Browsing by Author "Chiou, Yu-Chiun"

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A dynamic analysis of motorcycle ownership and usage: A panel data modeling approach
(2012-11-01)
Wen, Chieh-Hua
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Chiou, Yu-Chiun
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Huang, Wan-Ling
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This study aims to develop motorcycle ownership and usage models with consideration of the state dependence and heterogeneity effects based on a large-scale questionnaire panel survey on vehicle owners. To account for the independence among alternatives and heterogeneity among individuals, the modeling structure of motorcycle ownership adopts disaggregate choice models considering the multinomial, nested, and mixed logit formulations. Three types of panel data regression models - ordinary, fixed, and random effects - are developed and compared for motorcycle usage. The estimation results show that motorcycle ownership in the previous year does exercise a significantly positive effect on the number of motorcycles owned by households in the current year, suggesting that the state dependence effect does exist in motorcycle ownership decisions. In addition, the fixed effects model is the preferred specification for modeling motorcycle usage, indicating strong evidence for existence of heterogeneity. Among various management strategies evaluated under different scenarios, increasing gas prices and parking fees will lead to larger reductions in total kilometers traveled. (C) 2011 Elsevier Ltd. All rights reserved.
A joint measurement of efficiency and effectiveness for non-storable commodities: Integrated data envelopment analysis approaches
(2010-03-01)
Chiou, Yu-Chiun
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Lan, Lawrence W.
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Yen, Barbara T. H.
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Efficiency and effectiveness for non-storable commodities represent two distinct dimensions and a joint measurement of both is necessary to fully capture the overall performance. This paper proposes two novel integrated data envelopment analysis (IDEA) approaches, the integrated Charnes, Cooper and Rhodes (ICCR) and integrated Banker, Charnes and Cooper (IBCC) models, to jointly analyze the overall performance of non-storable commodities under constant and variable returns to scale technologies. The core logic of the proposed models is simultaneously determining the virtual multipliers associated with inputs, outputs, and consumption by additive specifications for technical efficiency and service effectiveness terms with equal weights. We show that both ICCR and IBCC models possess the essential properties of rationality, uniqueness, and benchmarking power. A case analysis also demonstrates that the proposed novel IDEA approaches have higher benchmarking power than the conventional separate DEA approaches. More generalized specifications of IDEA models with unequal weights are also elaborated. (C) 2009 Elsevier B.V. All rights reserved.
A Modified Cellular Automaton Model for Accounting for Traffic Behaviors during Signal Change Intervals
(2018-01-01)
Hsu, Chih-Cheng
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Chiou, Yu-Chiun
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Previous cellular automata (CA) models have been developed for simulating driver behaviors in response to traffic signal control. However, driver behaviors during traffic signal change intervals, including cross/stop decision and speed adjustment, have not yet been studied. Based on this, this paper aims to propose a change interval CA model for replicating driver's perception and response to amber light based on stopping probability and speed adjusting functions. The proposed model has been validated by exemplified and field cases. To investigate the applicability of the proposed model, macroscopic and microscopic analyses are conducted. Although the macroscopic fundamental diagram analysis reveals only a small decrease in maximum traffic flow rates with considering driver behaviors in change intervals, in the microscopic analysis, the proposed model can present reasonable vehicular trajectories and deceleration rates during slowdown process.
A Novel Method to Predict Traffic Features Based on Rolling Self-Structured Traffic Patterns
(2014-10-02)
Chiou, Yu-Chiun
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Lan, Lawrence W.
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Tseng, Chun-Ming
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交大名義發表
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運輸與物流管理系註：原交通所+運管所
In this study, a novel method is proposed to predict the traffic features in a long freeway corridor with a number of time steps ahead. The proposed method, on the basis of rolling self-structured traffic patterns, utilizes the growing hierarchical self-organizing map model to partition the unlabeled traffic patterns into an appropriate number of clusters and then develops the genetic programming model for each cluster to predict its corresponding traffic features. For demonstration, the proposed method is tested against a 110-km freeway stretch, on which 48 time steps of 5-min traffic flows are predicted (i.e., a 4-h prediction). The prediction accuracy of the proposed method is compared with other models (ARIMA, SARIMA, and naive models) and the results support the superiority of the proposed method. Further analyses indicate that applications of the proposed method to larger scale freeway networks require sufficient lengths of observation to acquire enough traffic patterns for training and validation in order to achieve higher prediction accuracy.
