Influence of bus stop with left-turn lines between two adjacent signalized intersections

Based on the symmetric two-lane Nagel–Schreckenberg（STNS） model, a three-lane cellular automaton model between two intersections containing a bus stop with left-turning buses is established in which model the occurrences of vehicle accidents are taken into account. The characteristics of traffic flows with different ratios of left-turn lines are discussed via the simulation experiments. The results indicate that the left-turn lines have more negative effects on capacity,accident rate as well as delay if the stop is located close to the intersections, where the negative effect in a near-side stop is more severe than that in a far-side one. The range of appropriate position for a bus stop without the bottleneck effect becomes more and more narrow with the increase of the ratio of left-turn bus lines. When the inflow is small, a short signal cycle and a reasonable offset are beneficial. When the inflow reaches or exceeds the capacity, a longer signal cycle is helpful. But if the stop position is inappropriate, the increase of cycle fails in reducing the negative effect of left-turning buses and the effectiveness of offset is weakened.

Combined Effect of Bus Stop and Access on Expressway Capacity

To determinate the combined effect of bus bay stops near access points on the expressway capacity,a new theoretical approach is developed on the basis of gap acceptance theory and queuing theory. According to the location between the bus stop and the access upstream or downstream,the capacity models on the expressway are developed for four cases. The results show that there are no significant differences in the capacity among four cases when the bus arrival rate is less than 60 veh / h and the car volume at the entrance and exit is less than 200 pcu / h. As the bus arrival rate and the car volume at the entrance and exit increase,the bus stops at downstream of an entrance and upstream of an exit have remarkable effect on the capacity. The increasing of berth number of the bus stop has a positive effect on the capacities of four cases.

Combined bottleneck effect of on-ramp and bus stop in a cellular automaton model

The combined bottleneck effect is investigated by modeling traffic systems with an on-ramp and a nearby bus stop in a two-lane cellular automaton model. Two cases, i.e. the bus stop locates in the downstream section of the on-ramp and the bus stop locates in the upstream section of the on-ramp, are considered separately. The upstream flux and downstream flux of the main road, as well as the on-ramp flux are analysed in detail, with respect to the entering probabilities and the distance between the on-ramp and the bus stop. It is found that the combination of the two bottlenecks causes the capacity to drop off, because the vehicles entering the main road from the on-ramp would interweave with the stopping （pulling-out） buses in the downstream （upstream） case. The traffic conflict in the former case is much heavier than that in the latter, causing the downstream main road to be utilized inefficiently. This suggests that the bus stop should be set in the upstream section of the on-ramp to enhance the capacity. The fluxes both on the main road and on the on-ramp vary with the distance between the two bottlenecks in both cases. However, the effects of distance disappear gradually at large distances. These findings might give some guidance to traffic optimization and management.

Hierarchical predictive energy management strategy for fuel cell buses entering bus stops scenario

This paper aims to answer how to use traffic information to design energy management strategies for fuel cell buses in a networked environment.For the buses entering the bus stops scenario,this paper proposes a hierarchical energy management strategy for fuel cell buses,which considers the traffic information near the bus stops.In the upper-level trajectory planning stage,the optimal SOC trajectory under various historical traffic conditions is solved through dynamic planning.The traffic information and the best SOC trajectory are mapped through BiLSTM,which can achieve fast,real-time long-term SOC reference.In the lower-level real-time predictive energy management strategy,the optimal SOC is used as the state reference to guide the predictive energy management of fuel cell buses when entering the bus stops.Simulation results show that compared with the strategy without SOC trajectory reference,the life cost of the proposed strategy is reduced by 13.8%,and the total cost is reduced by 3.61%.The SOC of the proposed strategy is closer to the DP optimal solution.

Optimization of transit total bus stop time models

Several factors influence bus transit reliability which includes bus stop conditions along the route, traffic conditions, route of travel and time of day. The overall transit bus reli- ability is generally affected by dwell time （DT）, the fare payment method, the bus stop location, and the number of passengers alighting or boarding. A new variable is defined in this study, total bus stop time （TBST）, which is the summation of DT and the time it takes a bus to effectively park at a bus stop and the re-entering the traffic stream. It is suggested that the overall bus transit reliability along routes could be improved if the TBST is mini- mized at bus stops. In this study, TBST models for bus stops located at mid-blocks and near intersections were developed based on multivariate regression analysis using ordinary least squares method. Data collection was conducted at 60 bus stops, 30 of which were near intersections and 30 at mid-blocks, in Washington DC during morning, mid-day and evening peak hours. The variables observed at each bus stop are as follows： number of passengers alighting or boarding, DT, TBST, bus stop type, bus pad, length number of lanes on approach to the bus stop, and permitted parking. Statistical inferences were based on 5% level of significance. From the results, it was inferred that the new variable, TBST, could potentially be used to improve scheduling and transit bus systems planning in a dense urban area.