Designing Limited-Stop Transit Service with Fixed Fleet Size in Peak Hours by Exploiting Transit Data

2017 ◽  
Vol 2647 (1) ◽  
pp. 134-141
Author(s):  
Xiaoling Luo ◽  
Yangsheng Jiang ◽  
Zhihong Yao ◽  
Youhua Tang ◽  
Yuan Liu
Keyword(s):  
Travel Time ◽  
Heuristic Algorithm ◽  
Travel Demand ◽  
Fleet Size ◽  
Transit Service ◽  
User Costs ◽  
Passenger Flow ◽  
Line Structure ◽  
Total Travel Time ◽  
Travel Behaviors

Efficiently designed limited-stop transit service is an attractive way to respond to high commuter travel demand in which trips concentrate on a few origin–destination pairs during peak hours. Such service is redesigned in many metropolises in China. Some research has dealt with this situation; bus fleet size was assumed to be unlimited, and the research was concerned with the average daily passenger flow rather than the specific average peak hour travel demand. In contrast to previous work, this paper presents an approach to design limited-stop transit service with the existing available fleet size from current normal service and focuses only on peak hour travel demand extracted through exploitation of transit data. First, a model for limited-stop service was proposed to minimize user costs through existing fixed fleet size. A heuristic algorithm was developed to search the transit line structure for limited-stop service instead of selecting lines from the predefined set. Next, a case in Chengdu, China, was tested. The results indicate that up to 9.32% of total travel time can be saved with the fixed fleet size when limited-stop transit service is applied. Finally, different proportions of commuter flow and different travel behaviors are discussed to illustrate the performance of limited-stop service for different scenarios.

scholarly journals Evaluation of Evacuation Strategies According to the Travel Demand: The Case of Nuclear Research Reactor HANARO’s EPZ

2020 ◽  
Vol 12 (15) ◽  
pp. 6128
Author(s):  
Bongseok Kim ◽  
Hyeonmyeong Jeon ◽  
Bongsoo Son
Keyword(s):  
Travel Time ◽  
Research Reactor ◽  
Travel Demand ◽  
Protective Action ◽  
Nuclear Research ◽  
Emergency Plan ◽  
The Public ◽  
Nuclear Research Reactor ◽  
Total Travel Time ◽  
The Republic

In the event of a nuclear accident, evacuation is the most effective protective action for the public. During the evacuation, total travel time is a key measure to protect the public because it is directly related to the public’s radiation exposure. Thus, strategies that reduce the total travel time are needed for a safer nuclear emergency plan. Many studies on evacuation strategies so far have suggested the methodology of effective routing decisions or delay management. Despite the application of those strategies during evacuation, the effectiveness of those strategies, in reality, varies depending on the level of travel demand. In this study, evacuation strategies based on travel demand levels were evaluated based on the case of the Emergency Planning Zone (EPZ) of HANARO, the nuclear research reactor in the Republic of Korea. As a result, it was confirmed that effective evacuation strategies could be applied differently according to travel demand levels.

scholarly journals Shared Autonomous Taxi System and Utilization of Collected Travel-Time Information

2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
Zhiguang Liu ◽  
Tomio Miwa ◽  
Weiliang Zeng ◽  
Michael G. H. Bell ◽  
Takayuki Morikawa
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Autonomous Vehicles ◽  
Traffic Information ◽  
Path Finding ◽  
Fleet Size ◽  
Real Time Traffic ◽  
Total Travel Time ◽  
The Mean ◽  
Time Information

