Mixed Bicycle Research Articles

A macroscopic flow model for mixed bicycle–car traffic

Bicycles are gaining popularity as a mode of transport resulting in a mixed bicycle–car traffic situation on urban roads. Cyclists, however, are hardly included in traffic flow models which complicates the design of safe and congestion-free traffic situations. This work introduces class-specific speed functions based on two variables, being space headway for both cars and cyclists. This enables the macroscopic modelling of mixed bicycle–car traffic. The multi-class macroscopic flow model is successfully tested for different traffic situations that occur on urban roads where cyclists and cars share the same infrastructure, e.g. cyclists overtaking a queue of cars and cars overtaking cyclists with reduced speed. The mixed bicycle–car flow model allows travel time estimation of both classes, which in turn can be used to evaluate the overall performance of a mixed traffic road.

Lane width‐based cellular automata model for mixed bicycle traffic flow

AbstractIn this paper, an improved extended Burgers cellular automata (EBCA) model for heterogeneous bicycle traffic flow is proposed. The compressibility of bicycle traffic flow is considered as a probability, which is related to the bicycle path width. The proposed improved EBCA model is calibrated and validated using the field data collected from three sites in Hangzhou, China. The proposed model is compared with the original EBCA model that does not consider compressibility. The comparison results show that our improved model can simulate heterogeneous bicycle traffic flow better. Moreover, the proposed model overcomes the shortcoming of the other BCA models that only specific path widths can be simulated directly when lane width is determined. Lastly, the EBCA model performance in the congested regions is improved significantly.

Research on the characteristics of mixed traffic flow based on an improved bicycle model

Mixed traffic flow is a main feature of urban traffic in developing countries. Mixed bicycle flow includes human-powered and electric-powered bicycles and plays an important role in this mixed traffic flow. In mixed bicycle flow, cyclist behavior is flexible and variable. Cyclists move arbitrarily in the road and may influence the vehicle flow at intersections. Therefore, we first propose an improved bicycle model that can reproduce the main features of cyclist behavior, such as overtaking and self-protection. Then a simulation model based on the improved bicycle model is proposed to research the characteristics of mixed traffic flow in intersections. The conflict avoidance rules are then applied in the simulation model to eliminate traffic accidents. The simulation results indicate that the improved bicycle model is practical and that the density–velocity diagram of bicycle flow is similar to real traffic data. The existence of bicycle flow decreases vehicle velocity and worsens traffic flow in mixed traffic flow. However, the influence of bicycle flow might disappear at a particular vehicle density.

Lateral Drift Behavior Analysis in Mixed Bicycle Traffic: A Cellular Automaton Model Approach

Bicycle movements are always associated with lateral drifts. However, the impacts of lateral drift behavior, as well as variable lateral clearance maintaining behavior due to the variation of drift intensity, on mixed bicycle flow are not clear. This paper establishes a new cellular automata model to study typical characteristics of mixed bicycle traffic induced by lateral drift and its accompanying behavior. Based on derived positive correlation between passing speed and drift speed through survey, the occurrence probability of lateral drift and the degree of maintained lateral clearance are both introduced in accordance with the variance of passing speed. Then, in whole density region, firm conformity between simulation results and actual survey data is reached, which has seldom been achieved in previous studies. It is further verified that speed distortions in intermediate and high density region induced by assumption of constant lateral clearance requirements can be revised by introducing its variability characteristics. In addition, two contrastive impacts of lateral drift behavior are observed. That is, it causes speed fluctuation in low density while alleviating the speed fluctuation in relatively high density. These results are expected to be helpful to improve the simulation performance of mixed bicycle flow as well as depict more realistic vehicle-bicycle conflicts and so on.

Modeling of speed distribution for mixed bicycle traffic flow

Speed is a fundamental measure of traffic performance for highway systems. There were lots of results for the speed characteristics of motorized vehicles. In this article, we studied the speed distribution for mixed bicycle traffic which was ignored in the past. Field speed data were collected from Hangzhou, China, under different survey sites, traffic conditions, and percentages of electric bicycle. The statistics results of field data show that the total mean speed of electric bicycles is 17.09 km/h, 3.63 km/h faster and 27.0% higher than that of regular bicycles. Normal, log-normal, gamma, and Weibull distribution models were used for testing speed data. The results of goodness-of-fit hypothesis tests imply that the log-normal and Weibull model can fit the field data very well. Then, the relationships between mean speed and electric bicycle proportions were proposed using linear regression models, and the mean speed for purely electric bicycles or regular bicycles can be obtained. The findings of this article will provide effective help for the safety and traffic management of mixed bicycle traffic.

A Modified Cellular Automaton Approach for Mixed Bicycle Traffic Flow Modeling

Several previous studies have used the Cellular Automaton (CA) for the modeling of bicycle traffic flow. However, previous CA models have several limitations, resulting in differences between the simulated and the observed traffic flow features. The primary objective of this study is to propose a modified CA model for simulating the characteristics of mixed bicycle traffic flow. Field data were collected on physically separated bicycle path in Shanghai, China, and were used to calibrate the CA model using the genetic algorithm. Traffic flow features between simulations of several CA models and field observations were compared. The results showed that our modified CA model produced more accurate simulation for the fundamental diagram and the passing events in mixed bicycle traffic flow. Based on our model, the bicycle traffic flow features, including the fundamental diagram, the number of passing events, and the number of lane changes, were analyzed. We also analyzed the traffic flow features with different traffic densities, traffic components on different travel lanes. Results of the study can provide important information for understanding and simulating the operations of mixed bicycle traffic flow.

