is proposed and proved effective in anticipating accident occurrences on the district level. The feature importance analysis has shown that time period and factors such as holiday, temperature and season are most important factors. The rate is higher on working days and in spring, and collisions of both types peak at 6–7 am. When the highest daily temperature is 27 °C and the lowest is 20 °C or -8 °C, the incidence is relatively higher. On the basis, the recommendations are aimed at optimizing transportation systems, mitigating accident risks, and enhancing public safety in urban environments.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142551885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An assignment-based decomposition approach for the vehicle routing problem with backhauls","authors":"Irandokht Parviziomran,&nbsp;Monireh Mahmoudi","doi":"10.1016/j.multra.2024.100174","DOIUrl":"10.1016/j.multra.2024.100174","url":null,"abstract":"<div><div>In the context of the Vehicle Routing Problem with Backhauls, which involves delivering to linehaul and picking up from backhaul customers, we propose a novel mathematical model that can decompose the main problem into three sub-problems: two Open Vehicle Routing Problems and one Assignment Problem. In our proposed model, Open Vehicle Routing Problems optimize routes for homogeneous vehicles serving linehaul/backhaul customers, while the Assignment Problem matches linehaul and backhaul routes. We utilize Lagrangian decomposition approach and solve subproblems in parallel and sequential layouts. We measure the performance of the foregoing arrangements (in terms of solution quality and computational efficiency) by testing our model on two benchmark datasets, proposed by Goetschalckx and Jacobs-Blecha (1989) and Toth and Vigo (1997) and are known as GJ and TV datasets in the extant literature, respectively. Our model matches best known solutions in 35 % and 33 %, with most within 2 % deviation, for GJ and TV instances, respectively. We also showcase our model on a real-world transportation network containing 100, 250, and 500 customers and geographically located in Lansing, Michigan. To reduce the computational burden of solving the Vehicle Routing Problem with Backhauls on the Lansing dataset, we present a cluster first-route second algorithm and then analyze the impact of vehicle capacity on the solution quality of our proposed algorithm.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An adapted savings algorithm for planning heterogeneous logistics with uncrewed aerial vehicles","authors":"Andy Oakey ,&nbsp;Antonio Martinez-Sykora ,&nbsp;Tom Cherrett","doi":"10.1016/j.multra.2024.100170","DOIUrl":"10.1016/j.multra.2024.100170","url":null,"abstract":"<div><div>This paper proposes a new extension to the Sustainable Specimen Collection Problem (SSCP), where medical specimens are transported by vans, bikes, and uncrewed aerial vehicles (UAVs, or drones) from local medical practices/offices to a central hospital laboratory for analysis, employing a two-echelon collection approach. Time restrictions from existing operations and literature are also introduced, with the study being formulated as a weighted multi-objective problem seeking to minimise (i) operating costs; (ii) transit times; and (iii) energy/environmental impacts. A new adaptation of the Clarke and Wright Savings Algorithm is subsequently presented to create collection rounds that leverage each mode’s strengths. Subsequently, routes are compiled into workable fixed shifts using a modified bin-packing algorithm in each iteration.</div><div>The approach of this study is based on a case study of the UK’s National Health Service (NHS), involving the collection of pathology samples using traditional vans operating within fixed time slots. Using case study data from the Solent region (England), a novel test instance generation methodology was also developed, whereby realistic site positioning and origin-destination travel data are captured to enable effective algorithm experimentation. The findings from applying the proposed algorithm to a set of test instances based on this methodology are subsequently discussed, where it was found that the adapted savings and bin-packing approach produced effective solutions quickly, with 90% of all large instances (200 sites) being solved within 15 min. Further algorithm developments and the application of the devised problem/methodologies are also discussed.