Bicycle mode share in China: a city-level analysis of long term trends

In the past 15 years, cities in China have experienced big changes in socioeconomic and traffic conditions, resulting in a long term change in bicycle use. This study aims to quantify the changes in bicycle mode share in Chinese cities and explore the potential causes. Based on data from 51 cities, it is found that bicycle mode share at the city level decreased gradually in the past. Conventional bicycle mode share decreased with a rate of 3 % per year, but electric bicycle mode share increased with a rate of 2 % per year. The correlations between city features such as demographics and built environments and bicycle mode share at different city sizes are compared. The generalized linear models are estimated to relate the changes in the share of different trip modes to various city-level factors. The results show that the bicycle mode share in a city is impacted by factors including city area size, population density, number of cars, percentage of local road mileage among all roads, and trip purpose. Possible reasons for the changes in bicycle uses in Chinese cities are explored and policy implications are discussed.     

Bicycle lane priority: Promoting bicycle as a green mode even in congested urban area

The main obstacles to boosting the bicycle as a mode of transport are safety concerns due to interactions with motorized traffic. One option is to separate cyclists from motorists through exclusive bicycle priority lanes. This practice is easily implemented in uncongested traffic. Enforcing bicycle lanes on congested roads may degenerate the network, making the idea very hard to sell both to the public and the traffic authorities. Inspired by Braess Paradox, we take an unorthodox approach to seeking latent misutilized capacity in the congested networks to be dedicated to exclusive bicycle lanes. The aim of this study is to tailor an efficient and practical method to large size urban networks. Hence, this paper appeals to policy makers in their quest to scientifically convince stakeholder that bicycle is not a secondary mode, rather, it can be greatly accommodated along with other modes even in the heart of the congested cities. In conjunction with the bicycle lane priority, other policy measures such as shared bicycle scheme, electric-bike, integration of public transport and bicycle are also discussed in this article. As for the mathematical methodology, we articulated it as a discrete bilevel mathematical programing. In order to handle the real networks, we developed a phased methodology based on Branch-and-Bound (as a solution algorithm), structured in a less intensive RAM manner. The methodology was tested on real size network of city of Winnipeg, Canada, for which the total of 30 road segments – equivalent to 2.77 km bicycle lanes – in the CBD were found.     

Symbolism in California’s early market for hybrid electric vehicles

This study explores the symbolic meanings being created, appropriated, and communicated by the owners of hybrid electric vehicles. As symbolic meanings are shown to be important to hybrid electric vehicle purchase and use, understanding the meanings, as well as their construction and communication, is essential for policy makers and others hoping to promote these new types of vehicles. Hybrid electric vehicles embody combinations of meanings that were previously unavailable from automobiles. Market observers who fail to recognize this struggle to explain why some people buy hybrid electric vehicles. They may characterize buyers as naı¨ve about calculating payback on fuel economy, or dismiss owners as image-seeking environmentalists. This research belies such simplistic explanations. Through the telling and analysis of buyers’ own stories, this study takes a robust approach to understanding the creation and spread of new symbolic meanings in the automotive market. Data were collected in ethnographic interviews with hybrid electric vehicle owners in the California, and analyzed using methods based on semiotic theory. In particular, the study explores how widely recognized social meanings (denotations) are connected to more personal meanings (connotations) and the effect that both types of meanings have on vehicle purchase and use.     

Bicycle commuting market analysis using attitudinal market segmentation approach

The market segmentation analysis for bicycle commuting can help identify distinct bicycle market segments and develop specific policies or strategies for increasing the bicycle usage in each segment. This study aims to use the approach of attitudinal market segmentation for identifying the potential markets of bicycle commuting. To achieve the research objective, the household survey is conducted to obtain the travelers’ attitudes towards their commuting travels. The factor analysis is used to explore the latent attitudes. The structural equation modeling (SEM) simultaneously estimates the correlations between the attitudinal factors. The K-means clustering is conducted to segment the bicycle commuting market into several submarkets. Finally, six segments of bicycle commuting market with distinct attitudes are identified by four dividing factors including the willingness to use bicycle, need for fixed schedule, desire for comfort, and environmental awareness. The attitudinal characteristics, socioeconomic features, and actual bicycle choices in each market segment are analyzed and compared. The policy implications that best serve the needs of each submarket are discussed to promote the bicycle commuting.     

