Rapid urbanization and shifting demographics worldwide necessitate innovative urban transportation solutions.Shared micromobility systems,such as bicycle-and scooter-sharing programs,have emerged as promising alternat...Rapid urbanization and shifting demographics worldwide necessitate innovative urban transportation solutions.Shared micromobility systems,such as bicycle-and scooter-sharing programs,have emerged as promising alternatives to traditional urban mobility challenges.This study delves into the complexity of shared micromobility fleet development,focusing on the interplay between fleet size,user demand,regulatory frameworks,economic viability,and public engagement.By employing a system dynamics modeling approach that incorporates causal loop diagrams(CLDs)and stock and flow models(SFMs),we explore various policy scenarios to optimize micromobility management systems.Our findings reveal that financial incentives,such as fee reductions and government subsidies,significantly increase user adoption and profitability,whereas increased operational fees necessitate a delicate balance between cost management and service attractiveness.Sensitivity and uncertainty analyses highlight critical parameters for effective fleet management.This research offers actionable insights for policymakers and operators,promoting sustainable urban transport systems.展开更多
This paper aims aimed at evaluating the potential for micromobility in South Florida.The influential factors motivating users to switch to micromobility modes are investigated,utilizing a stated preference(SP)approach...This paper aims aimed at evaluating the potential for micromobility in South Florida.The influential factors motivating users to switch to micromobility modes are investigated,utilizing a stated preference(SP)approach.The survey collected information on respondents’socioeconomic and demographic characteristics,current modes of transportation,and mobility attitudes.Additionally,trip attributes for a recent journey were gathered to construct the SP scenarios.Analyzing the survey data using a mixed logit(ML)model revealed significant variables that influence users’mode choice.The findings indicate that micromobility options are more likely to be adopted by younger,well-educated,and lower-income individuals,particularly students.Positive perceptions towards micromobility modes,alternative modes,and supportive infrastructure(e.g.,ample bike lanes and parking facilities)serve as key motivators for individuals considering a switch to micromobility.Conversely,individuals who prefer vehicle ownership are less inclined to choose micromobility,and perceived reliability of micromobility plays a crucial role in discouraging its adoption.Nevertheless,improving infrastructure support and service design can help counter this effect,especially in offering safe alternatives for congested areas.Moreover,those expressing concerns about environmental impacts are more inclined to consider micromobility,suggesting that emphasizing the environmental benefits could promote greater usage of micromobility services.展开更多
In recent years,e-scooters have been introduced in many European cities.In several places we have witnessed a rapid uptake of this new mode of transport mainly as a result of public sharing schemes.A number of inciden...In recent years,e-scooters have been introduced in many European cities.In several places we have witnessed a rapid uptake of this new mode of transport mainly as a result of public sharing schemes.A number of incidents,injuries and even fatalities have given rise to questions regarding the safety of these vehicles.These questions are being researched mainly using official crash data and data specifying injuries and hospital treatment.Until now,the research has focused on investigating typical injury patterns and estimating risk levels.Very little is known about exactly where conflicts and crashes occur.Knowledge of hazard hotspots is crucial when investigating risk levels and improving safety for all road users.Hence,this paper develops an approach to investigating locations with potentially dangerous interactions within the active mobility system in the city of Berlin.The approach consists of explorative expert interviews,an online poll,and quantitative analyses.For the latter we combine three datasets.First,we research crash hotspots using official data.Second,we use data based on acceleration sensors from cyclists'smartphones to find locations of sudden movements.Third,we use trip data from the operators of escooter sharing systems.The information gathered is used in a conclusive expert workshop to identify hazard hotspots.Results show that many of the conflicts with pedestrians are caused by parked escooters.Second,e-scooter trips are concentrated in the inner city and along specific routes.In moving traffic,various data sources are used to identify hotspots at intersections and in areas between intersections.The present research lays the foundation for important further studies to investigate interactions at hotspots in detail by determining nine specific locations in the city of Berlin.展开更多
E-scooter sharing services have grown exponentially in many cities of the world within the last 10 years, mainly with the goal to serve first/last mile trips. Compared to other shared mobility modes (e.g., autonomous ...E-scooter sharing services have grown exponentially in many cities of the world within the last 10 years, mainly with the goal to serve first/last mile trips. Compared to other shared mobility modes (e.g., autonomous buses and electric taxis), for which Agent-based Models (ABMs) have been applied in many cases, just a few studies attempted to simulate e-scooter trips. This study aims to bridge the gap between ABMs and e-scooter sharing services by reviewing the existing ABMs and conducting a qualitative assessment. Initially, existing ABMs are described based on ten descriptors. To test suitability of each model for simulating e-scooter sharing services, we developed an evaluation checklist based on empirical findings. The ten criteria refer to the capabilities of each model to (a) adjust in new challenges via an open-source code, (b) model shared mobility modes, (c) perform large scale simulation, (d) describe spatiotemporal variation of demand, (e) simulate bicycle, (f) pedestrian, and (g) mixed traffic (h) consider socio-demographic characteristics, (i) integrate new choice models, and (j) model multimodal trips. Our results reveal the advantages and disadvantages of each model in simulating flexible transport modes and services. We end up with a dilemma or a scalability problem: to model e-scooter riding behavior in link level or e-scooter services in network level. It is concluded that the dual behavior of e-scooter users (pedestrian or vehicle) poses new challenges that can be met through the development of new extensions or hybrid simulation models.展开更多
基金FFG/BMK Endowed Professor DAVeMoS program.Importantly,this research also received support from the Indonesia-Austria Scholarship Program(IASP),a program organized by OeAD—Austria's Agency for Education and Internationalization—and funded by the Directorate of Resources,Directorate General of Higher Education,Ministry of Education and Culture in Indonesia(KEMDIKBUD)(MPC-2022—05864).
