Curbside Bus Research Articles

Capacity Reduction for Urban Road Due to Curbside Bus Stop: A Case Study of Srijana Chowk, Nepal

Curbside bus stops have a significant impact on traffic characteristics, including speed and roadway capacity. Srijana Chowk, the urban area within Pokhara metropolitan city, was selected for the study. The objective of the study is to evaluate the reduction in roadway capacity at the curbside bus stop at Srijana Chowk. The primary data was collected using videographic techniques. The analysis indicated that Srijana Chowk’s curbside bus stop caused an average stream speed reduction of 6.23%. The capacity at the Srijana Chowk bus stop was 2532 PCU/hr and 2718 PCU/hr at the curbside and on the opposite side of the bus stop, respectively. Similarly, the capacity reduction was analyzed to be 16.62% and 6.84% by the Indonesian Highway Capacity Manual and Greenshield’s model, respectively

Analysis of Time Headway Characteristics at the Curbside Bus Stop on Multi-Lane Divided Urban Arterials under Mixed Traffic Conditions

Analysis of Time Headway Characteristics at the Curbside Bus Stop on Multi-Lane Divided Urban Arterials under Mixed Traffic Conditions

Capacity drop at the bus stop on multilane divided urban roads under mixed traffic conditions

Time headway characteristics are of great importance for planning and design of roadway. The present study determines time headway distribution pattern of vehicular stream at various urban roads and evaluate drop in capacity of roadway section having curb-side bus stops. Field data for present study was collected at 8 different locations on four-lane and six-lane divided sections in the cities of Warangal and Hyderabad in India. The mean time headway of heterogeneous vehicles fitted to various headway distributions for estimating capacity of road section. The factors affecting the capacity have been identified as bus frequency, dwell time, and the average roadway width lost. Percentage reduction in capacity (PRC) is determined to develop regression model. Further, speed-flow diagrams were developed using field observed traffic flow data for determining parameters free-speed, critical speed, and roadway capacity on selected section. After comparing capacity values obtained from two methods, the study determined avg. time headway of vehicular stream under the traffic flow at capacity and free flow conditions. The study also finds capacity value of bus stop section using methodology provided in Indo-HCM (2017). The PRC values estimated based on Indo-HCM guidelines are found to be significantly higher than those estimated by the proposed PRC model. It is due to the Indo-HCM guideline considering only one parameter i.e. bus frequency. The study finds, in addition to bus frequency the dwell time, roadway width lost, and presence of an extra lane also influences the drop in capacity of bus stop section on multilane divided urban roads.

Efficient heuristic methods for berth allocation at multi-line, multi-berth curbside bus stops

Transit management agencies often pre-allocate a multi-berth stop’s berths to specific bus lines so that passengers can find the right place to wait for their buses. Developing optimal berth allocation plans that minimize the total bus delay is essential for mitigating bus queues at busy multi-berth stops. However, this problem is challenging due to the huge solution space, the high degree of stochasticity in bus queues, and the resulting extremely high computational cost. In this paper, we first propose a simple heuristic method inspired by queueing theory. It is based on the idea that evenly distributing the total traffic intensity (defined as the total bus arrival rate times the mean dwell time) among all the berths would produce a lower bus delay. Numerical results demonstrate that this simple method generated very good berth allocation plans (with optimality gaps <6% for no-overtaking and free-overtaking stops) in seconds! It does not rely on time-consuming simulation surrogate models or numerous input data such as the stochastic bus arrival processes and dwell time distributions of each bus line. To further improve the simple heuristic’s performance (especially for limited-overtaking stops), we develop a cluster-based nested partition algorithm that can find a near-optimal plan (e.g., with an optimality gap of <3%) in a much shorter time than a previous algorithm. The algorithm employs the simple heuristic plan as the initial solution. Our methods can be applied to stops with various berth numbers, different proximities to nearby traffic signals, and under diverse bus queueing rules.

