Pub Date : 2025-03-01DOI: 10.1016/j.multra.2025.100195
Mason D. Gemar , Shidong Pan , Zhanmin Zhang , Randy B. Machemehl
Over the past decade, many municipalities have begun to replace incandescent lamps in their traffic signals with light emitting diode (LED) arrays. While LED technology boasts longer lifetimes and superior performance over their counterparts, there are many limitations involved in both testing and evaluating their reliability. As such, the methodology and subsequent analysis procedures used to evaluate the reliability of traffic signal lamps along a corridor is proposed. To accomplish this task, the progression of the reliability assessment from individual lamp to the entire signal light system for a corridor is demonstrated. Furthermore, due to the nature of these systems and reliability assessment strategies, it is suggested that fuzzy, or more specifically, profust reliability theory could be applied to effectively analyze LED arrays, as well as corridor-wide signal light systems. Preliminary case study results, coupled with field observations of partially burned-out LED arrays, support this hypothesis.
{"title":"Fuzzy reliability theory analysis of traffic signal lamp performance","authors":"Mason D. Gemar , Shidong Pan , Zhanmin Zhang , Randy B. Machemehl","doi":"10.1016/j.multra.2025.100195","DOIUrl":"10.1016/j.multra.2025.100195","url":null,"abstract":"<div><div>Over the past decade, many municipalities have begun to replace incandescent lamps in their traffic signals with light emitting diode (LED) arrays. While LED technology boasts longer lifetimes and superior performance over their counterparts, there are many limitations involved in both testing and evaluating their reliability. As such, the methodology and subsequent analysis procedures used to evaluate the reliability of traffic signal lamps along a corridor is proposed. To accomplish this task, the progression of the reliability assessment from individual lamp to the entire signal light system for a corridor is demonstrated. Furthermore, due to the nature of these systems and reliability assessment strategies, it is suggested that fuzzy, or more specifically, profust reliability theory could be applied to effectively analyze LED arrays, as well as corridor-wide signal light systems. Preliminary case study results, coupled with field observations of partially burned-out LED arrays, support this hypothesis.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 1","pages":"Article 100195"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143509645","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}
Pub Date : 2025-02-13DOI: 10.1016/j.multra.2025.100208
Lalit Swami, Mokaddes Ali Ahmed, Suprava Jena
As shared mobility options like ridesourcing services continue to reshape urban transportation systems globally, their impact on airport ground access has become increasingly significant. This study investigates the changing dynamics of airport access at Lokpriya Gopinath Bordoloi International Airport (LGBI) in Guwahati, India, amidst the growing presence of ridesourcing services. A total of 700 air passengers were surveyed using a random sampling technique over 15 consecutive days, providing comprehensive data for the analysis. A multinomial logit (MNL) model was employed to examine factors influencing mode choice, considering variables such as age, residential status, group size, car ownership, luggage, safety, and convenience. The model explains 48.2 % to 57.2 % of the variation in mode choice. The results reveal that younger passengers (aged 21–30) are 2.14 times more likely to choose ridesourcing services. Additionally, visitors are significantly more inclined to use ridesourcing services compared to locals, with an odds ratio of 2.56. While passengers with car ownership are 5.43 times more likely to prefer private vehicles. The study underscores the growing significance of ridesourcing services in airport ground access and highlights the need for transportation planning and policymaking to adapt to these evolving trends.
