Posts tagged cycling
Bicycle and Transit: a Powerful Combination
Cities are facing mobility related problems such as traffic congestion and air pollution. The combination of bicycle and transit offers a sustainable alternative to individual motorized transport. It combines the benefits of both modes, namely speed, flexibility and accessibility. This paper merges several results of our recent studies in this combined mode. The bicycle and transit mode is at first reviewed from a governance point of view. After this top-down approach a shift to the actual bicycle and transit users is made. The objective of this paper is to understand the characteristics of the bicycle-transit combination. Understanding the bicycle-transit chain makes it possible to improve the design of the chain by adapting policies which enhances (further) growth of this sustainable transport mode.
Regarding the governance point of view: two metropolitan areas in the world where both bicycle and transit systems are highly developed are compared. The metropolitan region of Copenhagen and the Dutch Randstad conurbation. In the Netherlands the governance structure of spatial planning and transit planning has gradually been shifted from local and national level to provincial level. Furthermore, many provinces are a key stakeholder when developing so called bicycle highways. The combination of responsibilities for (i) spatial planning, (ii) transit, and (iii) bicycle planning has proven to be extremely successful when making the most out of the bicycle-transit combination. It is seen that the results of the integration of transit and spatial planning highly encourages citizens to use the bicycle and transit mode.
In addition to our policy-related analysis, the actual bicycle and transit user has been examined. It is seen that the current users of the combined mode are mainly middle-aged, male, full-time employees. Catchment areas of transit stops depends on multiple factors. One of these factors is quality of the transit supply. In comparison to low level services, high level services attract users from twice as far. While over 40% of the Dutch train traveller uses the bike to get from home to the station, modal shift might be possible regarding egress trips and from and to high level bus, tram and metro services. Dockless bikes are helpful regarding egress transport. In the city of Delft, approximately 15% of the MoBike dockless bike trips are related to the train stations.
Finally, it is concluded that the combination of bicycle and transit is a successful and sustainable transport combination. Both from a governance and user perspective, there are major opportunities regarding the egress side of the bicycle transit chain. Furthermore, the transition of low level transit to high level transit makes the bicycle-transit combination more attractive, transit authorities are therefore highly encouraged to facilitate bicycle parking and shared bicycle facilities at their transit stops.
Check the ETC presentation with Raymond Huisman HERE
Walking and bicycle catchment areas of tram stops: factors and insights
Pollution and congestion are important issues in urban mobility. These can potentially be solved by multimodal transport, such as the bicycle-transit combination, which
benefits from the flexible aspect of the bicycle and the wider spatial range of public transport. In addition, the bicycle can increase the catchment areas of public transport stops. Most transit operators consider a fixed 400m buffer catchment area. Currently, not much is known about what influences the size of catchment areas, especially for the bicycle as a feeder mode.
Bicycles allow for reaching a further stop in order to avoid a transfer, but it is not clear whether travelers actually do this.This paper aims to fill this knowledge gap by assessing which factors affect feeder distance and feeder mode choice. Data are collected by an on-board transit revealed preference survey among tram travelers in The Hague, The Netherlands. Both regression models and a qualitative analysis are performed to identify the factors that influence feeder distance and feeder mode choice. Results show that the median walking feeder distance is 380m, and the median cycling feeder distance is 1025m. The tram stop density and chosen feeder mode are most important in feeder distance. For feeder mode choice, the following factors are found to be influential: tram stop density, availability of a bicycle, and frequency of cycling of the tram passenger. Furthermore, the motives of respondents for choosing a stop further away are mostly related to the quality of the transit service and comfort matters, of which avoiding a transfer is named most often. In contrast, the motives for cycling relate mostly to travel time reduction and the built environment. Three important barriers for the bicycle-tram combination have been discovered: unavailability of a bicycle, insufficient and unsafe bicycle parking places. Infrequent users of the bicycle-tram combination are more inclined to travel further to a stop that suits them better.
Find the MT-ITS paper and presentation of Lotte Rijsman HERE and HERE
Understanding the difference in travel patterns between docked and dockless bike-sharing systems: a case study in Nanjing, china
The co-existence of dockless and traditional docked bike-sharing systems presents new opportunities for sustainable transportation in cities all over the world, both serving door to door trips and access and egress to and from transit. To compare travel patterns of these two systems, we explored the GPS data of a dockless bike-sharing scheme and the smart card data of a docked bike-sharing scheme in the city of Nanjing, China over the same time period. In order to obtain information from different perspectives, such as user perception and opinions, an intercept survey on bike-sharing mode choice was conducted. A mode choice model was estimated to reveal the effects of personal information, user perception and experience on bike-sharing usage. Results show that dockless bike-sharing systems have a shorter average travel distance and travel time but a higher use frequency and hourly usage volume compared to docked bike-sharing systems. Trips of docked and dockless bike-sharing on workdays are more frequent than those on weekends, especially during the morning and evening rush hours from 7:00-9:00 and 17:00-19:00, respectively. As to the factors influencing travelers’ mode choice, results show that retirees, enterprise staff and users with E-bikes are less likely to use docked sharing-bikes than dockless bikes. In contrast, high-income travelers and people who are highly sensitive to discounts, internet technology and online payment service are more likely to use the dockless bike-sharing. Finally, policy implications are discussed for cities to improve the performance of docked and dockless bike-sharing systems.
