Bus Lines Research Articles

A Pilot Protection Scheme of DC Lines for MMC-HVDC Grid Using Random Matrix

The over-current capacity of half-bridge modular multi-level converter (MMC) is quite weak, which requests protections to detect faults accurately and reliably in several milliseconds after DC faults. The sensitivity and reliability of the existing schemes are vulnerable to high resistance and data errors. To improve the insufficiencies, this paper proposes a pilot protection scheme by using the random matrix for DC lines in the symmetrical bipolar MMC high-voltage direct current (HVDC) grid. Firstly, the 1-mode voltage time-domain characteristics of the line end, DC bus, and adjacent line end are analyzed by the inverse Laplace transform to find indicators of fault direction. To combine the actual model with the data-driven method, the methods to construct the data expansion matrix and to calculate additional noise are proposed. Then, the mean spectral radiuses of two random matrices are used to detect fault directions, and a novel pilot protection criterion is proposed. The protection scheme only needs to transmit logic signals, decreasing the communication burden. It performs well in high-resistance faults, abnormal data errors, measurement errors, parameters errors, and different topology conditions. Numerous simulations in PSCAD/EMTDC confirm the effectiveness and reliability of the proposed protection scheme.

Performance Analysis of Multi-Objective Demand-Responsive Transport as a Replacement for Local Bus Lines: A Case Study of Canberra Australia

Performance Analysis of Multi-Objective Demand-Responsive Transport as a Replacement for Local Bus Lines: A Case Study of Canberra Australia

Design of integrated passenger-freight transport: A multi-stakeholder perspective

Integrated passenger freight transport (IPFT) is a tactical solution that can potentially reduce travel demand and the costs of first- and last-mile services. Although the scientific interest in this topic increased in the last decade, IPFT contributions are still mostly related to the definition of a general framework. Conversely, the design of the service attributes and the evaluation of the operational performances have been object of less attention. To address such a research gap, this paper presents the results of a Delphi survey with international stakeholders. The aim is to verify the minimum requirements upon the introduction of the IPFT in both urban and rural contexts, including fare reductions for users, which are necessary to compensate for the differences as compared with passenger-only and freight-only services. The survey results indicate the necessity of an efficient service in terms of information, environmental performances, space division, and security (the last aspect refers more to passenger than to freight transport). Other attributes, such as cleanliness on board, are more debated. Policymakers and practitioners can use these findings as a benchmark for the definition of performance requirements and boundaries for designing the service. The suitability of the IPFT scheme in real-case contexts is then verified. New suburban and urban IPFT services are designed by modifying the characteristics of two existing urban and suburban bus lines that operate in the Italian provinces of Forlì-Cesena and Rimini according to both the results of the Delphi survey and the territorial specificities. The scheme’s suitability to the existing schedules is finally determined. As next steps, the new design has to be assessed through a) a stated preference survey submitted to potential users of the service; b) a supply model that verifies the matching of supply and demand under the new configuration, and c) an economic evaluation of the service, which considers the perspective of single actors.

Analysis of the time and number of stops during the operation of selected public bus line in Rzeszow

Public transport fulfils many functions in the city. Its efficient functioning improves the comfort of residents’ life and eliminates communication exclusions. One of the basic criteria to evaluate different means of transport is the travel time on a given route. This time is largely dependent on stops. In the case of city buses, some of these stops result from the need to stop at bus stops. The second major part of these stops is forced by external traffic conditions. The article is devoted to examination of the number of stops and stopping times of a city bus on a selected route. The results obtained from the research indicate the possibility of reducing travel time and thus fuel consumption. These activities are part of the development of sustainable transport and contribute to the increase in the competitiveness of public transport in the city.

