Passenger Delay Research Articles

Modelling Approach to Develop a Multimodal Transportation Network

Multimodal transportation (MMT) refers to a system that utilizes various means of transportation to transfer people & goods from one place to another. Transit operations are measured as the maximum number of passengers that can be carried past a fixed route, in a given period. Investing in and using multiple modes of transportation does not only bring efficiencies but also goes a long way to reduce time & delay, as well as the overall cost of transportation. This paper presents the efficient mode of transportation system at selected routes in the Bengaluru city, the route stretch selected is 12.2 km in length and it has 8 major intersections. The type of pavement surface consists of both bituminous and Reinforced cement concrete (R.C.C). The complete study stretch is a 2-way 4-lane road. This study provides walkability-index, traffic volume studies in terms of passenger car unit (PCU), time and delay study, and Cost & time analysis. Four modes of transportation are used in this study to find the effective multimodal-transportation system namely, 2-wheeler, 4-wheeler, para-transit [15], and buses/metro. The outcome of this paper is to arrive at the shortest distance for reducing delay & time, and cost-effective travel using multi-mode transport. While focusing on the present condition of the para-transit transport facilities. The time, delay & cost during MMT and to provide a safe, cost-effective & convenient way to travel or transport. The result shows the reduction in time, cost & delay of transportation by using the MMT model. This MMT system could be adopted as an efficient mode of transportation on this route. Similar rural-urban junction routes around the world could use this approach for effective transit by making a modal study.

Regional Coordinated Bus Priority Signal Control Considering Pedestrian and Vehicle Delays at Urban Intersections

Bus priority signal control can reduce bus delay at intersections and improve bus operation efficiency. The existing research focus mainly on bus priority control methods at isolated intersections, as well as urban arterial corridors. Rarely existing works consider a network-level bus priority control. Treating regional-wide intersections can be challenging, given that more traffic directions and large multi-modal traffic volume should be considered. The conventional transit signal priority (TSP) research focus on the delay of buses and social vehicles and neglect the delay of pedestrians. To fill these gaps, this paper proposes a regional coordinated bus priority signal control (RCBPSC) method, which is a network-level bus priority control method considering pedestrian and passenger delays. This method is divided into two stages. The first stage is the regional coordinated signal control to obtain the basic signal timing schemes. The second stage is the bus priority signal control. At this stage, the timing schemes at each intersection will be adjusted according to the bus arrival time and the delays. In order to verify the effectiveness of this method, we choose four intersections in Chengdu to study. The results show that the total delay of the proposed method at the first stage (control case 1) can be reduced by 602s (2.3%) and 606s (3.7%) comparing with the conventional timing method in the peak and non-peak period. At the second stage, the proposed method can reduce more pedestrian delay than the conventional TSP method in both <xref ref-type="other" rid="other1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">scenario 1</xref> and <xref ref-type="other" rid="other2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">scenario 2</xref> .

Algorithm and Application of Multi-modal Evacuation Strategy for Intercity Railway Disruption in a Metropolitan Area

When an emergency situation befalls the intercity high-speed railway system, response contingency always focuses on mitigating the interruption to the original operation. This study addresses an evacuation problem for stranded passengers by coordination of multi-modal transit, with the immediate recovery of transport corridors and the redesign of transit routes. A multi-modal transit-based evacuation strategy is proposed through a bi-level optimization model. The model simultaneously formulates the selection of lines, vehicle scheduling, and passenger assignment that trades off passenger delay versus operating cost. The upper level uses an integer program to determine the transit lines and fleet size, and the lower level assigns passengers onto multi-modal routes considering their perceptions of transfer and vehicle congestion. A hybrid heuristic algorithm is proposed to solve the complexity from back-up conditions and nonlinear on-route utility. The case study is based on a disruption to the Beijing-Hebei metropolitan transit system, which is composed of five transit modes, to analyze the conflicting objectives under different mode combinations and network topologies. The adaptation for demand distribution with regard to trip distance is studied to recommend the vehicle composition in a realistic situation. The application and analysis procedure aim to enhance the decision-support system. Results show that mode combinations could provide time and cost saving solutions and extend the Pareto frontier. Effectiveness of mode combination is not equivalent to different demand distributions. Multi-modal collaboration would effectively accelerate the evacuation and save costs. These findings may be of interest to decision makers developing efficient response strategies to improve post-disruption resilience.