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Catastrophic causes of truck drivers’ crashes on Brazilian highways: Mixed method analyses and crash prediction using machine learning","authors":"Rodrigo Duarte Soliani ,&nbsp;Ana Rita Tiradentes Terra Argoud ,&nbsp;Fábio Santiago ,&nbsp;Alisson Vinicius Brito Lopes ,&nbsp;Nwabueze Emekwuru","doi":"10.1016/j.multra.2024.100173","DOIUrl":"10.1016/j.multra.2024.100173","url":null,"abstract":"<div><div>Traffic crashes represent a global challenge, especially in Brazil, where one-third of incidents on federal highways involve trucks, highlighting significant economic and safety risks for truck drivers and the community at large. This study focuses on understanding the specific causes of crashes involving trucks on Brazilian highways, using a decade of data from the Federal Highway Police to develop a predictive model aimed at accident prevention. It analyzes historical crash trends, selects attributes for prediction models, trains classifiers, evaluates predictions through confusion matrices, and enhances reliability via cross-validation techniques, aiming to develop an accident prevention tool. The analysis revealed a temporal pattern, with a slowdown in fatal incidents from 2013 to 2016, followed by an upward trend from 2017. MG-381 emerged as the deadliest highway, and single-lane roads were identified as more accident-prone, emphasizing the need for targeted preventive measures. Additionally, machine learning models achieved an accuracy of over 70 %, with XGBoost and <span><span>LightGBM</span></span> leading at 73 %, providing reliable insights for road safety interventions. In transportation engineering and road safety research, these findings highlight the importance of data-driven approaches to understand accident dynamics and design effective interventions to mitigate risks on highways, thereby contributing to increased road safety and social well-being.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142440883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reinforcement learning in transportation research: Frontiers and future directions","authors":"Xiongfei Lai ,&nbsp;Zhenyu Yang ,&nbsp;Jiaohong Xie ,&nbsp;Yang Liu","doi":"10.1016/j.multra.2024.100164","DOIUrl":"10.1016/j.multra.2024.100164","url":null,"abstract":"<div><p>The development of reinforcement learning (RL) provides innovative solutions for various decision-making problems in transportation, often pertaining to integrating advanced vehicular technologies such as connected and autonomous vehicles and electric vehicles. This paper reviews transportation research with RL-based methods over the recent decades. We start with a bibliometric analysis through extensive literature retrieval of 1030 papers from 1996 to 2023. We identify different research areas of RL in transportation, summarizing the most visited research problems. We find that, at the vehicle level, motion and route planning and energy-efficient driving problems have attracted the most attention. Meanwhile, adaptive traffic signal control and management have been the most visited problems at the network level. We discuss several potential future directions, including the migration of RL models from simulations to real-world cases, designing tailored control architectures for complex transportation systems, exploring explainable RL in transportation research to ensure transparency and accountability in decision-making processes, and integrating people and vehicles into transportation systems in a sustainable and equitable manner.</p></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772586324000455/pdfft?md5=e3dac5e354b11e94ecca9b838c9118dd&pid=1-s2.0-S2772586324000455-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142272803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancement of the impacts 2050 model to enable a whole system sustainability assessment of rideshare","authors":"Mark Muller ,&nbsp;Gonçalo Homem de Almeida Correia ,&nbsp;Seri Park ,&nbsp;Yimin Zhang ,&nbsp;Brett Fusco ,&nbsp;Ross Lee","doi":"10.1016/j.multra.2024.100171","DOIUrl":"10.1016/j.multra.2024.100171","url":null,"abstract":"<div><p>Emerging concepts, such as Mobility as a Service (MaaS), could evolve to provide sustainable mobility, especially in densely populated urban areas. However, recent studies highlight the challenge of evaluating how the complex interactions of user demographics, mode choice, vehicle automation, governance, and efficiency will impact the sustainability of future mobility. Given this challenge, this research identifies a whole system (STEEP - social, technical, economic, environmental, and political) framework as essential to assess the overall sustainability of emergent urban mobility systems such as rideshare. The need is a single tool that can rapidly explore the long-range sustainability impact of such alternative future mobility scenarios for a given city region. This paper documents enhancements made to Impacts 2050, a strategic-level model of urban mobility, to address this need, including updates to the statistical travel behavior model and the addition of rideshare including trip occupancy. Results obtained with the enhanced Impacts 2050 showed that, while rideshare use increased significantly for some scenarios, its overall mode share remained limited. In addition, though rideshare enabled users to shed car ownership, the overall percentage increase of “no car ownership” was low. An urban mobility sustainability scorecard based on STEEP and generated by output from the enhanced Impacts 2050 is presented.