Integrated solution for electric bus timetabling and vehicle scheduling combined with choices of charging locations

This paper presents a novel mathematical model, integrating timetabling and vehicle scheduling problems for electric buses. The objective is to minimize the number of buses while satisfying constraints concerning routing and charging, including design choices for where to install charging stations. The aim of the paper is to illustrate and discuss the effects of solving the timetabling and vehicle scheduling of electric buses (including where to install charging infrastructure) separately, compared to solving them jointly in one single step. For that purpose, we perform tests with: i) given timetable, that is, solving only the vehicle scheduling problem, ii) fixed headways for each line, and iii) variable headways. A small test case based on actual bus lines from Västra Frölunda, Gothenburg, Sweden, is used. From the numerical experiments, we verify that combining the two planning steps can significantly reduce the number of vehicles needed.

Boarding Stop Assignment for Public Bus Trips Using Smart Card Data: Comparison of Two Algorithms

Public transit (PT) is a challenging service to provide, as it is often subsidized and planned to serve a varying demand via fixed supply network and timetable. One critical factor is the need of spatio-temporal demand data, but, increasing use of smart card (SC) fare collection systems has provided big data for free, and become a major PT data source and enabled deep analyses of PT-based mobility helps local authorities to manage PT operations. As SC data for bus PT systems mostly records transaction location with coordinates rather than the boarding stop (BS), there is a need to associate the coordinates with the boarding stop, which is the aim of this paper. To overcome with this issue, two different algorithms were developed as i) ground truth algorithm and ii) spatial temporal stop assignment algorithm supported by kinematic models which are the scope of this paper. As there was no shift or trip information in SC data, in the first algorithm, shift and trips were determined for each bus lines which were later used to assign transactions to BS. In the second algorithm, the speeds of vehicles were calculated using GPS data, and SC transactions were assigned to the stops spatially and temporally. One of the major problems faced during the BS determination was the precision/scattering of GPS points showing the location of transaction. Thus, the conditions of the assignment results were grouped as i) on stop and ii) en-route (while vehicle moving between stations) and iii) not assigned. For the application of these algorithms, one-month SC data of Konya City (Turkey) with 4.9 million boarding transactions was used as an example. The statistics on BS assignment by two algorithms were presented and their performance in terms of running times were compared. Besides the general limitations and problems in the assignment procedures were discussed in detail.

Shuttle Bus Line Planning in Response to Unexpected Disruption in Urban Rail Transit Networks

When metro systems need to be temporarily closed due to an unexpected disruption, the metro operators have to arrange shuttle buses as alternative transport for trains, while passengers have to find new routes to complete their journeys. However, the additional shuttle bus lines might be redundant if the well-known phenomenon of the “Braesss Paradox” exists. To address this issue, this paper proposes a bi-level programming model in which the objective of the upper-level model is to minimize the number of shuttle bus lines, while the lower-level model is a UE (User Equilibrium) model that simulates the route choice of passengers. To solve this bi-level programming model, the Overload Arc-oriented Heuristics (OAH) algorithm is developed to find an initial solution, and then we develop a BS (Bi-direction Search) algorithm to obtain the optimal solution to our model. Numerical cases of the partial Beijing Metro network have proved the efficiency and effectiveness of our method, and the result shows that: (1) compared with the standard bus bridging routes, the additional shuttle bus lines can significantly reduce the number of stranded passengers; (2) the number of stranded passengers at each station can be controlled by two strategies: adjust the departure frequency of each shuttle bus line and control the passenger flow at each station.

Shift-Based Penalty for Evolutionary Constrained Multiobjective Optimization and its Application.

This article presents a new constraint-handling technique (CHT), called shift-based penalty (ShiP), for solving constrained multiobjective optimization problems. In ShiP, infeasible solutions are first shifted according to the distributions of their neighboring feasible solutions. The degree of shift is adaptively controlled by the proportion of feasible solutions in the current parent and offspring populations. Then, the shifted infeasible solutions are penalized based on their constraint violations. This two-step process can encourage infeasible solutions to approach/enter the feasible region from diverse directions in the early stage of evolution, and guide diverse feasible solutions toward the Pareto optimal solutions in the later stage of evolution. Moreover, ShiP can achieve an adaptive transition from both diversity and feasibility in the early stage of evolution to both diversity and convergence in the later stage of evolution. ShiP is flexible and can be embedded into three well-known multiobjective optimization frameworks. Experiments on benchmark test problems demonstrate that ShiP is highly competitive with other representative CHTs. Further, based on ShiP, we propose an archive-assisted constrained multiobjective evolutionary algorithm (CMOEA), called ShiP+, which outperforms two other state-of-the-art CMOEAs. Finally, ShiP is applied to the vehicle scheduling of the urban bus line successfully.

