Actuated traffic signals usually use loop detectors. The current practice in many cities is to install four consecutive loop detectors in each lane to reduce the chance of undetected vehicles. Due to practical reasons...Actuated traffic signals usually use loop detectors. The current practice in many cities is to install four consecutive loop detectors in each lane to reduce the chance of undetected vehicles. Due to practical reasons, all four loop detectors in each lane and other detectors referring to the same phase are spliced together. Thus, it is possible for several vehicles to be counted as one single car. This way of detector wiring to the cabinet reduces the accuracy of detectors for collecting traffic volumes. Our preliminary studies show cases with an error greater than 75 percent. Therefore, the purpose of this paper is to provide a simple method to obtain turning volumes from signal information in actuated non-coordinated traffic signals without using loop detector data. To produce the required data, a simulation was performed in VISSIM with different input volumes. To change turning volumes, a code was developed in COM interface. With this code, the inputs did not have to be changed manually. In addition, the COM code stored the outputs. Data were then exported to a single Excel file. Afterwards, regression and the adaptive neural fuzzy inference system （ANFIS） were used to build models to obtain turning volumes. The accuracy of models is defined in terms of mean absolute percent error （MAPE）. Results of our two case studies show that during peak hours, there is a high correlation between actuated green time and volumes. This method does not need extensive data collection and is easy to be employed. The results also show that ANFIS produces more accurate models compared to regression.展开更多
In real traffic,any vehicle must give lane-changing signal(i.e.the turn signal) before changing lanes;at this time,the vehicles behind the lane-changing vehicle will be hindered and may form "plugs" due to t...In real traffic,any vehicle must give lane-changing signal(i.e.the turn signal) before changing lanes;at this time,the vehicles behind the lane-changing vehicle will be hindered and may form "plugs" due to the turn signal effect.However,few studies focus on exploring the effect.In this paper,the turn signal effect was taken into account by proposing a new symmetric two-lane cellular automaton(T-STCA) model,and the new model was set to compare with the STCA,H-STCA and A-STCA models.Numerical results show that using the T-STCA model to describe lane-changing or overtaking,the process appeared in several consecutive time steps;while using the other three models,the process appeared only in one time step.In addition,the T-STCA model could describe the mixed traffic flow more realistically and the turn signal effect could help the plugs to dissolve more quickly.展开更多
文摘Actuated traffic signals usually use loop detectors. The current practice in many cities is to install four consecutive loop detectors in each lane to reduce the chance of undetected vehicles. Due to practical reasons, all four loop detectors in each lane and other detectors referring to the same phase are spliced together. Thus, it is possible for several vehicles to be counted as one single car. This way of detector wiring to the cabinet reduces the accuracy of detectors for collecting traffic volumes. Our preliminary studies show cases with an error greater than 75 percent. Therefore, the purpose of this paper is to provide a simple method to obtain turning volumes from signal information in actuated non-coordinated traffic signals without using loop detector data. To produce the required data, a simulation was performed in VISSIM with different input volumes. To change turning volumes, a code was developed in COM interface. With this code, the inputs did not have to be changed manually. In addition, the COM code stored the outputs. Data were then exported to a single Excel file. Afterwards, regression and the adaptive neural fuzzy inference system （ANFIS） were used to build models to obtain turning volumes. The accuracy of models is defined in terms of mean absolute percent error （MAPE）. Results of our two case studies show that during peak hours, there is a high correlation between actuated green time and volumes. This method does not need extensive data collection and is easy to be employed. The results also show that ANFIS produces more accurate models compared to regression.
基金supported by the National Natural Science Foundation of China (Grant No.71101098)the Beijing Municipal Education Commission Foundation of China (Grant Nos. SM201210038008 and 00791154430107)the Funding Project for Academic Human Resources Development in Institutions of Higher Learning under the Jurisdiction of Beijing Municipality (Grant No.PHR201007117)
文摘In real traffic,any vehicle must give lane-changing signal(i.e.the turn signal) before changing lanes;at this time,the vehicles behind the lane-changing vehicle will be hindered and may form "plugs" due to the turn signal effect.However,few studies focus on exploring the effect.In this paper,the turn signal effect was taken into account by proposing a new symmetric two-lane cellular automaton(T-STCA) model,and the new model was set to compare with the STCA,H-STCA and A-STCA models.Numerical results show that using the T-STCA model to describe lane-changing or overtaking,the process appeared in several consecutive time steps;while using the other three models,the process appeared only in one time step.In addition,the T-STCA model could describe the mixed traffic flow more realistically and the turn signal effect could help the plugs to dissolve more quickly.