{"title":"The evolving dynamics of airport ground access: A multinomial logit analysis of mode choice at Guwahati Airport, India","authors":"Lalit Swami, Mokaddes Ali Ahmed, Suprava Jena","doi":"10.1016/j.multra.2025.100208","DOIUrl":"10.1016/j.multra.2025.100208","url":null,"abstract":"<div><div>As shared mobility options like ridesourcing services continue to reshape urban transportation systems globally, their impact on airport ground access has become increasingly significant. This study investigates the changing dynamics of airport access at Lokpriya Gopinath Bordoloi International Airport (LGBI) in Guwahati, India, amidst the growing presence of ridesourcing services. A total of 700 air passengers were surveyed using a random sampling technique over 15 consecutive days, providing comprehensive data for the analysis. A multinomial logit (MNL) model was employed to examine factors influencing mode choice, considering variables such as age, residential status, group size, car ownership, luggage, safety, and convenience. The model explains 48.2 % to 57.2 % of the variation in mode choice. The results reveal that younger passengers (aged 21–30) are 2.14 times more likely to choose ridesourcing services. Additionally, visitors are significantly more inclined to use ridesourcing services compared to locals, with an odds ratio of 2.56. While passengers with car ownership are 5.43 times more likely to prefer private vehicles. The study underscores the growing significance of ridesourcing services in airport ground access and highlights the need for transportation planning and policymaking to adapt to these evolving trends.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 2","pages":"Article 100208"},"PeriodicalIF":0.0,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143527555","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}
Pub Date : 2025-02-12DOI: 10.1016/j.multra.2025.100207
Yuyan Annie Pan , Fuliang Li , Anran Li , Zhiqiang Niu , Zhen Liu
Accurate traffic flow forecasting at urban intersections is critical for optimizing transportation infrastructure and reducing congestion. This manuscript introduces a novel framework, the Physics-Guided Spatio-Temporal Graph Neural Network (PG-STGNN), specifically designed for traffic flow prediction. By integrating the principles of traffic flow physics with advanced spatio-temporal graph neural network algorithms, the framework captures complex spatio-temporal dependencies in traffic networks. PG-STGNN adopts a stepwise approach, addressing key performance metrics like queue formation and signal timing complexities at intersections. To validate its effectiveness, the model was applied to real-world traffic data from the Yizhuang District of Beijing. Compared to traditional models such as ARIMA, KNN, and Random Forest, PG-STGNN significantly improves prediction accuracy, achieving MAPE reductions of 19.9 %, 18.6 %, 6.1 %, 20.7 %, 5.0 %, 1.8 %, and 1.1 % against KNN, ARIMA, RF, BP, T-GCN, STGCN, and ST-ED-RMGC, respectively. With the lowest MAPE (9.452 %), MAE (2.485), and RMSE (4.364), PG-STGNN demonstrates superior prediction performance. These results underscore its potential to provide reliable short-term traffic forecasts, offering essential insights for the strategic planning and management of urban intelligent transportation systems.
{"title":"Urban intersection traffic flow prediction: A physics-guided stepwise framework utilizing spatio-temporal graph neural network algorithms","authors":"Yuyan Annie Pan , Fuliang Li , Anran Li , Zhiqiang Niu , Zhen Liu","doi":"10.1016/j.multra.2025.100207","DOIUrl":"10.1016/j.multra.2025.100207","url":null,"abstract":"<div><div>Accurate traffic flow forecasting at urban intersections is critical for optimizing transportation infrastructure and reducing congestion. This manuscript introduces a novel framework, the Physics-Guided Spatio-Temporal Graph Neural Network (PG-STGNN), specifically designed for traffic flow prediction. By integrating the principles of traffic flow physics with advanced spatio-temporal graph neural network algorithms, the framework captures complex spatio-temporal dependencies in traffic networks. PG-STGNN adopts a stepwise approach, addressing key performance metrics like queue formation and signal timing complexities at intersections. To validate its effectiveness, the model was applied to real-world traffic data from the Yizhuang District of Beijing. Compared to traditional models such as ARIMA, KNN, and Random Forest, PG-STGNN significantly improves prediction accuracy, achieving MAPE reductions of 19.9 %, 18.6 %, 6.1 %, 20.7 %, 5.0 %, 1.8 %, and 1.1 % against KNN, ARIMA, RF, BP, T-GCN, STGCN, and ST-ED-RMGC, respectively. With the lowest MAPE (9.452 %), MAE (2.485), and RMSE (4.364), PG-STGNN demonstrates superior prediction performance. These results underscore its potential to provide reliable short-term traffic forecasts, offering essential insights for the strategic planning and management of urban intelligent transportation systems.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 2","pages":"Article 100207"},"PeriodicalIF":0.0,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479107","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}