Distributed Multiagent Deep Reinforcement Learning for Multiline Dynamic Bus Timetable Optimization

As a primary countermeasure to mitigate traffic congestion and air pollution, promoting public transit has become a global census. Designing a robust and reliable bus timetable is a pivotal step to increase ridership and reduce operating cost for transit authorities. However, most previous studies on bus timetabling rely on historical passenger count and travel time data to generate static schedules, which often yield biased results in these uncertain scenarios, such as demand surge or adverse weather. In addition, acquiring real-time passenger origin/destination from a limited number of running buses is not feasible. This article considers the multiline dynamic bus timetable optimization problem as a Markov decision process model to address the aforementioned issues, and proposes a multiagent deep reinforcement learning framework to ensure effective learning from the imperfect-information game, where the passenger demand and traffic condition are not always known in advance. Moreover, a distributed reinforcement learning algorithm is applied to overcome the limitation of high computational cost and low efficiency. A case study of multiple bus lines in Beijing, China, confirms the effectiveness and efficiency of the proposed model. The results demonstrate that our method outperforms heuristic and state-of-the-art reinforcement learning algorithms by reducing 20.30% of operating and passenger costs compared with actual timetables.

Increasing public transport system operation efficiency in the city of Košice - the case study

The paper deals with the urban public transport in the city of Košice and the proposed solution to traffic congestion, which causes delays for public transport vehicles. The biggest problem is the fact that the volume of cars used for individual transport is increasing in the city, and so the resulting congestions cause time losses for public transport vehicles. In the research, traffic data was collected to determine the one bus line experiencing the greatest travel time delays and the locations where the biggest time losses occurred were identified. In order to reduce these travel time delays, solutions and their application were proposed, which could reduce time losses and ensure high-quality urban public transport.

Collaborative optimization of electric bus line scheduling with multiple charging modes

Collaborative optimization of electric bus line scheduling with multiple charging modes

Позиції автовиробників КНР на світовому автомобільному ринку

The global car market is one of the most competitive markets in the world, with characteristics including technological advancements, product diversity, competition, and innovation. The aim of the article is to study the experience and features of participation of car manufacturers of the People’s Republic of China (PRC) in the world car market. It is determined that the leading car manufacturers in the world market are China, the USA, Japan, India, and Germany. The leading exporters of cars, in terms of value, are Germany, Japan, the USA, South Korea, and Mexico, in terms of quantity – Japan, Germany, China, South Korea and the USA. It is specified that the contemporary automotive industry of the People’s Republic of China consists of a small number of large companies, most of which have a State-owned share, and thousands of small enterprises that produce auto components and spare parts for local companies. The competitive advantage of Chinese cars, which increases their exports, remains their cost. The results of the carried out trend analysis indicate that the growth of exports of cars produced in China will continue in the coming years. It is examined how the PRC government stimulated car manufacturers to achieve leadership in the production of electric vehicles. That is, electric bus lines were laid in several cities of the country and electric vehicles were purchased, all of them made in China. It was the introduction of electric public transport and taxi fleets that helped Chinese car manufacturers subsequently become leaders in the global electric transport market. In the field of production of environmentally friendly cars, the leader is BYD company, being the largest manufacturer of electric vehicles in the world. The following features of the participation of automobile companies of the People’s Republic of China in the world car market are specified: export of a wide range of cars (from the least expensive to premium), the quantitative output of which is larger than in any country in the world; the People’s Republic of China not only develops its own production, but also expands its presence in the global automotive industry, using acquisitions, joint ventures and strategic partnerships; China is one of the largest markets for potential car consumers in the world, from which global car manufacturers are being gradually squeezed out, who cannot compete with locally produced cars in terms of price and range; it is projected that the average annual growth rate in the automotive industry of the People’s Republic of China in the coming years will reach 4.0%. It is concluded that China’s car manufacturers are active participants in the global car market and leaders in the export of new cars, including electric vehicles, the quality and safety of which have significantly improved in recent years.