Longitudinal Acceleration and Deceleration Behavior of Vehicles at the Curbside Bus Stop Under Mixed Traffic Conditions

Longitudinal Acceleration and Deceleration Behavior of Vehicles at the Curbside Bus Stop Under Mixed Traffic Conditions

Examining the Lane-Wise Time Headway and Speed Characteristics at Curb-Side Bus Stop on Four-Lane Divided Urban Arterials

Examining the Lane-Wise Time Headway and Speed Characteristics at Curb-Side Bus Stop on Four-Lane Divided Urban Arterials

Revealing safety impact of bus stops on passenger-cyclist interactions – Evidence from Nanjing, China

Bus passengers and cyclists often interact with each other at bus stops, which causes potential conflicts and safety risks. However, the safety impact of different types of bus stops on vulnerable road users has received limited attention. This study measures the safety impact of different types of bus stops on the interactions between passengers and cyclists. 3,136 passengers and 4,135 cyclists are observed at twelve typical bus stops in Nanjing, China. Road users’ behaviours, safety risks and congestion levels at different types of bus stops and their influential factors are analysed. Logit model and partial proportional odds model are used to analyse the occurrence rate and the severity of passenger-cyclist conflicts, respectively. Results indicate that generally floating bus stops with dedicated cycleway provide a safer environment for vulnerable road users, compared to curbside bus stops. Many factors are found increasing the safety risk significantly, including narrow road width, passengers using mobile phone, wrongful riding direction of cyclists, high passenger or cyclist densities, and passenger-cyclist interaction in cross direction. There is also a significant difference on the lag-time of road users at different types of bus stops. It is recommended that the layout design of bus stops should provide sufficient space for road users, and various regulations could be taken into consideration to alleviate the conflicts at bus stops and protect the safety of both passengers and cyclists.

Real-time cruising speed design approach for multiline bus systems

In this paper, we focus on controlling multiline buses operated in networks with curbside bus stops. In such networks, both bus bunching and bus queueing, which often result in passenger inconvenience as well as bus waiting delays, are frequently observed during bus operations. To address the adverse influences of these two phenomena, we propose a mixed integer programming (MIP) model to provide guidance on real-time bus cruising speeds based on the real-time state of the whole system. The proposed model can avoid bus bunching by coordinating bus cruising speeds and alleviate bus queueing congestion by restricting the number of bus arrivals at each stop. Specifically, to address bus bunching, the model has a quadratic objective function that minimizes the total expected passenger waiting time; while for bus queueing, the model has big-M and time-indexed constraints that restrict the number of bus arrivals in each time interval of length g based on the waiting capacity Qs of each stop s. Simulation experiments are conducted with different sizes of virtual networks, and the corresponding results show that the proposed model can lead to both a shorter average passenger waiting time and less bus congestion at stops. The improvement with respect to bus waiting delay is more significant: the percentage decrease can reach 46.9%. Moreover, the results of the average computing time show that the control model can be solved before a bus finishes service in most cases, which means decisions can be fed back to drivers in a timely manner; therefore, the proposed model can meet the requirements of real-time control. A sensitivity analysis with respect to parameters Qs and g is also performed. These two parameters are shown to only affect control performance with respect to bus waiting delays at stops, and shorter bus waiting delays can be achieved with relatively small Qs and large g. Further experiments are conducted within a real network, and the experimental results show that our method is suitable for implementation in practice.

Simulated Analysis of Exclusive Bus Lanes on Expressways: Case Study in Beijing, China

Deploying exclusive bus lanes is considered an important strategy for supporting public transit priority policy. This paper uses a simulation approach to evaluate planned exclusive bus lanes on expressways in Beijing, China. Two scenarios for deploying exclusive bus lanes—a curbside bus lane scenario and a median bus lane scenario—were designed. Then, a micro-simulation network platform using VISSIM was established and calibrated, with all relative errors between the simulated timevarying speeds and the field speeds less than 15 percent. Afterwards, the two bus lane scenarios were simulated, evaluated, and subsequently compared with current traffic conditions without bus lanes. It was found that for both the mainline and the whole network, the operational efficiencies of buses, general traffic, and all mixed traffic are improved with the deployment of exclusive bus lanes. Further, the median bus lane scenario slightly outperforms the curbside bus lane scenario in this case.