A refined cellular automaton model to rectify impractical vehicular movement behavior
(2009-09-15)
Lan, Lawrence W.
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Chiou, Yu-Chiun
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Lin, Zih-Shin
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Hsu, Chih-Cheng
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運輸與物流管理系註：原交通所+運管所
When implementing cellular automata (CA) into a traffic simulation, one common defect yet to be rectified is the abrupt deceleration when vehicles encounter stationary obstacles or traffic jams. To be more in line with real world vehicular movement, this paper proposes a piecewise-linear movement to replace the conventional particle-hopping movement adopted in most previous CA models. Upon this adjustment and coupled with refined cell system, a new CA model is developed using the rationale of Forbes' et al. car-following concept. The proposed CA model is validated on a two-lane freeway mainline context. It shows that this model can fix the unrealistic deceleration behaviors, and thus call reflect genuine driver behavior in the real world. The model is also capable of revealing Kerner's three-phase traffic patterns and phase transitions among them. Furthermore, the proposed CA model is applied to simulate a highway work zone wherein traffic efficiency (maximum flow rates) and safety (speed deviations) impacted by various control schemes are tested. (C) 2009 Elsevier B.V. All rights reserved.
A two-stage mining framework to explore key risk conditions on one-vehicle crash severity
(2013-01-01)
Chiou, Yu-Chiun
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Lan, Lawrence W.
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Chen, Wen-Pin
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This paper proposes a two-stage mining framework to explore the key risk conditions that may have contributed to the one-vehicle crash severity in Taiwan's freeways. In the first stage, a genetic mining rule (GMR) model is developed, using a novel stepwise rule-mining algorithm, to identify the potential risk conditions that best elucidate the one-vehicle crash severity. In the second stage, a mixed logit model is estimated, using the antecedent part of the mined-rules as explanatory variables, to test the significance of the risk conditions. A total of 5563 one-vehicle crash cases (226 fatalities, 1593 injuries and 3744 property losses) occurred in Taiwan's freeways over 2003-2007 are analyzed. The GMR model has mined 29 rules for use. By incorporating these 29 mined-rules into a mixed logit model, we further identify one key safe condition and four key risk conditions leading to serious crashes (i.e., fatalities and injuries). Each key risk condition is discussed and compared with its adjacent rules. Based on the findings, some countermeasures to rectify the freeway's serious one-vehicle crashes are proposed. (C) 2012 Elsevier Ltd. All rights reserved.
Advance purchase behaviors of air passengers: A continuous logit model
(2016-09)
Chiou, Yu-Chiun
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Liu, Chia-Hsin
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Modeling the advance purchase behaviors of air passengers is essential when airlines develop revenue management strategies. Therefore, this study empirically investigates advance purchase behaviors based on the air ticket transaction data by using a continuous logit model. The estimation results show that advance purchase behaviors are significantly affected by price, price uncertainty, time of day (morning, afternoon and evening flight), days of week (flight on Friday), months of year (peak or off-peak seasons), and consecutive holiday. Accordingly, different pricing strategies should be used for different flights to maximize revenue. (C) 2016 Elsevier Ltd. All rights reserved.
Advance purchase behaviors of air tickets
(2016-10)
Chiou, Yu-Chiun
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Liu, Chia-Hsin
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
The advance purchase behaviors of air passengers are essential to develop revenue management strategies of airlines, which should be carefully studied. Based on this, this study aims to empirically investigate the advance purchase behaviors for airline tickets based on the airline transaction data of Taipei-Macau (TPEMFM) route in 2011. In order to model the advance purchase behaviors, multinomial logit models are used. To facilitate model development, the advance purchase horizon is divided into five time periods by three segmentation methods, including equal time periods, time periods with equal number of purchases and time periods according to professional judgment. Several factors contributing to advance purchase behaviors are examined, including price, flight schedule (time of day, day of week, and months of year) and fare class preferences. The estimation results show that the model with segmentation of equal time periods performs best in terms of adjusted rho-square and AIC indices. It is also found that air passengers tend to purchase tickets earlier for the flights in the morning and in hot season, suggesting the fare and seat inventory control should be varied for different flights. (C) 2016 Elsevier Ltd. All rights reserved.