Energy Demand Model of Battery E-Buses for LPT: Implementation, Validation and Scheduling Optimization

The progressive conversion of conventional bus fleets into full-electric fleets have gained focus in recent years, instilled by awareness about the environment and significant trends of urbanization. Public transport operators in major cities worldwide have put efforts into fulfilling this change. However, an efficient electrification process is still a challenge for most operators. This paper aims to propose an E-Bus vehicle model that estimates the actual energy consumption. The proposed model is implemented on the case study of a real bus line for Local Public Transport (LPT) and considers all technical characteristics of the vehicle. Real-time input data are represented by real driving cycles of the actual bus fleet and slope profile of the line. Real-time input data allow to establish directly the influence on the energy consumed during real operations. As simulation results, the global energy consumption and battery State of Charge (SOC) are then computed for the whole daily service operations. The simulation results are validated with the real data available and several scenarios are then considered within the simulations. Based on the results obtained, further improvements are proposed and discussed aiming to optimize the utilization of bus fleet, regarding both vehicles scheduling and new charging solutions.

Design and test of a novel 1kw Stirling engine generator

This paper describes a practical design of a novel Stirling engine generator and 1kW machine test data. This machine’s configuration is a 4 cylinder double acting Stirling engine coupled with a Halback PM generator in line. This machine operates on the Stirling thermodynamic cycle and electromagnetic cycle established in 19th century by Carnot and Faraday. This machine’s unique function is bidirectional exchanging between thermal energy and electric power, as a same rotating direction of a same shaft. And the shaft speed can be controlled by three phases voltage source PWM inverter during both function such as the motor cooler mode and the engine generator mode. So, this unit can generate an electricity by using to many kinds of external heat source. As the heat source temperature changes as the shaft speed changes for the amount of absorbed heat changing in order to keep a cylinder temperature (700 ℃) and a heater tube temperature (<770 ℃). Consequently, the unit will achieve a highest efficiency keeping as a creep rapture strength limit level of the heater tubes. This unit has achieved 1.1 kW effective electric power, and 20.1% efficiency using LPG fuel, and 23.7 % thermal energy to electrical energy. This unit can connect to a commercial AC grid line by another inverter and, also connect a high voltage battery and a solar cell on the high voltage DC bus line in the PWM inverter.

Operational Effıciency and Energy Saving Analysis of Urban Transportation: The Case of Akcaray

Light rail systems are sustainable, energy-efficient, and eco-friendly alternatives to public transport systems that can offer solutions to increasing traffic density. As a solution to that traffic congestion, Akcaray, the first public transportation light rail system in Kocaeli, was launched by Ulasımpark in Kocaeli in 2017. In this study, operational efficiency and service level performance of 12 trams belonging to Akcaray, and 4 bus lines that interact with Akcaray route are compared with one another by Data Envelopment Analysis. It is found out that while the performance efficiency score of Akcaray is 100% in all 12 trams, it is 100% for one bus line only out of 4 busses. In addition, transportation costs, such as energy/fuel, maintenance cost, accident and environmental costs are calculated, and compared separately for both transportation options. Because Akcaray offers less energy consumption per passenger, it is calculated that USD 317,737/year can be saved, thus as a result, Akcaray consumes 1,3 million Sm3 compressed natural gas less while performing public transportation.