Dynamic Multi-Bus Dispatching Strategy With Boarding and Holding Control for Passenger Delay Alleviation and Schedule Reliability: A Combined Dispatching-Operation System

The continuing increase of the on-road private cars is contributing to a deterioration of the urban traffic system. Public transportation is widely used to tackle this issue due to its large ridership. In this paper, we propose a multi-bus dispatching strategy combined with the boarding and holding control (MBDBH) to improve bus utilization and further decrease the passenger excess delay. Dispatching adjustments and operation control are taken into account in the system. At the dispatching level, on the one hand, either a bus platoon or a single bus can be dispatched for each trip to provide adaptive bus capacity to match the highly-fluctuated stop demands, on the other hand, we adjust the bus dispatching time based on the existing timetable to minimize passenger excess waiting time to a large extent. Meanwhile, the operation level incorporates both holding strategy and boarding limit strategy to bring more flexible adjustments in improving bus service. Besides the efficiency, we also minimize the headway variation in order to maintain a high system reliability. The problem is formulated as a Mixed Integer Nonlinear Programming (MINP) problem, which is solved by the commercial solver Gurobi. With the computational complexity as a concern, we propose a distributed algorithm to implement dual decomposition based on the partial Lagrangian relaxation. Finally, numerical examples are investigated to illustrate the significant time reduction of distributed algorithm and the efficiency of our proposed strategy: The proposed MBDBH model can reduce roughly 50% and 30% of remaining passenger volumes when compared with the timetable-based fixed schedule and the optimized single-bus dispatching schedule, respectively.

A Vertiport Design Heuristic to Ensure Efficient Ground Operations for Urban Air Mobility

Urban Air Mobility is a novel concept of transportation with unknown market potential. Even in conservative estimates, thousands of operations could be expected on a single vertiport. This exceeds known heliport operations, which is the most comparable existing mode of transport—by far. Vertiport operations, in particular the dynamics on the airfield, are not well understood; in the following article, we want to address this research gap. By using means of agent-based simulation, the following design drivers were identified: peaks in demand, imbalance between arrivals and departures, pad operations and gate operations. We calculate a practical hourly capacity of 264 movements for our baseline scenario consisting of 4 pads, 12 gates and 20 stand. We are further able to shown that avoiding this peak and staying below a maximum imbalance between arrivals and departures of less than 33 ensures an average passenger delay of less than 3 min. Lastly, we present a parameter study varying the number of pads and gates, the length of approach/departure and boarding/de-boarding and the level of demand. The results of this study are aggregated into a graphical design heuristic displaying the interchangeability of the mentioned aspects.

Recovery of flights disrupted by snowstorm

PurposeTo reduce the time of flight rescheduling, reduce the total delay cost of all flights to a minimum and put forward more references for passengers to take flights, this paper aims to mainly study the recovery of flights affected by snow disaster within the minimum delay time.Design/methodology/approachThe temporal and spatial network flight recovery model is used to optimize all flights of various types of aircraft, and the adjusted flight schedule based on minute delay time is obtained. In addition, for passenger travel flights, the impact of passenger delay cost on the total delay time is minimized as an objective function to calculate the passenger delay cost.FindingsIn this paper, the actual departure time of aircraft is sorted in ascending order. Up to five planes can take off from the runway every 5 min, and the 10-min decision interval is successively delayed. The actual arrival time is sorted by the same method and the sequential delay is calculated to obtain the adjusted flight schedule. As a result, it takes less time to reschedule flights.Originality/valueIn this paper, heuristic algorithm is used to adjust the schedule of delayed flights flexibly, which is convenient for manual modification. This decision method has good robustness and can partially adjust the interrupted flights without affecting other scheduled flights while maintaining the stable operation of the whole plan, greatly improving the efficiency of civil aviation operations and reducing the impact of flight delays.