Evaluating zone of influence for traffic-related emissions generated near bus stops: a case study in Nanjing, China

ABSTRACT The estimation of zone of influence (ZoI) at bus stops is the basis for accurately modelling vehicle emissions and assessing the exposure of pedestrians to airborne toxins at emission hotspot locations. The purpose of this study was to investigate the changes in ZoIs for traffic-related emissions at different bus stops. An integrated approach coupling a traffic simulation model (VISSIM) with an emission model (MOVES) was implemented to estimate the vehicle emissions in ZoIs at bus stops for different scenarios. The results demonstrated that lane management mode and traffic conditions had a significant impact on vehicle emissions near different bus stops, and the emission factors (EFs) of pollutants were highest in the acceleration sublink. In addition, the length of the acceleration and queue sublinks mainly determined the length of the ZoIs of bus stops. Owing to the stop-and-go condition, the average contribution of CO, PM2.5, and PM10 towards the ZoI at curbside bus stop and bus bay without exclusive bus lane was significantly higher than under cruising condition. The sensitivity analysis also showed that the emission was more sensitive to acceleration than deceleration. Therefore, the emissions of the departure links for bus stops were significantly higher than those of the approach links. Commuters should reduce the long-time waiting at bus stops, wait downstream of bus stop when waiting for the bus stop, and the vehicles at the bus stop should accelerate slowly when leaving, which will all help to minimize the exposure of commuters to pollutants.

Impact of Connected Automated Buses in a Mixed Fleet Scenario With Connected Automated Cars

Considering the significant increase in transportation (R. Abe, 2019) demand in the last few decades and its consequences on society and the environment, the development of a sustainable transport system is vital. The relevance of public transport networks is expanding as present-day environmental, financial and resource pressures bear upon cities, providing the impetus for new sustainable and economical modes of mobility. Promoting public transport and introducing connectivity and automation are crucial for effectuating a sustainable transport system. Buses can improve the network performance, but curbside bus stops (CBS) elevate the side friction which cause substantial delays to other vehicles, urging imprudent forced lane changes and affecting safety. The introduction of connectivity and automation in buses may improve performance along with safety, and this study attempts to investigate the repercussions of connected automated buses (CABs) in a mixed fleet with connected automated vehicles (CAVs), through a microsimulation modelling exercise. Results indicate that CABs can reduce network-level travel time by 7.9%, 6.4%, 2.1%, 1.3%, 1.8%, 1.2% and 2.27% for 0%, 10%, 30%, 50%, 70%, 90% and 100% CAV penetration, when compared to the network with Human-driven buses (HBs) with the same CAV penetration. Furthermore, CABs also improve the performance of link containing bus stops by reducing standstill times (timespan when buses have zero velocity on the bus stop link). Results exhibit that CABs can decrease standstill times by 12.5%, 13.3%, 12.6%, 15%, 12.9%, 16.7% and 19.9% for 0%, 10%, 30%, 50%, 70%, 90% and 100% CAV penetration, when compared to the network with HBs with identical CAV penetration. Additionally, the number of lane changes in these links were reduced by 28.2% at 100% CAV penetration, indicating synchronous driving and reduced forced lane changes. The crash rate indicates that critical events involving automated vehicle entities and Manual Vehicles (MV) can increase as the MVs cannot adapt promptly to automated driving behaviour. This is supported by the non- parametric distribution of post-encroachment time (PET), time- to-collision (TTC) and relative speed (DeltaS), indicating that the conflict/collision typology’s severity can increase at intermediate CAV penetrations, but plunge significantly at 100% penetration when compared to the current scenario. Lastly, the limitation of tools in flagging conflicts involving CAVs is discussed, and future scrutiny is proposed.

Bus queue time estimation model for a curbside bus stop considering the blocking effect

Bus queue time estimation of a curbside bus stop is essential to evaluate the operation, reliability and performance of a bus system. Arriving buses and served buses on upstream berths form an overflow queue considering the no overtaking principle and limited overtaking principle. The bus dwelling time at the downstream berth may directly influence the capacity at bus stop. This study aims to estimate the queue time attributed to downstream berth blocking effect. The queue delay is modeled as a function of dwell time which is fitting by normal and lognormal distributions. Hence, the queue time should be evaluated by bus dwell time and joint probability density to quantify the negative influence on queue delay. The result indicate that probability distribution versus the queue time in the blocking effect. An illustrative example is presented to reflect the effectiveness of the estimation method. The fitting results further support our theoretical analyses.