Analyzing the transition from a public bicycle system to bicycle ownership: A complex relationship

Despite the success achieved by Public Bicycle Sharing Systems (PBSS) across the world, several researchers provide evidence on their limitations and constraints in a medium-long term, and bicycle ownership may be considered as a complementary tool to promote a ’bicycle-culture’. This paper aims to cover the gap about the interaction between both systems (public bicycle/private bicycle) and which are the key aspects to explain the bicycle-buying decision. After a fieldwork based on surveys conducted in Seville (Spain), one of the cities currently acknowledged worldwide for its successful policy of promoting cycling, we apply a Discrete Choice Model. Our findings show that among the socio-demographic factors that favor the move from the PBSS to the private bicycle are: having a higher level of education, being more progressive ideologically-speaking, and being a resident of the city itself; while age and gender do not appear to be conclusive. Experienced users, for whom the bicycle is a part of his/her healthy lifestyle, state a greater willingness to buy a bicycle. And the main obstacles to make the jump from the PBSS to the private bicycle, and that any action plan to support private bicycle usage should take into account, are: the lack of proper parking at the origin/destination, and fear of theft.     

I can’t believe your attitude: a joint estimation of best worst attitudes and electric vehicle choice

The number of conventionally fuelled motor vehicles in use is increasing worldwide despite warnings about finite fossil fuel and the detrimental impacts of burning such fuels. While electric vehicles, the subject of much research, generate far less emissions and offer the potential for power from renewable sources, they are yet to significantly penetrate the market. Tangible barriers such as price and vehicle range still exist, but consumer attitudes also drive behaviour. This paper examines attributes in a framework relatively new to transportation and energy policy; best–worst scaling. This method is widely considered an improvement over traditional methods of eliciting attitudes and beliefs, where respondents select attitudes they find best or worst from a set of attitudinal statements. To avoid potential endogeneity bias, we jointly model attitudes and choice for the first time with best–worst data. It is found that energy crisis, air quality and climate change concerns influence behaviour with respect to vehicle range and that travel behaviour change and forms of government incentives are needed influences on behaviour with respect to vehicle emissions. It is argued that correctly modelling attitudes reduces the error term of the vehicle choice model and provides policy makers with an improved lens for assessing behaviour. Additionally, the methods described within can easily be adapted to other policy scenarios.     

Exploring public bicycle network structure based on complex network theory and shortest path analysis: the public bicycle system in Yixing,China

A well-functioning public bicycle system relates not only to its mode of operation, vehicle allocation, rental station layout and vehicle leasing configuration, but also the bicycle network structure and its formation. However, the latter aspects have been widely overlooked in China. Here, we help to further attract more researchers to conduct relevant studies and make suggestions for the development of public bicycle transport in many small and medium-sized cities across the world. We demonstrate how to explore the public bicycle network structure of a county-level Chinese city – Yixing – known for its clay ware and tourism. We show that complex network theory and shortest path analysis technology are useful in characterizing the public bicycle network structure, in aspects such as network topology, the spatial distribution of sub-networks and traffic flows. Finally, the paper proposes relevant urban planning strategies.     

Influence of the weather on mode choice in corridors with time-varying congestion: a mixed data study

Studies that link human behaviour to the influence of weather have historically been conducted in such fields as tourism, marketing and leisure. In most studies that jointly examine weather and the mode of transport, only open-air transportation has been considered (for example, bicycle, motorcycle or walking). This focus, together with the habitual use of data collected with automatic devices and a lack of studies that analyse this issue using stated preference data, are the main reasons motivating this paper. This paper aims to analyse the influence of weather and the density of traffic on the choice of transport mode. A case study is conducted in an access/egress corridor located in the city of Barcelona (Spain). Two data sources were used: revealed preference and stated preference data. Modelling techniques using mixed data enabled the stronger features from both data sources to be captured. Finally, we discuss how the selection of different alternative specific constants in models estimated using mixed data could generate unrealistic forecasting results if environmental changes are expected in the actual market.     