Pub Date : 2025-02-12DOI: 10.1016/j.multra.2025.100206
Sixuan Xu , Xinbo Xie , Chen Wang , Junyi Yan
Among the factors related to traffic crash risk, the speed characteristics are crucial. Most studies on the safety effect of speed characteristics focused on highways and rural roads, whereas the investigations on urban roads are not comprehensive. Urban arterials operate at higher speeds during off-peak hours, which may possibly lead to more serious crashes. Hence, this study focuses on the correlation between speed characteristics and serious crash occurrence (i.e., injuries and fatalities) on urban arterials during off-peak hours, while considering the interaction between speed and road/traffic characteristics. The spatial autocorrelation and intrinsic correlation of injury and fatal crashes are analyzed by using multivariate conditional autoregressive model (MVCAR) from 12 urban arterials in a district in Ningbo, China. Research findings include: (1) speed characteristics, including the percentage of speeding vehicles, mean speed, speed standard deviation, speed skewness, were found as significant and the inclusion of interaction terms of speed characteristics improved the model fit; (2) the interaction terms of percentage of speeding vehicles with the presence of median and access density, speed skewness with access density showed significant effects; (3) the interaction term of mean speed and access density are positively correlated with crash risk; (4) Speed standard deviation is positively correlated with crash risk. The findings can provide guidance for improving urban speed management and safety.
{"title":"On the safety effects of off-peak hour speed characteristics of urban arterials","authors":"Sixuan Xu , Xinbo Xie , Chen Wang , Junyi Yan","doi":"10.1016/j.multra.2025.100206","DOIUrl":"10.1016/j.multra.2025.100206","url":null,"abstract":"<div><div>Among the factors related to traffic crash risk, the speed characteristics are crucial. Most studies on the safety effect of speed characteristics focused on highways and rural roads, whereas the investigations on urban roads are not comprehensive. Urban arterials operate at higher speeds during off-peak hours, which may possibly lead to more serious crashes. Hence, this study focuses on the correlation between speed characteristics and serious crash occurrence (i.e., injuries and fatalities) on urban arterials during off-peak hours, while considering the interaction between speed and road/traffic characteristics. The spatial autocorrelation and intrinsic correlation of injury and fatal crashes are analyzed by using multivariate conditional autoregressive model (MVCAR) from 12 urban arterials in a district in Ningbo, China. Research findings include: (1) speed characteristics, including the percentage of speeding vehicles, mean speed, speed standard deviation, speed skewness, were found as significant and the inclusion of interaction terms of speed characteristics improved the model fit; (2) the interaction terms of percentage of speeding vehicles with the presence of median and access density, speed skewness with access density showed significant effects; (3) the interaction term of mean speed and access density are positively correlated with crash risk; (4) Speed standard deviation is positively correlated with crash risk. The findings can provide guidance for improving urban speed management and safety.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 2","pages":"Article 100206"},"PeriodicalIF":0.0,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552975","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}
Pub Date : 2025-02-11DOI: 10.1016/j.multra.2025.100205
Graham Currie , Alexa Delbosc , Ryan Cox , Mahesha Jayawardhena , James Reynolds
This paper explores how public transport and shared e-scooter travel interact. Trip end travel patterns of shared e-scooter users are explored in relation to Public Transport service levels. An index measuring transit service level is developed. This is compared to spatial and temporal patterns of e-scooter trip ends to explore the hypothesis that e-scooter use is stronger in areas where inner area transit offers a poorer quality service i.e. are e-scooters acting as a ‘gap filler’ to transit providing first-last mile access to transit?
Analysis methodologies including comparative spatial and temporal mapping of service level and trip end concentrations supported by statistical tests. A novel approach is also adopted to compare PT service level at each e-scooter trip end which identifies potential first-last mile and gap filling e-scooter trips from a large trip end database.
