Study on the Optimal Improvement of the Bus Station

2012 ◽  
Vol 253-255 ◽  
pp. 1776-1781
Author(s):  
Wen Hua Jiang ◽  
Xian Xiang Wang ◽  
Hang Fei Lin
Keyword(s):  
Site Location ◽  
Bus Stop ◽  
Site Layout ◽  
Urban Bus ◽  
Bus Station ◽  
Bus Stops

Starting from several aspects of site location, site size and site layout, this document studies the urban bus stop systematically, proposes the setting principles of urban bus stop. Take Yiwu bus stops for example, which focus on the analysis of the reasonable setting of the sites, and has provided guidance for the layout of urban bus stop.

Optimization of Urban Bus Stops Setting Based on Data Mining

2021 ◽  
pp. 2159028
Author(s):  
Ganglong Duan ◽  
Xin Ma ◽  
Jianren Wang ◽  
Zhishi Wang ◽  
Yan Wang
Keyword(s):  
Public Transportation ◽  
Real Life ◽  
Matrix Analysis ◽  
Operating Efficiency ◽  
Gps Data ◽  
Data Set ◽  
Business System ◽  
Urban Bus ◽  
Bus Station ◽  
Bus Stops

The unreasonable setting of urban bus stops is a common problem in real life, which seriously affects people’s happiness, sense of belonging and brand in the city. However, the existing related research on the above problems generally has the defects of high technical complexity and high cost. Therefore, we aim to propose a way to optimize the setting of urban public transportation stations and reduce the technical complexity and high cost of existing public transportation station optimization by using artificial intelligence algorithms. First, we extract and integrate bus GPS data and bus card swipe data in the business system and perform exploratory analysis on the pre-processed data. Second, the original k-NN algorithm is improved, and an ik-NN algorithm is proposed to determine the cardholder’s boarding point. Then, we divide the upstream and downstream lines to calculate the total number of upstream and downstream passengers. Third, we propose an algorithm for calculating the number of passengers getting off at bus stations and calculating the number of passengers getting on and off at each bus station. Finally, according to the number of passengers getting on and off at each bus station, the OD matrix is constructed, the residents’ travel rules are analyzed, and optimization suggestions for the setting of urban bus stations are proposed. This paper selects the public transit GPS data set and swipe card data set of Shenzhen, China for experiments. The experimental results show that: (1) Compared with K-means, the ik-NN algorithm we proposed can effectively determine the actual car station of each cardholder, and the algorithm is less sensitive to feature dimensions. At the same time, the ik-NN algorithm has a high operating efficiency and is less affected by the “[Formula: see text]” value. (2) The calculation algorithm for the number of passengers getting off at bus stations can effectively use the existing data of the business system to determine the number of passengers getting off at each bus station. Therefore, the calculation times of this algorithm are low, and the accuracy is high. (3) The optimization suggestions for bus stations based on the OD matrix analysis of residents’ travel rules meet the needs of urban development and have certain reference value.

Modeling Bus Capacity for Bus Stops Using Queuing Theory and Diffusion Approximation

2021 ◽  
pp. 036119812110302
Author(s):  
Chao Wang ◽  
Weijie Chen ◽  
Yueru Xu ◽  
Zhirui Ye
Keyword(s):  
Approximation Method ◽  
Service Time ◽  
Diffusion Approximation ◽  
Coefficient Of Variation ◽  
Queuing Theory ◽  
Queuing Model ◽  
Bus Stop ◽  
Proposed Model ◽  
Bus Stops ◽  
Bus Service

For bus service quality and line capacity, one critical influencing factor is bus stop capacity. This paper proposes a bus capacity estimation method incorporating diffusion approximation and queuing theory for individual bus stops. A concurrent queuing system between public transportation vehicles and passengers can be used to describe the scenario of a bus stop. For most of the queuing systems, the explicit distributions of basic characteristics (e.g., waiting time, queue length, and busy period) are difficult to obtain. Therefore, the diffusion approximation method was introduced to deal with this theoretical gap in this study. In this method, a continuous diffusion process was applied to estimate the discrete queuing process. The proposed model was validated using relevant data from seven bus stops. As a comparison, two common methods— Highway Capacity Manual (HCM) formula and M/M/S queuing model (i.e., Poisson arrivals, exponential distribution for bus service time, and S number of berths)—were used to estimate the capacity of the bus stop. The mean absolute percentage error (MAPE) of the diffusion approximation method is 7.12%, while the MAPEs of the HCM method and M/M/S queuing model are 16.53% and 10.23%, respectively. Therefore, the proposed model is more accurate and reliable than the others. In addition, the influences of traffic intensity, bus arrival rate, coefficient of variation of bus arrival headway, service time, coefficient of variation of service time, and the number of bus berths on the capacity of bus stops are explored by sensitivity analyses.