</p></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772586324000522/pdfft?md5=6cc981bdab92bb50f51d7ef93c060687&pid=1-s2.0-S2772586324000522-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142241023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Co-creating multimodal transportation hubs in Switzerland: How to close the gap between actors across different scales, levels, and sectors","authors":"Philippe Stadler Benz,&nbsp;Michael Stauffacher","doi":"10.1016/j.multra.2024.100168","DOIUrl":"10.1016/j.multra.2024.100168","url":null,"abstract":"<div><p>Transforming railway stations and their surroundings into multimodal transportation hubs (MMTHs) involves numerous actors at different scales and from different economic sectors and levels of government. Successful transformations offer a wide range of benefits to sustainable development, including increased public transportation use and mixed-use, high-density station districts. Intensive collaboration and, ideally, co-creation are critical to achieving these outcomes through MMTHs; however, orchestrating all involved actors is challenging and requires supporting methods, and the knowledge required to develop and refine methods is scarce and rarely subjected to systematic analysis. Based on 15 semistructured interviews and two design thinking workshops attended by 13 and 20 MMTH experts, our study shows that the challenges of co-creating MMTHs relate not only to professional matters but also to managing collaboration and implementation among a large number of actors with various roles and interests. In this paper, we develop design guidelines for reviewing and evaluating two current methods and a prototypical method (the functional model) with the goal of identifying potential improvements and supporting MMTH co-creation in Switzerland. These guidelines cover the broad spectrum of co-creation activities, from organization and design collaboration with relevant actors to the development of a shared vision to support financing and the planning process. The functional model encompasses many aspects of the design guidelines and closes gaps between actors across different scales, economic sectors, and governmental levels. Due to the relatively low effort involved, the method can be repeated as needed throughout MMTH development, which often takes several years. Our study demonstrates that existing MMTH co-creation methods require improvement, and the design guidelines developed here suit this purpose. Our work thus contributes to the further development of MMTH co-creation methods, ultimately supporting sustainable development such as CO₂ emission reduction and responsible land use.</p></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772586324000492/pdfft?md5=3714111297e6fe50f6aa490dd1aefbca&pid=1-s2.0-S2772586324000492-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142161727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring micromobility choice behavior across different mode users using machine learning methods","authors":"Md Al Adib Sarker,&nbsp;Hamidreza Asgari,&nbsp;Afsana Zarin Chowdhury,&nbsp;Xia Jin","doi":"10.1016/j.multra.2024.100167","DOIUrl":"10.1016/j.multra.2024.100167","url":null,"abstract":"<div><p>In an effort to capture travelers’ propensity towards micro-mobility options, a consumer survey was designed and conducted in the state of Florida in Fall 2021. In addition to collecting socioeconomic, demographic, attitudinal, and trip-related information, stated-preference scenarios were presented to the respondents, in which they were asked to choose between their current mode, and three different micro-mobility alternatives, namely: e-scooter, e-scooter + public transit, and moped. A machine learning classification model, the tree-based Extreme Gradient Boosting algorithm was applied to study users’ mode choice toward micromobility options given its non-parametric nature and high predictive power. SHAP values were then used to analyze the contributing factors for each of the micro-mobility options. In addition, Local Interpretable Model-agnostic Explanations (LIME) was employed to interpret and validate the SHAP findings at the individual prediction level. Model results show that age, car-oriented attitudes, lack of familiarity/previous experience, and lack of appropriate infrastructures were the major