Results show e-scooter trip ends are concentrated in areas and at times when transit service levels are highest. This suggests that shared e-scooters may be competing with transit service rather than filling service gaps. We therefore conclude that the hypothesis that e-scooters act as a ‘gap filler’ for areas of low transit use is not supported.
Nevertheless, we have found limited and specific evidence of times and areas where ‘gap filling’ and first-last mile trips are apparent. Night time, early morning and weekend e-scooter travel volume is high when transit service levels are low. We also found limited evidence of spatial gaps in transit where first-last mile rail access was occurring and some evidence that rail-linked e-scooter travel was from lower service level trip ends and that these patterns increased with e-scooter trip distance.
{"title":"Exploring shared e-scooter trip patterns and links to public transport service level","authors":"Graham Currie , Alexa Delbosc , Ryan Cox , Mahesha Jayawardhena , James Reynolds","doi":"10.1016/j.multra.2025.100205","DOIUrl":"10.1016/j.multra.2025.100205","url":null,"abstract":"<div><div>This paper explores how public transport and shared e-scooter travel interact. Trip end travel patterns of shared e-scooter users are explored in relation to Public Transport service levels. An index measuring transit service level is developed. This is compared to spatial and temporal patterns of e-scooter trip ends to explore the hypothesis that e-scooter use is stronger in areas where inner area transit offers a poorer quality service i.e. are e-scooters acting as a ‘gap filler’ to transit providing first-last mile access to transit?</div><div>Analysis methodologies including comparative spatial and temporal mapping of service level and trip end concentrations supported by statistical tests. A novel approach is also adopted to compare PT service level at each e-scooter trip end which identifies potential first-last mile and gap filling e-scooter trips from a large trip end database.</div><div>Results show e-scooter trip ends are concentrated in areas and at times when transit service levels are highest. This suggests that shared e-scooters may be competing with transit service rather than filling service gaps. We therefore conclude that the hypothesis that e-scooters act as a ‘gap filler’ for areas of low transit use is not supported.</div><div>Nevertheless, we have found limited and specific evidence of times and areas where ‘gap filling’ and first-last mile trips are apparent. Night time, early morning and weekend e-scooter travel volume is high when transit service levels are low. We also found limited evidence of spatial gaps in transit where first-last mile rail access was occurring and some evidence that rail-linked e-scooter travel was from lower service level trip ends and that these patterns increased with e-scooter trip distance.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 2","pages":"Article 100205"},"PeriodicalIF":0.0,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143444355","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}
Pub Date : 2025-01-29DOI: 10.1016/j.multra.2025.100204
Sofia Suárez , Eloisa Macedo , Gennaro Ciccarelli , Jorge M. Bandeira
Mobility-as-a-Service (MaaS) is viewed as a prospective approach to encourage sustainable mobility. To ensure the effectiveness of MaaS subscription plans, continuous feedback and communication with users are crucial. The objective of this study is to develop a methodology for designing region-focused MaaS bundles and assess their viability through end-user's feedback and its potential for increasing users’ uptake of more sustainable travel. To explore user willingness to adopt the suggested MaaS bundles and estimate net changes in carbon dioxide (CO2) and nitrogen oxide (NOx) emissions, stated preference surveys (SPS) were conducted in the Portuguese cities of Aveiro and Coimbra. Results suggest a preference for bundles offering unlimited travel on public transport and, due to the efficient public transport network in Coimbra, the willingness to use such bundles was higher than for Aveiro. In an optimistic scenario, average emission savings of 35 % for CO2 and 30 % for NOx emissions, specifically for the most frequent trips, were found. In a realistic scenario with values adjusted to revealed preferences, these reductions drop to 5 % for CO2 and 4 % for NOx. Overall, our research highlights the complexities associated with behavioural changes and underscores the importance of policies that consider the intricacies of human behaviour. Furthermore, the findings regarding the introduction of MaaS bundles emphasize the pivotal role of a robust PT system in driving changes in travel behaviour among the population, contributing to mitigating the negative effects of unsustainable, carbon-dependent travel choices.