Passenger Volumes and Dwell Times for Commuter Trains: A Case Study Using Automatic Passenger Count Data in Stockholm

This study investigates the relationship between passenger volumes and the frequency and size of dwell times for commuter trains. We use data collected by automatic passenger count systems in Stockholm and show that dwell times often take longer than scheduled. To understand the effect of passenger volumes on delays, we use the frequencies of delays for different passenger volumes and delay sizes. We find that these frequencies differ significantly from a frequency distribution independent of passenger volumes, indicating that passenger volumes have an effect on the frequency of dwell time delays. Neglecting passenger volumes underestimates the frequency of delays in most cases, especially for smaller delays. Although the frequency of dwell time delays increases as passenger volumes increase, the same is not necessarily true for their size. The relationship between passenger volumes and delay sizes is thus non-linear, and it depends on scheduled dwell times. We conclude that small increases in dwell times can result in sharp increases in on-time performance but that only increasing dwell times is not sufficient. Measures to speed up the boarding and alighting process are also necessary.

An Occupancy-Based Adaptive Signal Control for a Congested Signalized Intersection in the Low CV Penetration Environment

Adaptive signal control (ASC) is a well-researched topic that offers an efficient way for traffic management. It possesses a powerful ability to accommodate complex and constantly changing urban transportation networks. With the development of vehicular communication, CV-based ASC shows remarkable advantages compared with the traditional ASC system. Though the existing CV-based ASC strategies were proposed in the past few years, however, there are still issues to overcome. Most of the studies on CV-based ASC are based on the assumption of high CV penetration rate, which often result in poor performance when applied to low CV penetration environments. Besides, the lack of consideration for mixed traffic flow, which is in terms of both the vehicle types and CV penetration of different types of vehicles. To solve these issues, this paper developed an Occupancy-Based ASC strategy for a congested signalized intersection to optimize signal timing and reduce total passenger delay in the low CV penetration environment. Focused on the issues existing in the low CV penetration environment, a Maximum Likelihood Estimation (MLE) model was proposed to estimate vehicle arrivals, and two traffic models, MicroDM and MacroDM, were developed to model the mixed traffic flow and estimate passenger delay. With the purpose of offering fair treatment to passengers approaching the intersection, we proposed an Occupancy-Based Adaptive Signal Control strategy. By transforming the complex signal control problem into a mixed-integer linear programming problem, we found the optimal solution for minimizing total passenger delay. We then evaluated the proposed Occupancy-Based ASC strategy using simulation case studies. The results show that changing traffic status could be captured and estimated with the real-time CV trajectory data as input. Applying the Occupancy-Based ASC control strategy, phases with HOVs or more vehicles will be allocated more travel time. In particular, optimization results show that the proposed Occupancy-Based ASC strategy effectively balances passenger travel demands during peak volume periods.

A coordinated bus bridging and metro short turning model in response to urban metro disruptions

Abstract When an urban metro disruption occurs, the urban metro usually operates in a short turning mode and bus bridging is the typical way to relink the disconnected stations. For emergency response models dealing with urban metro disruptions, minimizing passenger delay in the bus bridging process and the metro short turning process is usually the optimization objective. In this study, we simultaneously consider the passenger delay in the bus bridging process and the metro short turning process to develop a coordinated emergency response model dealing with urban metro disruptions. The proposed coordinated model is validated in an actual urban metro line using actual passenger boarding demand data. Useful insights in response to urban metro disruptions are obtained.