Examining the Effect of Curb-Side Bus Stop on Time Headway at Multilane Divided Urban Roads Under Mixed Traffic Conditions

Examining the Effect of Curb-Side Bus Stop on Time Headway at Multilane Divided Urban Roads Under Mixed Traffic Conditions

Optimization of Bus Scheduling and Bus-Berth Matching at Curbside Stops under Connected Vehicle Environment

It is commonly seen that buses are blocked by the ones in front serving passengers and have to queue outside a curbside bus stop although there are vacant berths at the stop. The resultant bus delays degrade the service level of urban public transportation. A potential solution is to reschedule the arrivals of the buses at the stop for full utilization of the berths with the aid of connected vehicle technologies. This study proposes a mixed-integer linear programming model to optimize the scheduling of bus arrivals and the bus-berth matching at a curbside stop under the connected vehicle environment. The objective is the minimization of the bus delays weighted by the number of passengers on the buses. Bus arrival times at the stop and the assignment of berths are optimized together with bus departure times from the stop. Bus punctuality is also taken into consideration. The proposed model could be applied dynamically to cater to time-varying traffic conditions. Numerical studies validate the advantages of the proposed model over the “first-come-first-service” strategy and the relaxed model without bus punctuality in terms of weighted bus delays and bus punctuality. Sensitivity analyses show that (1) the proposed model is robust to the fluctuation of bus service time and (2) a smaller number of berths may be preferred on the condition that the bus demand does not exceed the stop capacity.

Quantifying the Impact of Alternative Bus Stop Platforms on Vehicle Emissions and Individual Pollution Exposure at Bus Stops.

Due to stop-and-go events, bus stops are often treated as “hot spots” for air pollution. The design of bus stops should be optimized to reduce emissions and exposure for transit commuters. The objective of this study was to analyze the impact of bus stop platform types on vehicle emissions and individual pollution exposure. Second-by-second emissions data were first collected from one bus using a portable emission measurement system (PEMS). Microscopic traffic simulation was then used to estimate overall traffic emissions under six scenarios with different bus stop settings. Numerical simulation of pollutant dispersion was also conducted to calculate individual pollution exposure at bus stops. The results of PEMS tests showed no significant differences between bus emissions generated near two different types of stops. However, the effect of platform types on overall traffic emissions was revealed using traffic simulation. The results demonstrated that bus bays reduced the emissions of other heavy-duty vehicles. However, bus bays were not always effective during rush hours. The study also highlighted the importance of the location of bus stops, the number of bus lines, and the length of the platform, in addition to dynamic characteristics of traffic flows in the design of bus stop platforms. Bus stop platforms also affected individuals’ exposure due to the changes in the pollutant flow field. The passenger’s exposure at one bus stop was influenced by both the platform type and standing location. Results suggested that in a condition with a wind direction perpendicular to the bus stop shelter, the total exposure level to CO was lower at the bus bay stop if a passenger stood at the upstream of the station platform. However, the exposure was less at the downstream of the curbside bus stop.

Impact of Buses, Taxis, Passenger Cars, and Traffic Infrastructure on Average Travel Speed