{"title":"User feedback assessment of region-focused mobility-as-a-service bundles","authors":"Sofia Suárez , Eloisa Macedo , Gennaro Ciccarelli , Jorge M. Bandeira","doi":"10.1016/j.multra.2025.100204","DOIUrl":"10.1016/j.multra.2025.100204","url":null,"abstract":"<div><div>Mobility-as-a-Service (MaaS) is viewed as a prospective approach to encourage sustainable mobility. To ensure the effectiveness of MaaS subscription plans, continuous feedback and communication with users are crucial. The objective of this study is to develop a methodology for designing region-focused MaaS bundles and assess their viability through end-user's feedback and its potential for increasing users’ uptake of more sustainable travel. To explore user willingness to adopt the suggested MaaS bundles and estimate net changes in carbon dioxide (CO<sub>2</sub>) and nitrogen oxide (NOx) emissions, stated preference surveys (SPS) were conducted in the Portuguese cities of Aveiro and Coimbra. Results suggest a preference for bundles offering unlimited travel on public transport and, due to the efficient public transport network in Coimbra, the willingness to use such bundles was higher than for Aveiro. In an optimistic scenario, average emission savings of 35 % for CO<sub>2</sub> and 30 % for NOx emissions, specifically for the most frequent trips, were found. In a realistic scenario with values adjusted to revealed preferences, these reductions drop to 5 % for CO<sub>2</sub> and 4 % for NOx. Overall, our research highlights the complexities associated with behavioural changes and underscores the importance of policies that consider the intricacies of human behaviour. Furthermore, the findings regarding the introduction of MaaS bundles emphasize the pivotal role of a robust PT system in driving changes in travel behaviour among the population, contributing to mitigating the negative effects of unsustainable, carbon-dependent travel choices.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 2","pages":"Article 100204"},"PeriodicalIF":0.0,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143474515","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}
Pub Date : 2025-01-18DOI: 10.1016/j.multra.2025.100201
Deepjyoti Das , Aditya Saxena
Shipping sector is vital to Indian economy, making it crucial to understand the economic impact of the COVID-19 pandemic on port operations to develop strategies for future resilience. This study examines the effects of COVID-19 on Deendayal Port, a key Indian port, by analyzing freight volume, revenue, and expenditure data from April 2012 to October 2022. Autoregressive Integrated Moving Average (ARIMA) modeling covers pre-COVID, two COVID-19 waves, and post-COVID scenarios. Ordinary Least Squares (OLS) regression models for revenue and expenditure evaluate economic losses. The results show 6.2% decline in freight volume during the first wave, with a decrease from 123.4 million tons (Mt) to 115.8 Mt, leading to a monthly average loss of 0.6 Mt. The second wave saw recovery, with freight volume increasing from the forecasted 127.6 Mt to 129.6 Mt, resulting in a monthly gain of 0.2 Mt. Revenue losses during wave 1 were 215 crore INR, while wave 2 saw a revenue increase of 57 crore INR. The study highlights the importance of operational efficiency and managing key cost drivers like volume and manpower to maintain financial stability. These findings lay a foundation for future research to strengthen the shipping industry's resilience and sustainability in post-pandemic world.