Individual characteristics and stated preferences for alternative energy sources and propulsion technologies in vehicles: A discrete choice analysis for Germany

With respect to the German goal of a transition to a lead market for electromobility within a short time period, this paper empirically examines the preferences for alternative energy sources or propulsion technologies in vehicles and particularly for electric vehicles. The data stem from a stated preference discrete choice experiment with 598 potential German car buyers. In order to simulate a realistic future purchase situation, seven vehicle types were incorporated in each of the six choice sets, i.e. hybrid, gas, biofuel, hydrogen, and electric vehicles besides common gasoline and diesel vehicles. The econometric analysis with flexible multinomial probit models reveals that potential car buyers in Germany currently have a low stated preference for electric, hydrogen, and hybrid vehicles. While our paper also discusses the impact of common vehicle attributes such as purchase price or service station availability, it particularly considers the effect of socio-demographic and environmental awareness variables. The estimation results reveal that younger potential car buyers have a higher stated preference for hydrogen and electric vehicles, males have a higher stated choice of hydrogen vehicles, and environmentally aware potential car buyers have a higher stated preference for hydrogen and electric vehicles. These results suggest that common policy instruments such as the promotion of research and development, taxation, or subsidization in the field of electromobility could be supplemented by strategies to increase the social acceptance of alternative vehicle types that are directly oriented to these population groups. Methodologically, our study highlights the importance of the inclusion of taste persistence across the choice sets and a high number of random draws in the Geweke–Hajivassiliou–Keane simulator in the simulated maximum likelihood estimation of the multinomial probit models.     

电动自行车用氢燃料电池动力系统研究

论文研究开发了一种"电电"互混的电动自行车用氢燃料电池动力系统,旨在通过将燃料电池与一种具备瞬间大电流放电能力的储能设备连接,使得电动自行车用氢燃料电池动力系统在具备长航时、快速充装特性的同时,具备良好的爬坡与加速性能。文章提供了该电动自行车用氢燃料电池动力控制方法、电动自行车用氢燃料电池动力控制装置及包括该电动自行车用氢燃料电池动力控制装置的电动自行车用氢燃料电池动力系统,解决相关技术中存在的燃料电池的动态响应能力弱过载能力差的问题。     

Cycle commuting in Belgium: Spatial determinants and ‘re-cycling’ strategies

This paper attempts to explain the spatial variation of the use of a bicycle for commuting to work at the level of the 589 municipalities in Belgium. Regression techniques were used and special attention was paid to autocorrelation, heterogeneity and multicollinearity. Spatial lag models were used to correct for the presence of spatial dependence and a disaggregated modelling strategy was adopted for the northern and southern parts of the country. The results show that much of the inter-municipality variation in bicycle use is related to environmental aspects such as the relief, traffic volumes and cycling accidents. Town size, distance travelled and demographic aspects also have some effect. In addition, there are regional differences in the effects of the structural covariates on bicycle use: the impact of variables such as traffic volume and cycling accidents differs substantially between the north and the south of the country. This paper also suggests that high rates of bicycle use in one municipality stimulate cycling in neighbouring municipalities, and hence that a mass effect can be initiated, i.e. more cycle commuting encourages even more commuters in the area to cycle. These findings provide some recommendations for decision-makers wishing to promote a shift from car to bicycle use.     

Combining Intermodal Transport With Electric Vehicles: Towards More Sustainable Solutions

Abstract

This paper analyses the feasibility of incorporating electric or hybrid vehicles in intermodal transport for the transportation of containers in the pre- and post haulage (PPH) operation. In Europe, the intermodal transport market is being strongly supported, as it is seen as one of the keystones of a sustainable mobility system policy. The introduction of environmentally friendly electric/hybrid vehicles for the pre- and post haulage operation would mean a further enhancement leading to a more complete ecological intermodal transport chain. PPH operations are usually no longer than 30 km, and, hence, could possibly be handled by electric or hybrid vehicles.

Hybrid electric vehicles (HEV) combine electric and other drive systems, such as internal combustion engines, gas turbines and fuel cells. Hybrid electric vehicles merge the zero pollution and high efficiency benefits of electric traction with the high fuel energy density benefits of an energy source or thermal engine. The use of electrically driven vehicles for goods distribution has already been successfully proven in international demonstration projects, such as ELCIDIS. Transport of intermodal units (such as ISO containers), however, requires electric/hybrid heavy-duty goods vehicles, which are not readily available on the market, but for which the technology exists.

Different possibilities are assessed as to their technical, financial, organizational and environmental feasibility and suitability. This analysis is based on a typical mission for pre-and post haulage operations, such as type of trips, distance, frequency, urban/suburban, etc.     

