Bike share : a synthesis of the literature

This paper begins by providing an overview of bike share programs, followed by a critical examination of the growing body of literature on these programs. This synthesis of previous works, both peer-reviewed and grey, includes an identification of the current gaps in knowledge related to the impacts of bike sharing programs. This synthesis represents a critically needed evaluation of the current state of global bike share research, in order to better understand, and maximize the effectiveness of current and future programs. Several consistent themes have emerged within the growing body of research on bike share programs. Firstly, the importance bike share members place on convenience and value for money appears paramount in their motivation to sign up and use these programs. Secondly, and somewhat counter intuitively, scheme members are more likely to own and use private bicycles than non-members. Thirdly, users demonstrate a greater reluctance to wear helmets than private bicycle riders and helmets have acted as a deterrent in jurisdictions in which helmets are mandatory. Finally, and perhaps most importantly from a sustainable transport perspective, the majority of scheme users are substituting from sustainable modes of transport rather than the car.

Bike share's impact on car use : evidence from the United States, Great Britain, and Australia

There are currently more than 400 cities operating bike share programs. Purported benefits of bike share programs include flexible mobility, physical activity, reduced congestion, emissions and fuel use. Implicit or explicit in the calculation of program benefits are assumptions regarding the modes of travel replaced by bike share journeys. This paper examines the degree to which car trips are replaced by bike share, through an examination of survey and trip data from bike share programs in Melbourne, Brisbane, Washing, D.C., London, and Minneapolis/St. Paul. A secondary and unique component of this analysis examines motor vehicle support services required for bike share fleet rebalancing and maintenance. These two components are then combined to estimate bike share’s overall contribution to changes in vehicle kilometres traveled. The results indicate that the estimated mean reduction in car use due to bike share is at least twice the distance covered by operator support vehicles, with the exception of London, in which the relationship is reversed, largely due to a low car mode substitution rate. As bike share programs mature, evaluation of their effectiveness in reducing car use may become increasingly important. This paper reveals that by increasing the convenience of bike share relative to car use and by improving perceptions of safety, the capacity of bike share programs to reduce vehicle trips and yield overall net benefits will be enhanced. Researchers can adapt the analytical approach proposed in this paper to assist in the evaluation of current and future bike share programs.

Bike share's impact on car use : evidence from the United States, Great Britain, and Australia

There are currently more than 700 cities operating bike share programs. Purported benefits of bike share include flexible mobility, physical activity, reduced congestion, emissions and fuel use. Implicit or explicit in the calculation of program benefits are assumptions regarding the modes of travel replaced by bike share journeys. This paper examines the degree to which car trips are replaced by bike share, through an examination of survey and trip data from bike share programs in Melbourne, Brisbane, Washington, D.C., London, and Minneapolis/St. Paul. A secondary and unique component of this analysis examines motor vehicle support services required for bike share fleet rebalancing and maintenance. These two components are then combined to estimate bike share’s overall contribution to changes in vehicle kilometers traveled. The results indicate an estimated reduction in motor vehicle use due to bike share of approx. 90,000 km per annum in Melbourne and Minneapolis/St. Paul and 243,291 km for Washington, D.C. London’s bike share program however recorded an additional 766,341 km in motor vehicle use. This was largely due to a low car mode substitution rate and substantial truck use for rebalancing of bicycles. As bike share programs mature, evaluation of their effectiveness in reducing car use may become increasingly important. Researchers can adapt the analytical approach proposed in this paper to assist in the evaluation of current and future bike share programs.

An observational study of conflicts between cyclists and pedestrians in the city centre

City centres have large volumes of pedestrians and motorised traffic and increases in walking and cycling could potentially lead to more pedestrians and cyclists being injured. In this study, observers recorded cyclist characteristics, number of pedestrians within 1m and 5m radius and type of conflict (none, pedestrian, vehicle) for 1,971 cyclists in 2010 and 2,551 cyclists in 2012 at six locations in the Brisbane Central Business District. Only 1.7% of cyclists were involved in conflicts with a motor vehicle or pedestrian and no collisions were observed. Increased odds of a pedestrian-cyclist conflict was associated with: male riders, riders not wearing correctly fastened helmets, riding on the footpath, higher pedestrian density (within 1m but not within 5m), morning peak and 2-4 pm (compared with 4-6 pm), two-way roads, roads with more lanes, higher speed limits, and yellow marked bicycle symbols on the road.