barriers to choose micro-mobility services. Such services can be suitable alternatives for young people who come from large families or ride-share users who have prior experience with micromobility services. Among different micro-mobility alternatives, mopeds were favored by males and green travelers. It seems that e-scooter + public transit was considered a safe and comfortable option, especially for students and low-income individuals, but generally not favored by travel time-sensitive or green travelers. Finally, e-scooters seem to be a favorable option for younger individuals with short travel distances. Our findings provide additional insights on policies that may help encourage the use of micromobility devices and promote sustainable, affordable, and equitable mobility services.</p></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772586324000480/pdfft?md5=627854bf007e54aa81f10ca0ead8441d&pid=1-s2.0-S2772586324000480-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142161728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of technology belief, perceived risk and initial trust in users’ acceptance of urban air mobility: An empirical case in China","authors":"Enjian Yao ,&nbsp;Dongbo Guo ,&nbsp;Shasha Liu ,&nbsp;Junyi Zhang","doi":"10.1016/j.multra.2024.100169","DOIUrl":"10.1016/j.multra.2024.100169","url":null,"abstract":"<div><p>Urban Air Mobility (UAM) is poised to revolutionize transportation, necessitating an assessment of public acceptance before broad commercial adoption. This study presents the Urban Air Mobility Acceptance Model (UAM-AM), which draws from the Technology Acceptance Model (TAM) and underscores the crucial role of initial trust, technology belief and perceived risk. The UAM-AM is validated using Structural Equation Modeling (SEM) based on 544 questionnaires for the first time in China. The findings highlight the significant impact of perceived ease of use and perceived usefulness on acceptance, uncovering a complex interplay with the intention to utilize UAM services. Notably, initial trust emerges as a foundational factor, influencing attitudes directly or indirectly through perceived ease of use and perceived usefulness. Moreover, the research identifies technology belief and perceived risk as fundamental drivers of initial trust. Examination of demographic segments reveals a heightened technology belief among individuals with backgrounds in science, indicative of a more favorable attitude towards UAM adoption. In closing, the paper presents recommendations for policymakers, service providers, and eVTOL manufacturers to formulate effective strategies that promote public acceptance during the initial phases of UAM deployment.</p></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772586324000509/pdfft?md5=047451640b5c4fbbaac15c4dcf4f8fb5&pid=1-s2.0-S2772586324000509-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142128911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accounting for taxi service conditions in estimating route travel time from floating car data using Markov chain model","authors":"Tianli Tang ,&nbsp;Shaopeng Zhong ,&nbsp;Yuting Chen ,&nbsp;Lichen Luo","doi":"10.1016/j.multra.2024.100172","DOIUrl":"10.1016/j.multra.2024.100172","url":null,"abstract":"<div><p>Recognising the variations in driving behaviour between taxis in the <em>empty</em> and <em>carry</em> conditions is pivotal for enhancing the accuracy of route travel time estimations using floating car data. However, existing methods largely overlook this distinction. In light of this, this study aims to harness these variations for more precise estimations. Utilising taxi data, we segmented the information by service conditions and executed distinct estimations for each segment. The route travel time was deduced through convolutional operation, complemented by a Markov chain model to discern correlations between travel times across various links. Our innovative approach realised a substantial enhancement in accuracy. Notably, when accounting for distinct service conditions, there was a reduction of 51.44% in mean absolute error and a 46.83% decline in maximum percentage error. By providing more accurate and reliable travel time predictions, our methodology enables better-informed traffic management decisions. Accurate travel time estimations are essential for optimising traffic signal timings, planning efficient routing strategies, and managing road network usage. These improvements in traffic management can lead to smoother traffic flow, reduced travel times, and ultimately, diminished congestion in urban areas.</p></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772586324000534/pdfft?md5=9d880b6e35f44d43c139dc4a2f00a4c4&pid=1-s2.0-S2772586324000534-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}