Shared autonomous taxi systems (SATS) are being regarded as a promising means of improving travel flexibility. Each shared autonomous taxi (SAT) requires very precise traffic information to independently and accurately select its route. In this study, taxis were replaced with ride-sharing autonomous vehicles, and the potential benefits of utilizing collected travel-time information for path finding in the new taxi system examined. Specifically, four categories of available SATs for every taxi request were considered: currently empty, expected-empty, currently sharable, and expected-sharable. Two simulation scenarios—one based on historical traffic information and the other based on real-time traffic information—were developed to examine the performance of information use in a SATS. Interestingly, in the historical traffic information-based scenario, the mean travel time for taxi requests and private vehicle users decreased significantly in the first several simulation days and then remained stable as the number of simulation days increased. Conversely, in the real-time information-based scenario, the mean travel time was constant. As the SAT fleet size increased, the total travel time for taxi requests significantly decreased, and convergence occurred earlier in the historical information-based scenario. The results demonstrate that historical traffic information is better than real-time traffic information for path finding in SATS.

Research on Customer Requirements for Transit Service Design and Delivery

1997 ◽  
Vol 1604 (1) ◽  
pp. 121-127 ◽  
Author(s):  
Jane Glascock
Keyword(s):  
Service Delivery ◽  
Travel Time ◽  
Service Design ◽  
Customer Requirements ◽  
Staff Perceptions ◽  
Transit Service ◽  
Performance Requirements ◽  
Total Travel Time ◽  
Transit Agencies ◽  
Potential Customers

In the past, transit had a monopoly over service to large segments of society: one-car families or those who could not afford to drive. Now transit competes with the automobile for most consumers’ travel. To increase trip making and attract new customers in a competitive market, transit agencies must refocus from an internally driven orientation aligned with providing public service to an externally driven orientation aligned with the mission of delivering products and service that meet consumer expectations and requirements. Descriptive results of research to identify customer requirements for design and delivery of high-quality transit service are reported. Nearly 500 customers and potential customers of King County Metro Transit in Seattle, Washington, completed questionnaires designed to identify important elements and their performance requirements for each. The questionnaire was developed with intensive customer input to ensure that wording reflected customer and not staff perceptions. Requirements for service design included the following: 15-min headways for work and personal travel; no transferring to work; and total travel time to work no more than 50 percent longer than by car. Customer requirements for service delivery among elements that customers considered important included the following: the bus never leaves the stop early; seats are clean and dry; arrival time to work is no more than 5 min late; and windows are in good repair. Nonriders who were potential customers rated service delivery elements of transferring comparablity with automobile travel time as more important than did riders. Riders were more likely than nonriders to require 15-min headways for work travel.

Incorporating Travel Time Reliability in Equitable Congestion Pricing Schemes for Heterogeneous Users and Bimodal Networks

2021 ◽  
pp. 036119812110197
Author(s):  
Fatemeh Fakhrmoosavi ◽  
Ali Zockaie ◽  
Khaled Abdelghany
Keyword(s):  
Travel Time ◽  
Optimization Algorithm ◽  
Travel Demand ◽  
Demand Management ◽  
Congestion Pricing ◽  
User Equilibrium ◽  
Travel Time Reliability ◽  
Travel Demand Management ◽  
Equity Issues ◽  
Total Travel Time

Congestion pricing is proposed as an effective travel demand management strategy to circumvent the problem of congestion and generate revenue to finance developmental projects. There are several studies focusing on optimal pricing strategies to minimize the congestion level or maximize the revenue of the system. However, with regard to equity issues, benefiting only users with higher value of time is claimed to be the main factor that prevents implementation of such policies in practice. While many studies aimed to tackle the equity issues by certain welfare analyses, most of these studies fail to fully consider realistic features of users’ behavior and the uncertainty in link travel times. Given the variability of travel time in real-world networks and the impacts of pricing policies on path travel time distributions, it is important to consider the users’ reliability valuations, in addition to their travel time valuations. Thus, the goal in this study is to find an equitable pricing scheme that minimizes the total travel time of auto users in a general bimodal network considering heterogeneous users with different values of time and reliability. A particle swarm optimization algorithm is proposed to find self-funded and Pareto-improving optimal toll values. A reliability-based user equilibrium algorithm is embedded into this optimization algorithm to assign travelers to the equilibrated paths for different user classes given toll values. The proposed approach is successfully applied to a modified Sioux Falls network to explore impacts of subsidization, congestion level, and considering travel time reliability on the pricing strategy and its effectiveness.