Naïve Bayes-Based Transition Model for Short-Term Metro Passenger Flow Prediction under Planned Events

Short-term passenger flow prediction under planned events is important to reduce passenger delay and ensure operational safety in metro systems. However, most studies make predictions under normal conditions. The study proposes a naïve Bayes transition model for short-term passenger flow prediction under planned events. The target prediction scenario identification is modeled as a binary classification problem using naïve Bayes. The sub-models are developed using gradient boosting decision tree (GBDT) and deep learning (DL) models for normal and planned event scenarios with predictor variables tailored to different passenger demand patterns. The sub-predictor from GBDT or DL is selected based on the inferred prediction scenario. The case study uses automatic fare collection (AFC) data of Shanghai and Hong Kong metro systems. The results show that the proposed model outperforms other representative individual and fusion models. The results also highlight the effectiveness of the predictive transition mechanism between the normal and planned events and also the event information representation.

Vertiport Operations Modeling, Agent-Based Simulation and Parameter Value Specification

Urban air mobility (UAM) is the idea of creating a future mobility market through the introduction of a new mode of aerial transport with substantial travel time advantages. A key factor diminishing travel time savings is vertiport processes. So far, vertiport throughput capacity has only been studied in a static manner using analytical methods, which has been found to be insufficient. This paper wants to increase the level of understanding of operational dynamics on vertiport airfields by being the first to apply agent-based simulation. For this purpose, an existing vertiport model consisting of pads, gates and stands was refined through two means. First, a sensitivity study with over 100 simulations was executed shedding light on the driving processes on a vertiport airfield. Second, an expert interview series with 17 participants was conducted, letting the experts evaluate the model and specify relevant parameter values. Three main results should find mention here: (1) Pad operations were identified to be most impactful on passenger delays. (2) Pad and gate processes have a threshold capacity beyond which delays increase exponentially. (3) A refined vertiport model is presented, including the 27 most relevant parameters and their value specification. In conclusion, this paper finds that optimized vertiport airfield design is crucial to UAM operations, and dynamic passenger and vehicle interactions cannot be neglected.

A Comparative Study of Probabilistic and Deterministic Methods for the Direct and Indirect Costs in Life-Cycle Cost Analysis for Airport Pavements

Airports play a critical role in transporting goods and passengers and supporting the growth of the world economy. Airports spend huge sums annually to maintain and improve pavement functions by expanding the runways, taxiways, and aprons, and perform routine maintenance and rehabilitation of the existing pavements. Besides the traditional direct costs, a comprehensive airport pavement management system should also consider indirect costs such as fuel, crew, passenger delay, aircraft maintenance, and loss of airport revenue when conducting a life-cycle cost analysis (LCCA). Engineers, managers, and stakeholders can make better decisions on the appropriate pavement maintenance and rehabilitation strategies by performing economic analyses of the direct and indirect costs. This study performed probabilistic and deterministic LCCA to contrast the effect of direct costs vis-a-vis indirect costs in airport pavement management. A case study found that indirect costs could contribute up to 20% of the total costs when using Portland cement concrete (PCC), hot mixed asphalt (HMA), and crack seat overlay (CSOL). Previous research did not give much attention to maintenance since the researchers believed that routine maintenance makes up only an insignificant percentage of the LCCA. However, routine maintenance of HMA and CSOL makes up 10.2% and 14.2% of the total cost. The rehabilitation cost of PCC makes up 16.3% of the total cost, and the rehabilitation cost for HMA and CSOL makes up 25.4% and 35.2% of the total cost.

Competence of Bus Rapid Transit Systems Coupled with Transit Signal Priority at Signalized Junctions

Abstract One of the primary causes of poor public transport performance is delays at intersections. Among the efficient and sustainable solutions to boost mass transportation performance, Bus Rapid Transit (BRT) consists of infrastructures integrating dedicated bus lanes and smart operational service with different ITS technologies like Transit Signal Priority (TSP). This research studies the competence of buses operating on junctions of the BRT corridor where they have Signal Priority on the dedicated lane. The studied intersection is located around the center of the Addis Ababa BRT-B2 line, which is relatively gentle grade and characterized by the high traffic and pedestrian volume. Microscopic models were created for the chosen intersection, along with possible calibration and validation; moreover, a statistical comparison was performed to evaluate different scenarios with the goal of displaying the deployment benefits. To assess the performance of BRT buses and their overall influence on general traffic, scenarios with and without TSP were evaluated. PTV VISSIM and the VisVAP add-on simulation program were used to examine TSP alternatives. Incorporating TSP reduced the travel time by up to 4.78% in the priority direction, the average travel speed increased by 7.25%, and the queue length also reduced by a maximum of 6%, whereas in the non-priority direction, the queue length increased by a maximum of 2.5%. Moreover, the overall average passenger delay has reduced by an average amount of 15%. One of the simplest ways to improve transit performance could be signal priority strategies, which has a minor influence on the general traffic.