Optimizing School Bus Stop Placement in Howard County, Maryland

2016 ◽  
pp. 1660-1676 ◽  
Author(s):  
Michael Galdi ◽  
Paporn Thebpanya
Keyword(s):  
Travel Time ◽  
Carbon Footprint ◽  
Current System ◽  
School Bus ◽  
School Officials ◽  
Statistical Estimates ◽  
Bus Stop ◽  
Network Analyst ◽  
Bus Stops ◽  
State And Local

In the current system, school bus stops in Howard County, Maryland are manually placed along the school bus routes based on safety, cost-efficiency, and many other variables. With such liberal placement, bus stops are sometimes placed unnecessarily. This issue is prevalent in many school districts and often results in needlessly close bus stop proximity. In this study, the authors implemented a GIS-based heuristic to assist school officials in optimizing their districts bus stop placement. They also estimated the proportion of county-wide bus stops that could be eliminated by this approach. Following the constraints determined by State and local guidelines, the ArcGIS Network Analyst Extension was used to identify unnecessary bus stops across the study area. The initial output was re-evaluated by school officials in order to determine if those bus stops would be eliminated. The results indicate that approximately 30% of the existing bus stops were marked as “candidates for elimination” by the GIS process. After a review of these candidates, it was determined that at least 15% of the total school bus stops could be eliminated. Statistical estimates lent credence to the benefit of a re-evaluation of these bus stops. The method developed in this study can easily be replicated. Hence, it may inspire other school systems to exercise the same approach. Additionally, the results provide a gateway for future studies in examining more efficient school bus routes with less travel time, as well as investigating how much the carbon footprint of school bus fleets can be reduced.

scholarly journals A Method of Bus Network Optimization Based on Complex Network and Beidou Vehicle Location

2019 ◽  
Vol 11 (4) ◽  
pp. 97 ◽  
Author(s):  
Peixin Dong ◽  
Dongyuan Li ◽  
Jianping Xing ◽  
Haohui Duan ◽  
Yong Wu
Keyword(s):  
Graph Theory ◽  
Complex Network ◽  
Network Optimization ◽  
Original Network ◽  
Network Efficiency ◽  
Bus Stop ◽  
Time Performance ◽  
Network Time ◽  
Vehicle Location ◽  
Bus Stops

Aiming at the problems of poor time performance and accuracy in bus stops network optimization, this paper proposes an algorithm based on complex network and graph theory and Beidou Vehicle Location to measure the importance of bus stops. This method narrows the scope of points and edges to be optimized and is applied to the Jinan bus stop network. In this method, the bus driving efficiency, which can objectively reflect actual road conditions, is taken as the weight of the connecting edges in the network, and the network is optimized through the network efficiency. The experimental results show that, compared with the original network, the optimized network time performance is good and the optimized network bus driving efficiency is improved.

scholarly journals Intelligent Buses in a Loop Service: Emergence of No-Boarding and Holding Strategies

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-18 ◽  
Author(s):  
Vee-Liem Saw ◽  
Luca Vismara ◽  
Lock Yue Chew
Keyword(s):  
Reinforcement Learning ◽  
Phase Difference ◽  
Waiting Time ◽  
Learning Process ◽  
Average Waiting Time ◽  
Bus Stop ◽  
Emergent Behaviour ◽  
Reasonable Amount ◽  
Bus Stops ◽  
Simulation Time

We study how N intelligent buses serving a loop of M bus stops learn a no-boarding strategy and a holding strategy by reinforcement learning. The no-boarding and holding strategies emerge from the actions of stay or leave when a bus is at a bus stop and everyone who wishes to alight has done so. A reward that encourages the buses to strive towards a staggered phase difference amongst them whilst picking up passengers allows the reinforcement learning process to converge to an optimal Q-table within a reasonable amount of simulation time. It is remarkable that this emergent behaviour of intelligent buses turns out to minimise the average waiting time of commuters, in various setups where buses move with the same speed or different speeds, during busy as well as lull periods. Cooperative actions are also observed, e.g., the buses learn to unbunch.

Study of Setting of Bus Bay Stop Based on VISSIM

2014 ◽  
Vol 641-642 ◽  
pp. 906-909
Author(s):  
Jian Jun Wang ◽  
Xin Ting Huang ◽  
Ning Zhao
Keyword(s):  
Traffic Flow ◽  
Delay Time ◽  
Road Traffic ◽  
Microscopic Simulation ◽  
Total Delay ◽  
Urban Road ◽  
Bus Stop ◽  
Road Design ◽  
Bus Station ◽  
Road System

Setting state of bus stop affects the efficiency of the entire road system. Through discussing bus bay stop’s width, length and distance to intersection, a microscopic simulation was conducted in this paper. With a certain bus frequency, the total delay time of vehicles was analyzed under different road traffic in different forms of Da Yanta Bus Station in Xi’an. The results show that setting bus bay stops on the secondary roads which have large traffic flow can significantly reduce delay time, and can provide references for urban road design.