文摘Rapid urbanization and shifting demographics worldwide necessitate innovative urban transportation solutions.Shared micromobility systems,such as bicycle-and scooter-sharing programs,have emerged as promising alternatives to traditional urban mobility challenges.This study delves into the complexity of shared micromobility fleet development,focusing on the interplay between fleet size,user demand,regulatory frameworks,economic viability,and public engagement.By employing a system dynamics modeling approach that incorporates causal loop diagrams(CLDs)and stock and flow models(SFMs),we explore various policy scenarios to optimize micromobility management systems.Our findings reveal that financial incentives,such as fee reductions and government subsidies,significantly increase user adoption and profitability,whereas increased operational fees necessitate a delicate balance between cost management and service attractiveness.Sensitivity and uncertainty analyses highlight critical parameters for effective fleet management.This research offers actionable insights for policymakers and operators,promoting sustainable urban transport systems.
基金sponsored by the United States Department of Transportation Office of the Assistant Secretary for Research and Technology(OST-R)through the Southeastern Transportation Research,Innovation,Development,and Education Center(Project D4).
文摘This paper aims aimed at evaluating the potential for micromobility in South Florida.The influential factors motivating users to switch to micromobility modes are investigated,utilizing a stated preference(SP)approach.The survey collected information on respondents’socioeconomic and demographic characteristics,current modes of transportation,and mobility attitudes.Additionally,trip attributes for a recent journey were gathered to construct the SP scenarios.Analyzing the survey data using a mixed logit(ML)model revealed significant variables that influence users’mode choice.The findings indicate that micromobility options are more likely to be adopted by younger,well-educated,and lower-income individuals,particularly students.Positive perceptions towards micromobility modes,alternative modes,and supportive infrastructure(e.g.,ample bike lanes and parking facilities)serve as key motivators for individuals considering a switch to micromobility.Conversely,individuals who prefer vehicle ownership are less inclined to choose micromobility,and perceived reliability of micromobility plays a crucial role in discouraging its adoption.Nevertheless,improving infrastructure support and service design can help counter this effect,especially in offering safe alternatives for congested areas.Moreover,those expressing concerns about environmental impacts are more inclined to consider micromobility,suggesting that emphasizing the environmental benefits could promote greater usage of micromobility services.
基金funded by the German Federal Ministry for Digital and Transport using resources from the National Cycling Plan 2020(NRVP)。
文摘In recent years,e-scooters have been introduced in many European cities.In several places we have witnessed a rapid uptake of this new mode of transport mainly as a result of public sharing schemes.A number of incidents,injuries and even fatalities have given rise to questions regarding the safety of these vehicles.These questions are being researched mainly using official crash data and data specifying injuries and hospital treatment.Until now,the research has focused on investigating typical injury patterns and estimating risk levels.Very little is known about exactly where conflicts and crashes occur.Knowledge of hazard hotspots is crucial when investigating risk levels and improving safety for all road users.Hence,this paper develops an approach to investigating locations with potentially dangerous interactions within the active mobility system in the city of Berlin.The approach consists of explorative expert interviews,an online poll,and quantitative analyses.For the latter we combine three datasets.First,we research crash hotspots using official data.Second,we use data based on acceleration sensors from cyclists'smartphones to find locations of sudden movements.Third,we use trip data from the operators of escooter sharing systems.The information gathered is used in a conclusive expert workshop to identify hazard hotspots.Results show that many of the conflicts with pedestrians are caused by parked escooters.Second,e-scooter trips are concentrated in the inner city and along specific routes.In moving traffic,various data sources are used to identify hotspots at intersections and in areas between intersections.The present research lays the foundation for important further studies to investigate interactions at hotspots in detail by determining nine specific locations in the city of Berlin.
基金This research has been co-financed by the European Union and Greece,National Strategic Reference Framework 2014-2020(NSRF),through the Operational Program Competitiveness,Entrepreneurship and Innovation,under the call RESEARCH–CREATE–INNOVATE(project code:T2EDK-02494).
文摘E-scooter sharing services have grown exponentially in many cities of the world within the last 10 years, mainly with the goal to serve first/last mile trips. Compared to other shared mobility modes (e.g., autonomous buses and electric taxis), for which Agent-based Models (ABMs) have been applied in many cases, just a few studies attempted to simulate e-scooter trips. This study aims to bridge the gap between ABMs and e-scooter sharing services by reviewing the existing ABMs and conducting a qualitative assessment. Initially, existing ABMs are described based on ten descriptors. To test suitability of each model for simulating e-scooter sharing services, we developed an evaluation checklist based on empirical findings. The ten criteria refer to the capabilities of each model to (a) adjust in new challenges via an open-source code, (b) model shared mobility modes, (c) perform large scale simulation, (d) describe spatiotemporal variation of demand, (e) simulate bicycle, (f) pedestrian, and (g) mixed traffic (h) consider socio-demographic characteristics, (i) integrate new choice models, and (j) model multimodal trips. Our results reveal the advantages and disadvantages of each model in simulating flexible transport modes and services. We end up with a dilemma or a scalability problem: to model e-scooter riding behavior in link level or e-scooter services in network level. It is concluded that the dual behavior of e-scooter users (pedestrian or vehicle) poses new challenges that can be met through the development of new extensions or hybrid simulation models.