Factors influencing bike share membership : an analysis of Melbourne and Brisbane

The number of bike share programs has increased rapidly in recent years and there are currently over 700 programs in operation globally. Australia’s two bike share programs have been in operation since 2010 and have significantly lower usage rates compared to Europe, North America and China. This study sets out to understand and quantify the factors influencing bike share membership in Australia’s two bike share programs located in Melbourne and Brisbane. An online survey was administered to members of both programs as well as a group with no known association with bike share. A logistic regression model revealed several significant predictors of membership including reactions to mandatory helmet legislation, riding activity over the previous month, and the degree to which convenience motivated private bike riding. In addition, respondents aged 18 - 34 and having docking station within 250m of their workplace were found to be statistically significant predictors of bike share membership. Finally, those with relatively high incomes increased the odds of membership. These results provide insight as to the relative influence of various factors impacting on bike share membership in Australia. The findings may assist bike share operators to maximize membership potential and help achieve the primary goal of bike share – to increase the sustainability of the transport system.

Pedestrian-cyclist interactions at bus stops along segregated bike paths : a case study of Montreal

Safety is one of the major world health issues, and is even more acute for “vulnerable” road users, pedestrians and cyclists. At the same time, public authorities are promoting the active modes of transportation that involve these very users for their health benefits. It is therefore important to understand the factors and designs that provide the best safety for vulnerable road users and encourage more people to use these modes. Qualitative and quantitative shortcomings of collisions make it necessary to use surrogate measures of safety in studying these modes. Some interactions without a collision such as conflicts can be good surrogates of collisions as they are more frequent and less costly. To overcome subjectivity and reliability challenges, automatic conflict analysis using video cameras and deriving users’ trajectories is a solution to overcome shortcomings of manual conflict analysis. The goal of this paper is to identify and characterize various interactions between cyclists and pedestrians at bus stops along bike paths using a fully automated process. Three conflict severity indicators are calculated and adapted to the situation of interest to capture those interactions. A microscopic analysis of users’ behavior is proposed to explain interactions more precisely. Eventually, the study aims to show the capability of automatically collecting and analyzing data for pedestrian-cyclist interactions at bus stops along segregated bike paths in order to better understand the actual and perceived risks of these facilities.

Swim lanes example

From Jisc Infonet's 'swim lanes' tool

On your bike. 'En tu bicicleta'.

Contiene: Libro del profesor, Libro del alumno

Arjo's bike.

Arjo y sus amigos salen a dar una vuelta en bici por los alrededores de su pueblo, Wolf Hill y encuentran una vieja fábrica. Allí, unos adolescentes han fabricado unas rampas con dos tablas colocadas sobre un viejo bidón de gasolina y pasan por encima con la bicicleta. Arjo les imita pero cae al agua del canal, este desatre conduce a un extraño descubrimiento.

Motion planning of autonomous vehicles in a non-autonomous vehicle environment without speed lanes