Market introduction strategies for alternative powertrains in long-range passenger cars under competition

Alternative powertrains are considered as a promising option to significantly reduce CO₂ emissions from passenger cars. One major prerequisite is their successful market introduction. In this paper, we present a system dynamics model that allows for the evaluation of strategies for the market introduction of alternative powertrain technologies in long-range passenger cars (⩾400 km) under competition. The model considers two competing manufacturers, one first-mover and one follower, each introducing plug-in hybrids and fuel cell electric vehicles according to exogenously defined strategies, which comprise timing, pricing, and technology parameters. The manufacturers can learn from each other due to technology spillover, leading to cost reductions of the powertrains. We use an exemplary dataset for the German car market to study the manufacturers’ influence on the market success of alternative powertrains as well as the underlying mechanisms. The results indicate that in general more competition leads to higher market shares of alternatively powered vehicles and thus allows for a higher reduction of emissions. However, this might cause decreasing profits for both manufacturers, especially if the follower pursues an aggressive pricing strategy when entering the market to gain market shares from its competitor. Also, technology spillover has a positive effect on the market penetration. This particularly holds true for a low level of technology experience where high cost reductions can be achieved and for fuel cell electric vehicles where the costs of the powertrain are much higher compared to plug-in hybrids.     

Strava Metro data for bicycle monitoring: a literature review

ABSTRACT

Monitoring bicycle trips is no longer limited to traditional sources, such as travel surveys and counts. Strava, a popular fitness tracker, continuously collects human movement trajectories, and its commercial data service, Strava Metro, has enriched bicycle research opportunities over the last five years. Accrued knowledge from colleagues who have already utilised Strava Metro data can be valuable for those seeking expanded monitoring options. To convey such knowledge, this paper synthesises a data overview, extensive literature review on how the data have been applied to deal with drivers’ bicycle-related issues, and implications for future work. The review results indicate that Strava Metro data have the potential—although finite—to be used to identify various travel patterns, estimate travel demand, analyse route choice, control for exposure in crash models, and assess air pollution exposure. However, several challenges, such as the under-representativeness of the general population, bias towards and away from certain groups, and lack of demographic and trip details at the individual level, prevent researchers from depending entirely on the new data source. Cross-use with other sources and validation of reliability with official data could enhance the potentiality.     

Short-term planning and policy interventions to promote cycling in urban centers: Findings from a commute mode choice analysis in Barcelona,Spain

BackgroundCycling for transportation has become an increasingly important component of strategies to address public health, climate change, and air quality concerns in urban centers. Within this context, planners and policy makers would benefit from an improved understanding of available interventions and their relative effectiveness for cycling promotion. We examined predictors of bicycle commuting that are relevant to planning and policy intervention, particularly those amenable to short- and medium-term action.MethodsWe estimated a travel mode choice model using data from a survey of 765 commuters who live and work within the municipality of Barcelona. We considered how the decision to commute by bicycle was associated with cycling infrastructure, bike share availability, travel demand incentives, and other environmental attributes (e.g., public transport availability). Self-reported and objective (GIS-based) measures were compared. Point elasticities and marginal effects were calculated to assess the relative explanatory power of the independent variables considered.ResultsWhile both self-reported and objective measures of access to cycling infrastructure were associated with bicycle commuting, self-reported measures had stronger associations. Bicycle commuting had positive associations with access to bike share stations but inverse associations with access to public transport stops. Point elasticities suggested that bicycle commuting has a mild negative correlation with public transport availability (−0.136), bike share availability is more important at the work location (0.077) than at home (0.034), and bicycle lane presence has a relatively small association with bicycle commuting (0.039). Marginal effects suggested that provision of an employer-based incentive not to commute by private vehicle would be associated with an 11.3% decrease in the probability of commuting by bicycle, likely reflecting the typical emphasis of such incentives on public transport.ConclusionsThe results provide evidence of modal competition between cycling and public transport, through the presence of public transport stops and the provision of public transport-oriented travel demand incentives. Education and awareness campaigns that influence perceptions of cycling infrastructure availability, travel demand incentives that encourage cycling, and policies that integrate public transport and cycling may be promising and cost-effective strategies to promote cycling in the short to medium term.     