scholarly journals A Methodology to Evaluate Accessibility to Bus Stops as a Contribution to Improve Sustainability in Urban Mobility

2019 ◽  
Vol 11 (3) ◽  
pp. 803 ◽  
Author(s):  
Maria Corazza ◽  
Nicola Favaretto
Keyword(s):  
Multicriteria Analysis ◽  
Urban Mobility ◽  
Mobility Patterns ◽  
Sustainable Mobility ◽  
Urban Network ◽  
Bus Stop ◽  
Final Score ◽  
Advanced Knowledge ◽  
Bus Stops

Walking and transit are the backbone of sustainable mobility. Bus stops not only represent the connection between the two, but are also central in dictating the attractiveness of the latter. Accessibility of bus stops becomes, then, pivotal in increasing both attractiveness and sustainability of public transport. The paper describes a multi-step methodology to evaluate bus stops’ accessibility starting from a cluster of seven indicators describing objective and subjective features influencing passengers’ choice toward a given bus stop. The indicators are weighed by a questionnaire submitted to experts. Finally, a multicriteria analysis is developed to obtain a final score describing univocally the accessibility of each stop. Outcomes are mapped and a case study in Rome is reported as an example, with 231 bus and tram stops assessed accordingly. Results shows the relevance of the urban network and environment in evaluating the accessibility and in promoting more sustainable mobility patterns. Research innovation relies on the possibility to merge data from different fields into a specific GIS map and easily highlight for each bus stop the relationships between built environment, passengers’ comfort, and accessibility, with the concluding goal to provide advanced knowledge for further applications.

INFLUENCE OF BUS BAY AND CURBSIDE BUS STOP IN AN URBAN ROAD

2020 ◽  
Vol 8 (3) ◽  
pp. 14-19
Author(s):  
Saurav Barua
Keyword(s):  
Traffic Congestion ◽  
Simulation Models ◽  
Good Alternative ◽  
Road Segment ◽  
Dhaka City ◽  
Average Speed ◽  
Urban Road ◽  
Traffic Conditions ◽  
Bus Stop ◽  
Bus Stops

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.

TRAFFIC BEHAVIOR IN A TWO-LANE SYSTEM CONSISTING OF A MIXTURE OF BUSES AND CARS

2007 ◽  
Vol 18 (12) ◽  
pp. 1925-1938 ◽  
Author(s):  
YAO-MING YUAN ◽  
RUI JIANG ◽  
QING-SONG WU ◽  
RUILI WANG
Keyword(s):  
Fixed Number ◽  
Optimal Number ◽  
Gradual Transition ◽  
Homogeneous State ◽  
System Behavior ◽  
Fundamental Diagram ◽  
Traffic System ◽  
Bus Stop ◽  
Bus Stops ◽  
Traffic Behavior

In this paper, a two-lane traffic system consisting of a mixture of buses and cars is studied. The buses stop at each bus stop to pick up passengers and are not allowed to change lane. The cars may change lane when hindered by preceding vehicles. Our simulations show that with a fixed number of buses, four states of the traffic system are identified. The spatial-temporal plots of the four traffic states, and the trajectories of buses at different densities are presented. A gradual transition instead of sharp phase transition from bunching state to homogeneous state of the buses is found. Next, we study the system behavior at different number of bus stops, and an optimal number of stops is suggested. Finally, the influence of bus stops on the fundamental diagram is studied.

Transporting Urban Inequality through Public Transit Designs & Systems

2017 ◽  
Vol 16 (4) ◽  
pp. 364-368 ◽  
Author(s):  
Gwendolyn Y. Purifoye
Keyword(s):  
The South ◽  
Large White ◽  
Train Station ◽  
Urban Inequality ◽  
Bus Stop ◽  
Far North ◽  
The North ◽  
Predominantly Minority ◽  
Bus Stops ◽  
North End

Four large, and often overflowing, dumpsters are situated at one of the more than dozen bus stops at the Chicago Transit Authority's (CTA) Red Line 95th Street/Dan Ryan train station. This station is on the city's far south side and the ridership on the buses that board and disembark there and the train is predominantly minority. On a warm or hot day, the smell of bus engines and dumpster contents fill the waiting areas. One 28–year–old Black male passenger (BMP) noted, as he stood at one of the nearly one dozen (no seating available) bus stops at the station, “In the summer it's really horrible because of the smells, flies, and bees.” He also added that as far as he could remember “they've [the bus stop dumpsters] been here my whole life” (June 2012). His experience at the south end of this train line, which also has a majority minority ridership, is starkly different from the waiting experiences on the far north end of the same line, Howard Street, where the ridership is diverse (with a large white ridership). The north end station is surrounded by shops and restaurants, more open waiting spaces, and places to sit to wait for buses that travel through the adjoining bus depot. There are no bus stop benches at the south end station, even though there are over a dozen buses that use that station's depot.

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