Find our poster HERE
Insights into factors affecting the combined bicycle-transit mode
The combination of bicycle and transit is an upcoming, sustainable multimodality. The flexibility of the bicycle combined with the speed and comfort of good transit can be a highly competitive alternative to the car. This study shows that many factors influence the uptake and attractiveness of the bicycle-transit combination. An in-depth literature review resulted in over thirty unique factors: six transit related factors, twenty first-last mile factors and fifteen context related factors. All these factors might influence the demand for this ‘new’ mode positively or negatively. An exploratory choice modelling study showed that Dutch bicycle-train users in our sample are willing to pay €0.11 for a minute less bicycle time, €0.08 for a minute less train time, €0.11 for a minute of less time to park and €0.60 per avoided transfer. These kinds of insights give the bicycle and transit sector valuable information to be used in modelling multimodality and cost-benefit analyses, thereby supporting improved decision making and integrated design of bicycle and transit networks.
Read the full CASPT paper HERE and find the presentation HERE
Opportunities for the Combined Bicycle and Transit Mode
Around the world cities face negative effects generated by increasing mobility needs. To tackle these issues, mobility should be environmental and spatial friendly. Combining bicycle and public transport into a ‘bicycle + transit mode’ will create a synergy with the best of both worlds: superb door-to-door accessibility offered by the bicycle and a large spatial reach from transit modes. These complemented modes combined easily challenge private carsin terms of speed as well accessibility.
Research regarding the users and trip types of the bicycle and transit mode is largely missing. This is unfortunate, since understanding both user and trip characteristics is of the utmost importance to improve the share of the bicycle and transit mode. Policy-makers can make concrete decisions on infrastructure and service investments only when the gap between the aforementioned societal need and scientific knowledge is filled.
The main analysis in the study is based on data from the Netherlands. The Netherlands is one of the countries with a head start regarding the use of the bicycle + transit mode. A one-day trip diary survey, representative of the population of the Netherlands, with more than 250,000 respondents who made nearly 700,000 trips over the course of 6 years (2010-2015), is used to derive important trip and user characteristics of the bicycle + transit mode. Finally, latent class cluster analysis is applied to find prototypical users of this mode on the basis of their socio-demographic attributes.
It is, for example, found that the most important purposes of the bicycle and transit mode are work or education, typically involving relatively long distances. Bicycle and transit-potential for other transit network levels, such as metros and bus rapid transit can be found. Moreover, seven unique user groups – from middle-aged professionals to school children – are identified, and their different travel behaviour is discussed.
Understanding the trip and user characteristics of the combined bicycle and transit mode
Several cities around the world are facing mobility related problems such as traffic congestion and air pollution. Although limited individually, the combination of bicycle and transit offers speed and accessibility; by complementing each other’s characteristics the bicycle and transit combination can compete with automobiles. Recognising this, several studies have investigated policies that encourage integration of these modes. However, empirical analysis of the actual users and trips of the combined mode is largely missing. This study addresses this gap by (i) reviewing empirical findings on related modes, (ii) deriving user and trip characteristics of the bicycle and transit mode in the Netherlands, and (iii) applying latent class cluster analysis to discover prototypical users based on their socio-demographic attributes. Most trips by this mode are found to be for relatively long commutes where transit is in the form of trains, and bicycle and walking are access and egress modes respectively. Furthermore, seven user groups are identified and their spatial and temporal travel behaviour is discussed. Transport authorities may use the empirical results in this study to further streamline integration of bicycle and transit for its largest users as well as to tailor policies to attract more travellers.
Find our Thredbo conference presentation HERE
Read our paper HERE
Modelling Multimodal Transit Networks: Integration of bus networks with walking and cycling
Demand for (public) transportation is subject to dynamics affected by technological, spatial, societal and demographic aspects. The political environment, together with financial and spatial constraints limit the possibilities to address transit issues arising from growing demand through the construction of new infrastructure. Upgrading of existing services and improving integration over the entire trip chain (including cycling) are two options that can address these transport issues. However, transport planners and transport service operators often fail to include the entire trip when improving services, as improvement is normally achieved through the adaptations of characteristics (e.g. speeds, stop distances) of the services.
Our developed framework consists of two parts: one to assess the characteristics of the different bus services and their access and egress modes, and one to assess the effects of integration of these services, which includes the modelling and analysis in a regional transit model. The framework has successfully been applied to a case study showing that bus systems with higher frequencies and speeds can attract twice the amount of cyclists on the access and egress sides. It also shows that passengers accept longer access and egress distances with more positive characteristics of the bus service (higher speeds, higher frequencies).
Find the presentation of Judith Brand at MT-ITS in Napoli HERE
Find our paper HERE
Insights into door-to-door travel patterns of public transport passengers
Public transport enables fast and reliable station to station journeys. To assess passenger travel patterns and to infer actual quality of service, smartcard and AVL data offer great opportunities. There is, however, an increasing interest in insights into access and egress dynamics of public transport riders as well. What is the size of a stop’s catchment area, which modes are used, and how long and reliable are access and egress times? The answers to these and other questions enable optimization of the total mobility system, thereby also increasing public transport ridership and efficiency. Sufficient biking access of public transport stops (routes and parking), for instance, offer opportunities to increase public transport stopping distances, thereby increasing operational speed and reliability, without compromising accessibility of service areas. We developed a methodology to calculate and demonstrate these dynamics by using new and existing data technologies, namely AVL, survey and new promising app.
Find the Transit Data Conference abstract HERE and our presentation HERE