Modelling market diffusion of electric vehicles with real world driving data – German market and policy options

Plug-in electric vehicles (PEVs) have the potential to reduce green house gas emissions from the transport sector. However, the limited electric range of PEVs could impede their market introduction. Still some potential users are willing to pay more for PEVs. The combined effect of these and other influencing factors as well as the resulting future market evolution are unclear. Here, we study the market evolution of PEVs in Germany until 2020. Our results reveal a great deal of uncertainty in the market evolution of PEVs due to external conditions and the users’ willingness to pay. We find the future share of PEVs in German passenger car stock to range from 0.4% to almost 3% by 2020. Energy prices have a large impact on PEV market evolution as a 25% increase in fuel prices would double the number of PEVs in stock by 2020 compared to a reference scenario. We find a special depreciation allowance for commercial vehicles and a subsidy of 1000 Euro as the most effective and efficient monetary policy options. The high uncertainty of the market evolution implies that policies to foster market diffusion of PEVs should be dynamically adaptable to react to changing framework conditions.     

Modelling the potential for cycling in access trips to bus,train and metro in Rio de Janeiro

Most studies that address the integration of cycling and public transport (PT) focus on developed countries and deal with multi-modal bicycle-train trips. Little is known about the integration of cycling and other main modes such as bus and metro, especially in developing countries, where entirely different socio-economic and trip making conditions prevail. The aim of this study is to model the propensity of current PT users to shift to the bicycle in access trips to bus stops, train and metro stations in Rio de Janeiro, Brazil. Interviews were conducted to collect data on the socio-economic characteristics of the interviewee, trip and spatial characteristics and self-reported barriers and motivators for bicycle use. Two binary logit models were estimated to predict the main factors affecting the propensity to use a bicycle as feeder mode to PT. The results show that socio-economic characteristics as well as barriers and motivators are important factors to explain propensity for bike and ride. The barriers’ model reveals that personal constraints, living too close to the PT boarding point, current parking conditions and public safety play a role. For the motivators’ model, changing home location, owning a bicycle, implementation of cycle ways and improvement in parking conditions are explanatory. Policy recommendations are formulated to increase bicycle ownership and improve cycling infrastructure.     

The role of charging and refuelling infrastructure in supporting zero-emission vehicle sales

Widespread uptake of battery electric, plug-in hybrid, and hydrogen fuel-cell vehicles (collectively zero-emissions vehicles or ZEVs) could help many regions achieve deep greenhouse gas mitigation goals. Using the case of Canada, this study investigates the extent to which increasing ZEV charging and refuelling availability may boost ZEV sales relative to other ZEV-supportive policies. We adapt a version of the Respondent-based Preferences and Constraints (REPAC) model using 2017 survey data from 1884 Canadian new vehicle-buyers to simulate the sales impacts of increasing electric vehicle charging access at home, work, public destinations, and on highways, as well as increasing hydrogen refuelling station access. REPAC is built from a stated preference choice model and represents constraints in supply and consumer awareness, as well as dynamics in ZEV policy out to 2030. Results suggest that new ZEV market share from 2020 to 2030 does not substantially benefit from increased infrastructure. Even when electric charging and hydrogen refuelling access are simulated to reach “universally” available levels by 2030, ZEV sales do not rise by more than 1.5 percentage points above the baseline trajectory. On the other hand, REPAC simulates ZEV market share rising as high as 30% by 2030 with strong ZEV-supportive policies, even without the addition of charging or refuelling infrastructure. These findings stem from low consumer valuation of infrastructure found in the stated preference model. Results suggest that achieving ambitious ZEV sale targets requires a comprehensive suite of policies beyond a focus on charging and refueling infrastructure.     

Policy options to support the adoption of electric vehicles in the urban environment

In this paper we discuss the effectiveness, efficiency and feasibility of policy measures that cities may adopt to stimulate the uptake and use of electric vehicles. Our analysis is based on an expert workshop in which municipal policy-makers used a group decision room system to exchange their experiences with electric vehicle related policies. We distinguish six categories of measures: supporting citizens and businesses, supporting charging-infrastructure build up, regulatory measures, raising awareness, government as lead user, and governing the transition with other levels of government. We find two feasible policy mixes of effective and efficient measures, one for cities that strive to be among the global frontrunners and one of no-regret policies that any city should adopt, if it wants to stimulate electric mobility.