scholarly journals Estimation of Travel Demand for Bangkok–Chiang Mai Hyperloop Using Traveler Surveys

2021 ◽  
Vol 13 (24) ◽  
pp. 14037
Author(s):  
Paras Agrawal ◽  
Surachet Pravinvongvuth
Keyword(s):  
Travel Time ◽  
High Speed ◽  
Travel Demand ◽  
Stated Preference ◽  
Travel Cost ◽  
Monthly Income ◽  
Chiang Mai ◽  
Modal Shift ◽  
Long Distance ◽  
Total Travel Time

Hyperloop, projected as fast and efficient, and envisaged as the future of high-speed transportation, does not have much published information about its demand estimation. This paper aims to estimate the willingness of air and car passengers to shift to hyperloop. A nested logit model was used to analyze stated preference data gathered from the air and car travelers along the Bangkok–Chiang Mai sector in Thailand. The variables contributing the most to the modal shift towards hyperloop are total travel cost, total travel time, monthly income, gender, education level, bearer of trip expenses, and number of trips in the last 6 months and duration of stay at the destination. The highest value of elasticity for hyperloop is obtained for the total travel cost followed by total travel time and monthly income. It is concluded that hyperloop will be the predominant mode of transportation between the Bangkok–Chiang Mai sectors with a modal share of almost 50% by the year 2025. Survey results also revealed that the preferences of the passengers in order of priorities for long distance travel are comfort, low travel cost, less travel time, safety, high frequency of travel mode and low CO2 emission. The main contribution of this paper is to provide an insight on factors that may contribute towards a possible shift in mode from car and air to hyperloop. The study will be beneficial to policy makers in developing a strategy for a more efficient mass transportation system using new and emerging technologies.

scholarly journals Coupling Research on Land Use and Travel Behaviors Along the Tram Based on Accessibility Measurement—Taking Nanjing Chilin Tram Line 1 as an Example

2019 ◽  
Vol 11 (7) ◽  
pp. 2034
Author(s):  
Yang Zhou ◽  
Caiyun Qian ◽  
Han Xiao ◽  
Jiachen Xin ◽  
Zixiong Wei ◽  
...  
Keyword(s):  
Land Use ◽  
Travel Demand ◽  
Present Situation ◽  
Rail Transit ◽  
Low Carbon ◽  
Passenger Flow ◽  
The Social ◽  
Volume Level ◽  
Travel Behaviors ◽  
The Relationship

The expansion of urban space makes citizens more dependent on cars, resulting in various urban environmental and traffic problems. Advocating low-carbon travel and building a sustainable low-carbon city are the major trends of urban development. Many scholars have pointed out that the urban spatial environment will lead residents to change their travel modes, but the residents’ travel patterns will also have an impact on the urban spatial layout. Based on the interaction between the two, most of the studies have been evaluated and studied from the level of rail transit and normal bus transit. The traffic volume level of trams lies between the rail transit and the normal public transit. However, the research and discussion on the relationship between the surrounding land use and residents’ travel behaviors are not yet perfect domestically. This paper takes Nanjing Chilin Tram Line 1 in China as the research object, combines the research of the the social attributes of the passengers who live along the tram line and the psychological accessing threshold of different travel purposes, provides analysis and evaluations of the coupling degree between the present situation of land use around its various stations and the residents’ actual travel demand with the measure of accessibility. The traffic volume level of trams lies between the rail transit and the normal public transit. However, the research and discussion on the relationship between the surrounding land use and residents’ travel behaviors are not yet perfect domestically. Taking Nanjing Chilin Tram Line 1 in China as the research object, this paper combines the research of the the social attributes of the passengers who live along the tram line and the psychological accessing threshold of different travel purposes. Furthermore, based on the measure of accessibility, it provides the analysis and evaluations of the coupling degree between the present situation of land use around its various stations and the residents’ actual travel demand. The research method of this paper is divided into three parts. Firstly, based on the questionnaire and OD survey, the coupling degree between the type of the station along the tram line and the distribution of passenger flow and the purpose of passenger travel is analyzed. Secondly, the KLP model is used to calculate and determine the effective influence range of the tram through the critical accessing distance for pedestrians psychologically. Based on different psychological thresholds for different purposes, the land use index within the influence range of the station is evaluated and analyzed, and the controlled circle of land use around each type of station is defined. Finally, the coupling degree between the actual land use status in each circle and residents’ psychological threshold with different purposes is analyzed, and the optimization strategy is proposed from the coupling degree between the overall station type & passenger flow along the line and the land use layout around the station & the residents’ psychological threshold.