{"title":"Effect of COVID-19 pandemic on freight volume, revenue and expenditure of deendayal port in India: An ARIMA forecasting model","authors":"Deepjyoti Das , Aditya Saxena","doi":"10.1016/j.multra.2025.100201","DOIUrl":"10.1016/j.multra.2025.100201","url":null,"abstract":"<div><div>Shipping sector is vital to Indian economy, making it crucial to understand the economic impact of the COVID-19 pandemic on port operations to develop strategies for future resilience. This study examines the effects of COVID-19 on Deendayal Port, a key Indian port, by analyzing freight volume, revenue, and expenditure data from April 2012 to October 2022. Autoregressive Integrated Moving Average (ARIMA) modeling covers pre-COVID, two COVID-19 waves, and post-COVID scenarios. Ordinary Least Squares (OLS) regression models for revenue and expenditure evaluate economic losses. The results show 6.2% decline in freight volume during the first wave, with a decrease from 123.4 million tons (Mt) to 115.8 Mt, leading to a monthly average loss of 0.6 Mt. The second wave saw recovery, with freight volume increasing from the forecasted 127.6 Mt to 129.6 Mt, resulting in a monthly gain of 0.2 Mt. Revenue losses during wave 1 were 215 crore INR, while wave 2 saw a revenue increase of 57 crore INR. The study highlights the importance of operational efficiency and managing key cost drivers like volume and manpower to maintain financial stability. These findings lay a foundation for future research to strengthen the shipping industry's resilience and sustainability in post-pandemic world.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 2","pages":"Article 100201"},"PeriodicalIF":0.0,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143099536","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}
Pub Date : 2025-01-17DOI: 10.1016/j.multra.2025.100200
Sangen Hu , Zikang Huang , Ke Wang , Haiyuan Lin , Mingyang Pei
Flying cars, a symbol of Urban Air Mobility (UAM), signify a pivotal step in revolutionizing urban transportation and play a pivotal role in shaping future transport systems. To enhance travelers' willingness to accept flying cars and promote the widespread adoption of this novel transportation mode, this study develops a comprehensive model to explore key factors determining the public's acceptance of flying cars by integrating the Technology Acceptance Model, Risk Perception Theory, and Trust Theory. The validity of the model was confirmed through a rigorous structure equation modeling analysis, utilizing 553 sample data collected from a network questionnaire survey across a diverse demographic of the Chinese market. Results revealed significant associations between the intention to use flying cars and various factors, including attitudes towards usage, perceived usefulness, and personal innovativeness. Heterogeneity analysis further uncovered how demographic factors (such as age, gender, education, and possession of a driver's license) impacted perceptions and acceptance. As the study concludes, despite general optimism, public acceptance of flying cars is strongly influenced by factors such as cost, safety, and privacy concerns play crucial roles in public acceptance. The insights from this study provide valuable implications for manufacturers, policymakers, and marketers in strategizing the introduction and promotion of flying cars.
{"title":"Modeling the adoption of urban air mobility based on technology acceptance and risk perception theories: A case study on flying cars","authors":"Sangen Hu , Zikang Huang , Ke Wang , Haiyuan Lin , Mingyang Pei","doi":"10.1016/j.multra.2025.100200","DOIUrl":"10.1016/j.multra.2025.100200","url":null,"abstract":"<div><div>Flying cars, a symbol of Urban Air Mobility (UAM), signify a pivotal step in revolutionizing urban transportation and play a pivotal role in shaping future transport systems. To enhance travelers' willingness to accept flying cars and promote the widespread adoption of this novel transportation mode, this study develops a comprehensive model to explore key factors determining the public's acceptance of flying cars by integrating the Technology Acceptance Model, Risk Perception Theory, and Trust Theory. The validity of the model was confirmed through a rigorous structure equation modeling analysis, utilizing 553 sample data collected from a network questionnaire survey across a diverse demographic of the Chinese market. Results revealed significant associations between the intention to use flying cars and various factors, including attitudes towards usage, perceived usefulness, and personal innovativeness. Heterogeneity analysis further uncovered how demographic factors (such as age, gender, education, and possession of a driver's license) impacted perceptions and acceptance. As the study concludes, despite general optimism, public acceptance of flying cars is strongly influenced by factors such as cost, safety, and privacy concerns play crucial roles in public acceptance. The insights from this study provide valuable implications for manufacturers, policymakers, and marketers in strategizing the introduction and promotion of flying cars.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 2","pages":"Article 100200"},"PeriodicalIF":0.0,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143099537","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}
Pub Date : 2025-01-15DOI: 10.1016/j.multra.2025.100198
Ehsan Amirnazmiafshar , Marco Diana
This study investigates perception gaps among stakeholders—policy-makers, operators, users, and non-users—regarding car-sharing, bike-sharing, and scooter-sharing systems in Turin, Italy. Based on 628 surveys collected between November 2021 and February 2022 and analyzed using the Bayesian Best-Worst Method (BWM) multicriteria technique, it highlights key differences in prioritizing factors influencing shared mobility demand.