An optimal charging scheduling model and algorithm for electric buses

Electrification poses a promising low-carbon or even zero-carbon transportation solution, serving as a strategic approach to reducing carbon emissions and promoting carbon neutrality in the transportation sector. Along the transportation electrification pathway, the goal of carbon neutrality can be further accelerated with an increasing amount of electricity being generated from renewable energies. The past decade observed the rapid development of battery technologies and deployment of electricity infrastructure worldwide, fostering transportation electrification to expand from railways to light and then heavy vehicles on roadways. In China, a massive number of electric buses have been employed and operated in dozens of metropolises. An important daily operations issue with these urban electric buses is how to coordinate their charging activities in a cost-effective manner, considering various physical, financial, institutional, and managerial constraints.This paper addresses a general charging scheduling problem for an electric bus fleet operated across multiple bus lines and charging depots and terminals, aiming at finding an optimal set of charging location and time decisions given the available charging windows. The charging windows for each bus are predetermined in terms of its layovers at depots and terminals and each of them is discretized into a number of charging slots with the same time duration. A mixed linear integer programming model with binary charging slot choice and continuous state-of-charge (SOC) variables is constructed for minimizing the total charging cost of the bus fleet subject to individual electricity consumption rates, electricity charging rates, time-based charging windows, battery SOC bounds, time-of-use (TOU) charging tariffs, and station-specific electricity load capacities. A Lagrangian relaxation framework is employed to decouple the joint charging schedule of a bus fleet into a number of independent single-bus charging schedules, which can be efficiently addressed by a bi-criterion dynamic programming algorithm. A real-world regional electric bus fleet of 122 buses in Shanghai, China is selected for validating the effectiveness and practicability of the proposed charging scheduling model and algorithm. The optimization results numerically reveal the impacts of TOU tariffs, station load capacities, charging infrastructure configurations, and battery capacities on the bus system performance as well as individual recharging behaviors, and justify the superior solution efficiency of our algorithm against a state-of-the-art commercial solver.

Spatial Accessibility Analysis of Medical Facilities Based on Public Transportation Networks.

Aiming to look at the problems of the unreasonable layout of medical facilities and low coverage of primary medical services. This paper selects tertiary grade A hospitals, general hospitals, specialized hospitals, community-level hospitals, clinics, and pharmacies in the main urban areas of Chongqing as research objects. The nearest analysis, kernel density, mean center, and standard deviational ellipse method were used to analyze the spatial differentiation characteristics of medical facilities and public transportation stations. Spatial accessibility was assessed from the perspective of service area ratios and service population ratios by constructing multiple modes of transportation (pedestrian systems, bus lines, rail lines). The results show that (1) the spatial layout of medical facilities in the main urban area of Chongqing is unbalanced; and the spatial distribution of medical facilities is characterized by "large agglomeration, small dispersion" and "multi-center group"; (2) the sub-core circle is centered on the Southwest University Area in Beibei District, the University Town Area in Shapingba, the Yudong Area and Lijiatuo Area in Banan District, the Pingan Light Rail Station Area in Dadukou District, the Chongqing No. 8 Middle School Area in Jiulongpo District, the Tea Garden Area in Nanan District, and the Jiangbei Airport Area in Yubei District; (3) the medical facilities with the weakest average accessibility are tertiary grade A hospitals, and the strongest are pharmacies; (4) the areas with vital average accessibility are Yuzhong District, Shapingba District, Dadukou District, and Nanan District.