Estimation of Bus Dwell Times with Automatic Passenger Counter Information

2003 ◽  
Vol 1841 (1) ◽  
pp. 120-127 ◽  
Author(s):  
Rajat Rajbhandari ◽  
Steven I. Chien ◽  
Janice R. Daniel
Keyword(s):  
Travel Time ◽  
Dwell Time ◽  
Time Of Day ◽  
Descriptive Statistics ◽  
Fleet Size ◽  
Transit Service ◽  
Service Type ◽  
Vehicle Travel Time ◽  
The Impact

The average passenger boarding and alighting times and bus dwell times at stops are important information for estimating transit service capacities. Bus dwell time directly affects vehicle travel time, and thus the fleet size required to provide service based on scheduled headway is affected. Research focused on estimating bus dwell time and the impact of boarding and alighting passengers on dwell time. In addition, the effect of standees, time of day, and service type on bus dwell time was investigated. The data were recently collected from an archived database, within which automatic passenger counter information was recorded. The dwell times and passenger counts were recorded daily during 2001 and the first 6 months of 2002. The bus dwell time and average passenger boarding and alighting time at stops are explained using descriptive statistics.

Estimating Express Train Preference of Urban Railway Passengers Based on Extreme Gradient Boosting (XGBoost) using Smart Card Data

2021 ◽  
pp. 036119812110133
Author(s):  
Eun Hak Lee ◽  
Kyoungtae Kim ◽  
Seung-Young Kho ◽  
Dong-Kyu Kim ◽  
Shin-Hyung Cho
Keyword(s):  
Travel Time ◽  
Smart Card ◽  
Public Transportation ◽  
Gradient Boosting ◽  
Log Data ◽  
Smart Card Data ◽  
Extreme Gradient Boosting ◽  
Express Train ◽  
Total Travel Time ◽  
The Individual

As the share of public transport increases, the express strategy of the urban railway is regarded as one of the solutions that allow the public transportation system to operate efficiently. It is crucial to express the urban railway’s express strategy to balance a passenger load between the two types of trains, that is, local and express trains. This research aims to estimate passengers’ preference between local and express trains based on a machine learning technique. Extreme gradient boosting (XGBoost) is trained to model express train preference using smart card and train log data. The passengers are categorized into four types according to their preference for the local and express trains. The smart card data and train log data of Metro Line 9 in Seoul are combined to generate the individual trip chain alternatives for each passenger. With the dataset, the train preference is estimated by XGBoost, and Shapley additive explanations (SHAP) is used to interpret and analyze the importance of individual features. The overall F1 score of the model is estimated to be 0.982. The results of feature analysis show that the total travel time of the local train feature is found to substantially affect the probability of express train preference with a 1.871 SHAP value. As a result, the probability of the express train preference increases with longer total travel time, shorter in-vehicle time, shorter waiting time, and few transfers on the passenger’s route. The model shows notable performance in accuracy and provided an understanding of the estimation results.

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