It is known that many variables influence traffic, yet very little is known about the weight of each factor in the dynamics of traffic in cities of developing countries, in many cases due to their peculiar traffic regulations. In this work, we search for the variables that have the most significant impact on the average travel speed of three distinct types of vehicles: passenger cars, taxis, and buses. First, we developed a tool featuring algorithms that simulate ordinary overtaking and car-following behaviors, along with controls for setting vehicles’ actions, particularly buses’ and taxis’ stops. Then, we chose a particular zone to study, based on its common geometry and the particular traffic infrastructure (speed bumps, traffic lights, and bus stops) inside it. Later on, three experiments were carried out, with the following results. (1) Both the buses’ arrival frequency and curbside bus stops affect the passenger cars’ average travel speed. The buses’ response was affected by the bus bay and curbside bus stops. The buses’ speed tendency influenced neither the passenger cars’ nor buses’ response. (2) Taxis’ arrival frequency, stopping frequency, and speed tendency were found to influence the passenger cars’ response. Taxis’ response was altered by taxis’ speed tendency, while buses’ response was affected by taxis’ arrival frequencies. (3) The number of speed bumps, the arrival frequency of passenger cars, and their speed conditions (homogeneous and heterogeneous) affect the passenger cars’ response. We expect that the findings presented in this study, along with the recommendations made from the results, may pave the way for better road design public policies.

Estimating the Capacity of a Curbside Bus Stop with Multiple Berths Using Probabilistic Models

Estimating the Capacity of a Curbside Bus Stop with Multiple Berths Using Probabilistic Models

Effect of curbside bus stops on passenger car units and capacity in disordered traffic using simulation model

ABSTRACT Representation of traffic in terms of Passenger Car Unit (PCU) is imperative to estimate capacity in disordered traffic. Many studies have been conducted on investigation of impacts of traffic and geometric conditions on traffic characteristics and PCUs. However, the sensitivity of PCUs due to roadside frictions are not adequately studied. To address this gap, this study aims to estimate PCU values for vehicles under the influence of curbside bus stop, which is the most common roadside friction in developing countries. Lack of space for providing exclusive bus bays and higher demand for public transport buses in urban roads justify the need for this study. Methodology of this study involves development and validation of a microscopic simulation model to quantify the impact of curbside bus stop on PCU as well as capacity. The results indicate the significant differences in PCU values due to the presence of curbside bus stop with varying traffic volume and composition.

Intersection traffic signal optimisation considering the impact of upstream curbside bus stops

Transit-oriented travel mode is considered as one of the most effective travel strategies for improving the level of travel service and reducing travel time and delay. Curbside bus stops are often built to support the operation of the transit system, which leads to new bottlenecks of road segments near such stops and exerts a negative impact on traffic flows of neighbouring intersections. The authors propose a traffic signal optimisation model with the objective to minimise total travel delay by considering the interaction of traffic flows between the intersections and upstream curbside bus stops. First, transits’ following and lane-changing behaviours are explored by analysing their trajectories collected by unmanned vehicle aerial video detectors. Second, transits’ occupancy time at curbside bus stops is statistically analysed by using automatic vehicle location data. They then use an equivalent-flow analysis method to quantify the impact caused by transits’ actions of lane-changing and moving into/out stop basins (including the waiting process). Such impact is integrated into the algorithm of intersection traffic signal optimisation. They finally validate the proposed signal optimisation model based on real-time traffic data collected from Nanjing, China. It is revealed that the improved model can reduce vehicle travel delay by 4.3% at the tested intersection.

Influence of Bus Bay and Curbside Bus Stop in an Urban Road

Purpose of Study: The purpose of this study is to investigate the efficiency of bus bay compare to the curbside bus stop in a midblock road segment of Dhaka city. Methodology: Vehicle composition and traffic volume were counted on-peak hours for the midblock of Azimpur road near the existing bus stop. Simulation models were developed in VISSIM, where Model 1 represented the existing road scenario with curbside bus stop and Model 2 represented the same road segment with a bus bay. Main findings: The simulation result showed that Model 2 outperformed Model 1 due to the presence of bus bay. Comparing Model 1, travel time and delay reduced by varying 1.80% to 12.5% and 6.25% to 100% respectively in Model 2 during the simulation. Similarly, average speed increased by 1.39% and density decreased by 61.29% in model 2. Application of this study: Curbside bus stops result in abrupt halt, disrupt traffic flow, and queuing of the small-sized vehicle behind buses. These bus stops caused traffic congestion and delays in urban roads which can be alleviated by alternatives, such as, bus bay. The novelty of this study: The bus bay is a good alternative to the curbside bus stop, which can improve existing traffic conditions in urban roads.