Planning is one of the key problems for autonomous vehicles operating in road scenarios. Present planning algorithms operate with the assumption that traffic is organised in predefined speed lanes, which makes it impossible to allow autonomous vehicles in countries with unorganised traffic. Unorganised traffic is though capable of higher traffic bandwidths when constituting vehicles vary in their speed capabilities and sizes. Diverse vehicles in an unorganised exhibit unique driving behaviours which are analysed in this paper by a simulation study. The aim of the work reported here is to create a planning algorithm for mixed traffic consisting of both autonomous and non-autonomous vehicles without any inter-vehicle communication. The awareness (e.g. vision) of every vehicle is restricted to nearby vehicles only and a straight infinite road is assumed for decision making regarding navigation in the presence of multiple vehicles. Exhibited behaviours include obstacle avoidance, overtaking, giving way for vehicles to overtake from behind, vehicle following, adjusting the lateral lane position and so on. A conflict of plans is a major issue which will almost certainly arise in the absence of inter-vehicle communication. Hence each vehicle needs to continuously track other vehicles and rectify plans whenever a collision seems likely. Further it is observed here that driver aggression plays a vital role in overall traffic dynamics, hence this has also been factored in accordingly. This work is hence a step forward towards achieving autonomous vehicles in unorganised traffic, while similar effort would be required for planning problems such as intersections, mergers, diversions and other modules like localisation.

Planning autonomous vehicles in the absence of speed lanes using lateral potentials

Chaotic traffic, prevalent in many countries, is marked by a large number of vehicles driving with different speeds without following any predefined speed lanes. Such traffic rules out using any planning algorithm for these vehicles which is based upon the maintenance of speed lanes and lane changes. The absence of speed lanes may imply more bandwidth and easier overtaking in cases where vehicles vary considerably in both their size and speed. Inspired by the performance of artificial potential fields in the planning of mobile robots, we propose here lateral potentials as measures to enable vehicles to decide about their lateral positions on the road. Each vehicle is subjected to a potential from obstacles and vehicles in front, road boundaries, obstacles and vehicles to the side and higher speed vehicles to the rear. All these potentials are lateral and only govern steering the vehicle. A speed control mechanism is also used for longitudinal control of vehicle. The proposed system is shown to perform well for obstacle avoidance, vehicle following and overtaking behaviors.

Planning autonomous vehicles in the absence of speed lanes using an elastic strip

Planning of autonomous vehicles in the absence of speed lanes is a less-researched problem. However, it is an important step toward extending the possibility of autonomous vehicles to countries where speed lanes are not followed. The advantages of having nonlane-oriented traffic include larger traffic bandwidth and more overtaking, which are features that are highlighted when vehicles vary in terms of speed and size. In the most general case, the road would be filled with a complex grid of static obstacles and vehicles of varying speeds. The optimal travel plan consists of a set of maneuvers that enables a vehicle to avoid obstacles and to overtake vehicles in an optimal manner and, in turn, enable other vehicles to overtake. The desired characteristics of this planning scenario include near completeness and near optimality in real time with an unstructured environment, with vehicles essentially displaying a high degree of cooperation and enabling every possible(safe) overtaking procedure to be completed as soon as possible. Challenges addressed in this paper include a (fast) method for initial path generation using an elastic strip, (re-)defining the notion of completeness specific to the problem, and inducing the notion of cooperation in the elastic strip. Using this approach, vehicular behaviors of overtaking, cooperation, vehicle following,obstacle avoidance, etc., are demonstrated.

Heuristic based evolution for the coordination of autonomous vehicles in the absence of speed lanes

The current state of the art in the planning and coordination of autonomous vehicles is based upon the presence of speed lanes. In a traffic scenario where there is a large diversity between vehicles the removal of speed lanes can generate a significantly higher traffic bandwidth. Vehicle navigation in such unorganized traffic is considered. An evolutionary based trajectory planning technique has the advantages of making driving efficient and safe, however it also has to surpass the hurdle of computational cost. In this paper, we propose a real time genetic algorithm with Bezier curves for trajectory planning. The main contribution is the integration of vehicle following and overtaking behaviour for general traffic as heuristics for the coordination between vehicles. The resultant coordination strategy is fast and near-optimal. As the vehicles move, uncertainties may arise which are constantly adapted to, and may even lead to either the cancellation of an overtaking procedure or the initiation of one. Higher level planning is performed by Dijkstra's algorithm which indicates the route to be followed by the vehicle in a road network. Re-planning is carried out when a road blockage or obstacle is detected. Experimental results confirm the success of the algorithm subject to optimal high and low-level planning, re-planning and overtaking.