A Novel Multi-Objective Energy Management Strategy for Fuel Cell Buses Quantifying Fuel Cell Degradation as Operating Cost

Fluctuation in a fuel cell’s output power affects its service life. This paper aims to explore the relationship between power output fluctuation and energy consumption and the cost of the fuel cell system. Hence, based on the actual driving information of vehicles, a novel multi-objective energy management strategy (EMS) for fuel cell buses (FCBs) that quantifies fuel cell life as operating cost is proposed. The actual driving data of FCBs on bus line 727 in Zhengzhou, China, were collected. Based on this, considering the degradation factors of the fuel cell and power battery hybrid energy system, a multi-objective cost framework was established to quantify the life degradation as consumption cost. Furthermore, the influence of different power change limits on the performance of the EMS was analysed based on real-world driving data and the typical Chinese city bus driving cycle, respectively. The simulation results show that the degradation cost of the fuel cell can be effectively reduced when the power change limit is 1 kW, and the simulation results obtained using real-world driving data are very different from those obtained using typical city bus driving cycles. This study provides a reference for the application of a vehicle energy management strategy in real-world scenarios as well as highlights its significance.

Preferences for first and last mile shared mobility between stops and activity locations: A case study of local public transport users in Utrecht, the Netherlands

Shared transport modes can potentially contribute to first and last mile connections of public transport (PT) trips but this remains quite underexplored in the literature. Our study explores the user preferences for shared modes as first and last mile option to connect activity locations. We have focussed on local public transport in the Utrecht province, The Netherlands, which includes bus and tram lines. Its diversity in land use and PT network density, the overall high bicycle usage, as well as the increased proliferation of shared mobility concepts yield promising information which can be a harbinger for future PT integration worldwide. For both the urban and suburban areas of the province, we have designed and conducted a stated choice experiment. Respondents were able to choose from shared bicycles, e-bikes, e-scooters, and e-mopeds to reach their urban destination from a PT stop. For suburban destinations, we also included light-electric vehicles (LEVs), e-cars, and demand-responsive taxi services. Such a complete list of possibilities to travel by shared modes allows comparing the different options and producing trade-offs not available yet in the literature. A sample of 499 respondents (285 urban and 214 suburban PT travellers) considered their first and last mile mode choice of a recent PT trip in light of the new options. Results show that shared (electric-)bicycles and e-scooters are generally preferred over other shared mobility options. The latter specifically targets younger people (<26 years) and travellers towards suburban destinations. Still, a majority of PT users prefers not to use shared modes in the first and last mile. We found that age, current cycling behaviour and weekday/weekend travelling are the most important factors which determine these preferences. We argue that shared bicycles and e-bikes are the most capable modes in providing benefits to PT travellers in this context and, given the relatively low travel time sensitivity, can best be distributed around the most important PT stops.

Online distributed optimization for spatio-temporally constrained real-time peer-to-peer energy trading

The proliferation of distributed renewable energy triggers the peer-to-peer (P2P) energy market formations. To make profits, prosumers equipped with photovoltaic (PV) panels and even the energy storage system (ESS) can actively participate in the real-time P2P energy market and trade energy. However, in real situations, system states such as energy demands and renewable energy power generation are highly uncertain, making it difficult for prosumers to make optimal real-time decisions. Moreover, severe problems with the physical network can arise from the real-time P2P energy trading, such as bus voltage violations and line overload. To handle these problems, this work first formulates the real-time P2P energy trading problem as a spatio-temporally constrained stochastic optimization problem by considering ESS and the spatial physical network constraints. To deal with the uncertainties online, a modified Lyapunov optimization method is innovatively proposed to approximately reformulate the stochastic optimization problem into an online one by relaxing the time-coupling constraints. Compared with the state-of-the-art online methods, the proposed one renders more flexibility and better performance for the real-time P2P energy market operation. Additionally, to protect the prosumers’ privacy, an online distributed algorithm based on the consensus alternating direction method of multipliers (ADMM) is developed to solve the reformulated online problem by decoupling the spatial constraints. The theoretical near-optimal performance guarantee of the proposed online distributed algorithm is derived, and its performance can be further improved by minimizing the performance gap. Simulation results demonstrate that the proposed online distributed algorithm can guarantee the fast, stable, and safe long-term operation of the real-time P2P energy market. Allied with a performance gap minimization step, the proposed online distributed algorithm can obtain approximately a 53.10% cost reduction compared to the greedy algorithm for the intraday market operation.