An integrated multi-objective model to determine the optimal rescue path and traffic controlled arcs for disaster relief operations under uncertainty environments
(2008-01-01)
Chiou, Yu-Chiun
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Lai, Yu-Hsuan
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This study proposes an integrated multi-objective model to determine the optimal rescue path and traffic controlled arcs for disaster relief operations under uncertainty environments. The model consists of three sub-models: rescue shortest path model, post-disaster traffic assignment model, and traffic controlled arcs selection model to minimize four objectives: travel time of rescue path, total detour travel time, number of unconnected trips of non-victims, and number of police officers required. Since these sub-models are inter-related with each other, they are solved simultaneously. This study employs genetic algorithms incorporated with traffic assignment and K-shortest path methods to determine optimal rescue path and controlled arcs. To cope with uncertain information associated with the damaged network, fuzzy system reliability theory (weakest t-norm method) is used to measure the access reliability of rescue path. To investigate the validity and applicability of the proposed model, studies on an exemplified case and a field case of Chi-Chi earthquake in Taiwan are conducted. The performances of three rescue strategies: without traffic control, selective traffic control (i.e. the proposed model) and absolute traffic control are compared. The results show that the proposed model can maintain the efficiency of rescue activity with minimal impact to ordinary trips and number of police officers required.
AN OPTIMAL SIGNAL CONTROL MODEL CONSIDERING EMISSION CONCENTRATION IN MIXED TRAFFIC CONTEXTS
(2012-01-01)
Chiou, Yu-Chiun
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Lan, Lawrence W.
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Hsieh, Chih-Wei
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Wu, Yi-Jie
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運輸與物流管理系註：原交通所+運管所
An optimal signal control model is proposed that minimizes the traffic emissions with restricted emission concentration in environment-sensitive areas where cars and motorcycles are prevailing. The proposed model comprises four sub-models: mixed traffic cell-transmission model, traffic emission model, Gaussian puff dispersion model, and stepwise genetic fuzzy logic controller model. Mixed traffic behaviors are replicated by the mixed traffic cell-transmission model, traffic emissions are estimated by TEDS 7.0 line source emissions database, emission concentration is estimated by the Gaussian puff model, and optimal cycle length and time split are solved by the stepwise genetic fuzzy logic controller model. Performance of the proposed model is tested at an experimental intersection as oppose to a pre-timed signal control strategy as the baseline. The results show that the proposed model has outperformed in reducing the emission concentration.
Assessing Interchange Effects in Public Transport: A Case Study of South East Queensland, Australia
(2017-01-01)
Yen, Barbara T. H.
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Tseng, Wen-Chun
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Mulley, Corinne
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Chiou, Yu-Chiun
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Burke, Matthew
Interchange or transfers for passengers in large multimodal public transport networks are more or less inevitable. A zone based fare system has the potential to ensure that there is no financial penalty for interchange. In South East Queensland (SEQ), Australia, there is a zone based fare system in place which does not penalize transfers within the same zone but does charge a full fare for an inter-zone transfer in a single journey. This research investigates the interchange effects from an analysis of passengers' travel patterns using the smart card data from the automated fare collection system in place in SEQ. Latent class nested logit models are estimated with social demographic characteristics to measure transfer behaviour and are used to investigate the opportunity for better interchange policies to increase the network effect in the SEQ network. The results identified passengers' heterogeneous preferences towards travel alternatives with markedly different market segments. The empirical results identified passengers categorised into four segments of employees, students, wealthier people and seniors. The findings suggest that public transport network effects are most important to the employee segment with student and senior segments being more likely to choose direct alternatives over alternatives involving interchange. In order to enhance the public transport network effects, two policies to encourage transfers by passengers are investigated using simulations with the policy implications identified. (C) 2017 The Authors. Published by Elsevier B.V.
Cellular automaton simulations for mixed traffic with erratic motorcycles' behaviours
(2010-05-15)
Lan, Lawrence W.
