In recent years, many cities in the world are committed to promoting the electrification of public transportation. For bus companies, how to select the right charging facilities accurately and quickly has become an urgent problem to be solved. In this paper, we propose a simulation method based on Anylogic to describe the operation of electric buses under wired charging and wireless charging conditions. We provide decision-making suggestions for bus companies by analyzing the impact of wireless charging and wired charging on operation cost and passenger waiting time. According to the simulation results, we found that the waiting time of passengers under wired charging conditions is about 8.63% higher than that under wireless charging in the same operating conditions. The use of wireless charging facilities can effectively reduce the waiting time of passengers. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Saturation flow rate (SFR) estimation of approaching lanes is an essential task to evaluate the signal timing and level of service of signalized intersections. There are few existing studies on SFR estimation of the shared left-turn lane. According to relative differences of directions between the front and behind vehicles, this paper divides the headways of shared left-turn lane during green times into four categories. For each category, a method is raised to identify whether the headways are saturated based on the KPSS test. The paper first provides a method to eliminate outliers considering the factors such as distracted driving and stochastic flow. The estimated value of SFR should be 3600 divided by saturation headway, and the estimated value of saturation headway is calculated as the weighted average value of four categories.
© 2019, Springer Nature Singapore Pte Ltd.

This paper is a case study to estimate the Saturation Flow Rate (SFR) on a practical shared left-turn lane during peak hour and off-peak hour using KPSS test method and Highway Capacity Manual (HCM) method. The results declare that the value of SFR estimated by HCM is less than the one estimated by KPSS test method during all time periods. The difference is 4.1% during off-peak hour while 1.2% during peak hour. However, this slight discrepancy could cause remarkable difference in cycle length and average vehicle delay. For example, compared with KPSS test method, in off-peak hour the cycle length increases by 19.2% while the average vehicle delay increases by 14.0% when using HCM method.
© 2019, Springer Nature Singapore Pte Ltd.

This paper is a case study to estimate the Saturation Flow Rate (SFR) on a practical shared left-turn lane during peak hour and off-peak hour using KPSS test method and Highway Capacity Manual (HCM) method. The results declare that the value of SFR estimated by HCM is less than the one estimated by KPSS test method during all time periods. The difference is 4.1% during off-peak hour while 1.2% during peak hour. However, this slight discrepancy could cause remarkable difference in cycle length and average vehicle delay. For example, compared with KPSS test method, in off-peak hour the cycle length increases by 19.2% while the average vehicle delay increases by 14.0% when using HCM method. © 2019, Springer Nature Singapore Pte Ltd.

Saturation flow rate (SFR) estimation of approaching lanes is an essential task to evaluate the signal timing and level of service of signalized intersections. There are few existing studies on SFR estimation of the shared left-turn lane. According to relative differences of directions between the front and behind vehicles, this paper divides the headways of shared left-turn lane during green times into four categories. For each category, a method is raised to identify whether the headways are saturated based on the KPSS test. The paper first provides a method to eliminate outliers considering the factors such as distracted driving and stochastic flow. The estimated value of SFR should be 3600 divided by saturation headway, and the estimated value of saturation headway is calculated as the weighted average value of four categories.
© 2019, Springer Nature Singapore Pte Ltd.