Simulation model of speed–density characteristics for mixed bicycle flow—Comparison between cellular automata model and gas dynamics model

The mixed bicycle flow refers to the bicycle flow containing electric bicycles. The traffic characteristics data of the mixed bicycle flow was collected by the virtual coil method in Nanjing and Ningbo, China. And the speed–density characteristics of the mixed bicycle flow with different proportions of electric bicycles were obtained. The results show that the overall speed of the mixed bicycle flow containing electric bicycles is higher than that of pure bicycle flow when the density is relatively low. The speed decreases when the density is higher than 0.08 bic/m2; the speed–density characteristics of the bicycles and the electric bicycles tend to be the same when the density is higher than 0.25 bic/m2. And when the density reaches 0.58 bic/m2, the mixed bicycle flow becomes blocked and the speed is zero. The cellular automata model and gas dynamics model were also adopted to simulate the speed–density characteristics of the mixed bicycle flow. The simulation results of the cellular automata model are effectively consistent with the actual survey data when the density is lower than 0.225 bic/m2; the simulation results of the gas dynamics model are effectively consistent with the actual survey data when the density is higher than 0.300 bic/m2; but both of the two types of simulation models are inapplicable when the density is between 0.225 and 0.300 bic/m2. These results will be used in the management of mixed bicycles and the research of vehicle–bicycle conflict and so on.

Modeling of Passing Events in Mixed Bicycle Traffic with Cellular Automata

The primary objective of this study was to use the cellular automata (CA) method to model the characteristics of bicycle passing events in mixed bicycle traffic on separated bicycle paths. The mixed traffic was composed of two types of bicycles: the conventional bicycle (c-bicycle) and the electric bicycle (e-bicycle). The number of passing events and the characteristics of mixed bicycle traffic were investigated in the field on eight physically separated bicycle paths in China. Then a CA model was calibrated with the use of the field data to simulate the passing events in the mixed bicycle traffic. The results showed that the CA model could simulate the features of bicycle passing events well. The simulation results were consistent with field observations. An increase in the ratio of e-bicycles would not significantly increase the number of passing events, but e-bicycles did contribute substantially to passing events in mixed bicycle traffic. E-bicycles were shown to have more stability than c-bicycles, especially in traffic with a high flow rate. The findings of this study could improve the performance of simulation techniques to reflect the actual characteristics of mixed bicycle traffic.

The Study on the Safety of High School Students’ Bicycle Traffic in Beijing

It is an environment-friendly transport for high school students go to school and go home by bicycle. It’s easily cause traffic accident and traffic jam owing to the time of high school students go to school and leave school is concentration or the circumstance of traffic flow mixed motor vehicle and bicycle, and the vehicle and bicycle scrambles for roads. This paper takes high school students go to school and leave school by bicycle as objects, studies bicycle traffic conflicts in two-phase intersection and the factors of insecurity, proposes the improvement measures for security. In this paper, taking T-shaped road junction ZaoJunmiaodonglu and Zaojunmiaolu in front of High school Attached to Northern Jiaotong University as example and using empirical analysis method to study.

Multi-value cellular automata model for mixed bicycle flow

In this paper, we investigate mixed bicycle flow using the multi-value cellular automata (CA) model. Two types of bicycles with different maximum speed are considered in the system. The system of mixed bicycles is investigated under both deterministic and stochastic regimes. It is shown under the deterministic case that there appear multiple states both in congested flow and free flow regions. Analytical analysis is carried out and is in good agreement with the simulation results. Under the stochastic case, the multiple states effect disappears only when both slow and fast bicycles are randomized. Spacetime plots are presented to show the evolution of mixed bicycle flow.

Nonmotorized Interference and Control Measures at Signalized Intersections in China

The adverse effects of bicycles and pedestrians on motor vehicle traffic in at-grade, signalized intersections under mixed-traffic conditions have been observed at several typical intersections in Beijing. Mixed bicycle and motor vehicle traffic is a major characteristic of urban transport in China and has led to serious congestion and capacity reduction in at-grade signalized intersections in urban areas. A method is presented to quantitatively measure nonmotorized effects, and values are recommended for adjusting the model to estimate the capacity of through vehicle lanes. Several temporal segregation solutions to mixed-traffic problems in at-grade signalized intersections are described that have proven cost-effective in several Chinese cities, and suggestions for their application are provided.

Development of a Computer Simulation Model of Mixed Motor Vehicle and Bicycle Traffic on an Urban Road Network

The first step has been taken in the effort to develop a microscopic simulation model of mixed motor vehicle and bicycle traffic over an entire network. The primary objective was to develop the main algorithm of BICycle SIMulator and translate it into a working computer program. To achieve the goal, the gaps in the existing literature were filled by data collected at the University of Delaware campus in Newark. An equation of mixed bicycle and motor vehicle following was developed and used for the representation of longitudinal interaction of vehicles. The program was implemented in C+plus; programming language and tested on real-world data. The resulting software is the first in the world to allow the inclusion of bicyclists in the analysis of urban transportation by the means of microscopic simulation.