Load-sensitive bus headway control for reducing onboard passenger waiting time

Regularity in the bus schedule on low frequency lines or the maintenance of headways on high frequency lines are desired in the operation of public transportation. Bus holding is a technique used for this purpose, but it may incur in delays for onboard passengers. Previous work based on a predictive control method identified a better performance when the holding actions were concentrated in stations where the buses were emptier. Based on these results, the forward headway and the two-way headway feedback control methods, both operated with static gains and mathematically and computationally simpler than predictive control, are modified to operate with variable gains according to the bus load using two different techniques. A variable slack, dependent on the bus load, is also incorporated into the controllers. Microsimulations of a BRT corridor with concentrated and distributed demand patterns have shown that the proposed techniques improve the system performance when compared to the corresponding methods with fixed gain.

Predictive and Prescriptive Analytics Toward Passenger-Centric Ground Delay Programs

Ground delay programs (GDPs) comprise the main interventions to optimize flight operations in congested air traffic networks. The core GDP objective is to minimize flight delays, but this may not result in optimal outcomes for passengers—especially with connecting itineraries. This paper proposes a novel passenger-centric optimization approach to GDPs by balancing flight and passenger delays in large-scale networks. For tractability, we decompose the problem using a rolling procedure, enabling the model’s implementation in manageable runtimes. Computational results based on real-world data suggest that our modeling and computational framework can reduce passenger delays significantly at small increases in flight delay costs through two main mechanisms: (i) delay allocation (delaying versus prioritizing flights) and (ii) delay introduction (holding flights to avoid passenger misconnections). In practice, however, passenger itineraries are unknown to air traffic managers; accordingly, we propose statistical learning models to predict passenger itineraries and optimize GDP operations accordingly. Results show that the proposed passenger-centric approach is highly robust to imperfect knowledge of passenger itineraries and can provide significant benefits even in the current decentralized environment based on collaborative decision making.

Optimization Model for Rail Line Crossover Design Considering the Cost of Delay

In this study, we introduce a method to optimally select the crossover locations of an independent rail line from a set of possible crossover locations considering a fixed number of crossovers that must be used in the design. This optimal selection aims to minimize the cost of passenger delay. Previous research showed that including passenger delay in the decision of rail design choices could be beneficial from economic and societal perspectives. However, those studies were only able to evaluate a few alternatives, because the degraded schedules had to be determined manually. In this research, we introduced an integer nonlinear model to find the best crossover design. We further developed an algorithm to evaluate a set of crossovers and determine the cost of delays for all segments on a rail line given a set of potential disruptions. The monetized cost of passenger delays was used to analyze the tradeoff between the unreliability costs emerging from the delay of passengers in the case of disruptions, and the total number of required crossovers. Our model was applied on a light rail line in Bergen (Norway) resulting in 10% reduction in relation to passenger delays without increasing the number of crossovers; thus, ensuring that there were no additional costs.

Lane-design for mixed pedestrian flow in T-shaped passage

T-shaped passage is one of the most important facilities in urban rail transit station, and the crowded phenomena always appear during peak hours. Mixed pedestrian flow in T-shaped passage may generate some conflicts, which causes a lot of delays for passengers. For reducing conflicts and improving efficiency in T-shaped passage, we designed the walking lanes for mixed pedestrian flow with different origins (Os) and destinations (Ds), and the preference strength was proposed to perform lane-design rule. A cellular automata (CA) based pedestrian simulation model with the lane-design was built, and we simulated the mixed pedestrian flow with the effect of lane-design on the platform of MATLAB software. Simulation results indicate that pedestrian conflicts were reduced and the efficiency of passing was improved. Reasonable lane-design was useful for mixed pedestrian flow, and it could provide technical support for the planning and design of pedestrian facilities.