Key Findings: For car-sharing, policy-makers overestimate the importance of trip purpose compared to both users and non-users, while undervaluing service availability. Operators undervalue trip-related factors, such as travel time and departure time, while overemphasizing user-friendliness. For bike-sharing, policy-makers overestimate travel time compared to users while undervaluing travel comfort and environmental friendliness compared to both users and non-users. Operators underestimate trip-related factors, including travel distance and trip purpose, while overemphasizing environmental friendliness, particularly compared to non-users. For scooter-sharing, policy-makers underestimate trip-related characteristics, such as travel time and departure time, while overestimating travel cost and user-friendliness compared to non-users. Operators undervalue travel comfort and service availability, while overestimating travel distance, especially compared to users.
Managerial Insights: For car-sharing, policy-makers should expand service coverage and incentivize vehicle deployment, while operators should use dynamic fleet management and offer flexible booking options. For bike-sharing, policy-makers should subsidize fleet expansion and improve infrastructure, while operators should transition to free-floating models and integrate navigation tools. For scooter-sharing, policy-makers should enforce safety standards and improve accessibility, while operators should invest in high-quality scooters and adopt competitive pricing models.
Bridging these perception gaps is essential for fostering shared mobility adoption and enhancing user satisfaction.
{"title":"Mind the perception gap: Identifying differences in views among stakeholder groups of shared mobility services through bayesian best-worst method","authors":"Ehsan Amirnazmiafshar , Marco Diana","doi":"10.1016/j.multra.2025.100198","DOIUrl":"10.1016/j.multra.2025.100198","url":null,"abstract":"<div><div>This study investigates perception gaps among stakeholders—policy-makers, operators, users, and non-users—regarding car-sharing, bike-sharing, and scooter-sharing systems in Turin, Italy. Based on 628 surveys collected between November 2021 and February 2022 and analyzed using the Bayesian Best-Worst Method (BWM) multicriteria technique, it highlights key differences in prioritizing factors influencing shared mobility demand.</div><div>Key Findings: For car-sharing, policy-makers overestimate the importance of trip purpose compared to both users and non-users, while undervaluing service availability. Operators undervalue trip-related factors, such as travel time and departure time, while overemphasizing user-friendliness. For bike-sharing, policy-makers overestimate travel time compared to users while undervaluing travel comfort and environmental friendliness compared to both users and non-users. Operators underestimate trip-related factors, including travel distance and trip purpose, while overemphasizing environmental friendliness, particularly compared to non-users. For scooter-sharing, policy-makers underestimate trip-related characteristics, such as travel time and departure time, while overestimating travel cost and user-friendliness compared to non-users. Operators undervalue travel comfort and service availability, while overestimating travel distance, especially compared to users.</div><div>Managerial Insights: For car-sharing, policy-makers should expand service coverage and incentivize vehicle deployment, while operators should use dynamic fleet management and offer flexible booking options. For bike-sharing, policy-makers should subsidize fleet expansion and improve infrastructure, while operators should transition to free-floating models and integrate navigation tools. For scooter-sharing, policy-makers should enforce safety standards and improve accessibility, while operators should invest in high-quality scooters and adopt competitive pricing models.</div><div>Bridging these perception gaps is essential for fostering shared mobility adoption and enhancing user satisfaction.</div></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":"4 2","pages":"Article 100198"},"PeriodicalIF":0.0,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143099538","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}
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