Impacts of real-time information levels in public transport: A large-scale case study using an adaptive passenger path choice model

Public transport services are often uncertain, causing passengers’ travel times and routes to vary from day to day. However, since door-to-door passenger delays depend on both intended and realised routes, they are difficult to calculate, as opposed to vehicle delays which can be derived directly from the widely available Automated Vehicle Location (AVL) data of the public transport system. In this study we use three months of such historical AVL data to calculate corresponding realised routes and passengers delays in a large-scale, multi-modal transport network by formulating and implementing an adaptive passenger path choice model in an agent-based scenario of Metropolitan Copenhagen with 801,719 daily trips. The proposed model allows analysing five different levels of real-time information provision, ranging from no information at all to global real-time information being available everywhere. The results of more than 258 million (positive or negative) passenger delays show that variability of passengers’ travel time is considerable and much larger than that of the public transport vehicles. It is also shown that obtaining global real-time information at the beginning of the trip reduces passengers delay dramatically, although still being inferior to receiving such along the trip. Additionally, being able to automatically obtain real-time passenger information while walking and being on-board public transport services is found not to lead to considerable improvements compared to acquiring such information manually while waiting at stops, although slight benefits are demonstrated in supplementary models run with pseudo-intelligent vehicle delay forecasting.

A Bus Signal Priority Model at Oversaturated Intersection under Stochastic Demand

This paper focuses on the optimization of bus signal priority with the consideration of the stochastic traffic demand. Based on a situation of the variability of traffic composition, the phase clearance reliability (PCR) value of each phase and traffic composition ratio is introduced to reflect the traffic condition at intersection. Then, a bus signal priority optimization model is proposed with the purpose of the maximum of the total vehicular departure as the optimization goal. In order to obtain the optimal solution, an improved algorithm is designed by introducing the PCR value search strategy. Finally, two cases’ study is exhibited to demonstrate the reasonability of the model, theory, and algorithm. The result shows that the model can not only clear the queue under the condition of continuous dynamic traffic flow but also reduce the vehicle queuing and passenger delay.

An Overlapping Phase Approach to Optimize Bus Signal Priority Control under Two-Way Signal Coordination on Urban Arterials

With the consideration of the uneven traffic volume distribution at intersections on urban arterials, this paper aims to minimize the overall passenger delay (buses and private vehicles) at intersections and identify the applicable conditions of the proposed method with field data. The overlapping phase-based signal control logic and the bus priority control algorithm under two-way signal coordination on arterial roads are proposed. The vehicular capacities and occupancies for buses and passenger cars are considered in the evaluation of the method performance. A field test was carried out at two major intersections on an arterial road in Hefei, China. With the test data, the proposed method is examined and the possible influencing factors are analyzed for identifying the corresponding applicable conditions. The analysis result shows that the application of the overlapping phase helps to provide a relatively flexible signal control for the varying traffic demands at intersections. Compared to the conventional phase, it isof more practical significance to consider overlapping phase and apply bussignal priority control under two-way signal coordination according to the condition of uneven traffic volumedistribution at intersections on urban arterials. The proposed method can effectively decrease the total passenger delay at the intersections on urban arterials under certain applicable conditions. The possible factors influencing the method applicability are identified as well. It is verified that bus signal priority control under the two-way signal coordination, based on overlapping phases, is more conducive to improving traffic efficiency on urban arterials. Regarding the influencing factors and the applicability of the proposed method, the results show that not all situations are conducive to decreasing passenger delay at intersections. The proposed method should be applied under certain applicable conditions and principles in order to efficiently and effectively improve the traffic efficiency on arterial roads.