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Chiou, Yu-Chiun
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Lin, Zih-Shin
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Hsu, Chih-Cheng
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運輸與物流管理系註：原交通所+運管所
Modeling mixed traffic composed of motorcycles can be a challenging issue because many erratic motorcyclists may not follow the lane disciplines, particularly when traffic is congested. Based upon the refined cellular automaton (CA) model recently developed by the authors [LW. Lan, Y C Chiou. Z.S. Lin, C.C. Hsu, Physica A 388 (2009) 3917-3930], this paper further proposed a sophisticated CA model to elucidate the erratic motorcycle behaviours in mixed traffic contexts. In addition to the conventional moving forward and lane-change rules, the sophisticated CA model also explicated the lateral drift behaviour for cars moving in the same lane, the lateral drift behaviour for motorcycles breaking into two moving cars. and the transverse crossing behaviour for motorcycles through the gap between two stationary cars in the same lane. Fundamental diagrams and space-time trajectories for vehicles with various car-motorcycle mixed ratios are demonstrated (C) 2010 Elsevier B.V. All rights reserved
Determinants of tourists' length of stay at various tourist attractions based on cellular data
(2020-01-01)
Chiou, Yu-Chiun
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Hsieh, Chih-Wei
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This paper aimed to investigate contributing factors in length of stay at various types of tourist attractions based on cellular data. Accelerated failure time (AFT) models with three error terms distribution were compared: Weibull, log-normal, and log-logistic. The model with frailty was further used to accommodate unobserved heterogeneity. Potential factors related to attractions and trip characteristics are selected. A case study on Yi-Lan County, Taiwan, where has a variety of sightseeing spots attracting visitors, was conducted. The estimation results show that the Log-normal AFT model with frailty performs best. The key contributing factors in length of stay are city of origin, travel distance, entrance time, travel mode, and sequence of visited spots.
DEVELOPMENT OF OPTIMAL VARIABLE SPEED-LIMIT CONTROL MODEL
(2009)
Chiou, Yu-Chiun
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Lan, Lawrence W.
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Lin, Po-Cheng
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Huang, Yen-Fei
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運輸與物流管理系註：原交通所+運管所
Application of variable speed-limit (VSL) control has become promising in managing the incidents in the contexts of intelligent highway systems wherein advanced VSL signs are densely placed along the roadways. This paper aims to develop a genetic-fuzzy-logic-controller (GFLC)-based VSL control model with an objective function to enhance both safety and throughput efficiency at the incident sites. In order to evaluate the performance of learned logic rules and tuned membership function, a revised cell transmission model (CTM) is proposed, which is validated with field traffic data. The results indicate that the proposed VSL control model can effectively curtail the crash likelihood without deteriorating or only slightly decreasing the throughput efficiency under different tested incident cases. It suggests that our proposed GFLC-based VSL control model is promising for practical applications.
Direct and indirect factors affecting emissions of cars and motorcycles in Taiwan
(2010)
Chiou, Yu-Chiun
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Chen, Tai-Chieh
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This article proposes Direct Correlation (DC) models and Integrated Correlation (IC) models for cars and motorcycles emissions, respectively. The DC models regress emissions on vehicle-related variables (i.e. direct factors), while the IC models further account for such variables (i.e. indirect factors) as driver/rider demographics, vehicle mileages travelled and regional types by using structural equation modelling. Results show that vehicle characteristics are the most influencing factors affecting hydrocarbon and carbon monoxide emissions. The old vehicles with small engine, manual transmission, high cumulative mileages travelled, using unleaded gasoline #92 and 2-stroke engine (for motorcycle) can be identified as 'high-emitting' vehicles. The second most influencing construct is the driver/rider demographics. The aged, male, low-educated car drivers and motorcyclists with high income and long driving/riding experience tend to use high-emitting vehicles.
Driver responses to green and red vehicular signal countdown displays: Safety and efficiency aspects
(2010-07-01)
Chiou, Yu-Chiun
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Chang, Chien-Hua
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This study investigates the effects of green signal countdown display (GSCD) and red signal countdown display (RSCD) on driver behaviours, and thus on intersection safety and efficiency. Three driver responses to GSCD, including late-stopping ratio, dilemma zone and decision to cross, and three driver responses to RSCD, including early start ratio, start-up delay, and discharge headway are observed and analyzed. Results show that although GSCD can reduce late-stopping ratio, the dilemma zone is increased by about 28 m and the decision to cross will be more inconsistent among the approaching vehicles, creating a potential risk of rear-end crashes. Additionally, following the provision of a green countdown the number of vehicles ejecting to cross the intersection reduces. On the other hand, comparisons among four observation periods examining the effects of RSCD-before-RSCD, 1.5 months after-RSCD, 3.0 months after-RSCD and 4.5 months after-RSCD, show that although RSCD significantly reduces the early start ratios of the leading vehicles in various waiting areas, the ratios soon return to their before-RSCD levels, suggesting that RSCD does not significantly improve intersection safety over the longer term. However. RSCD effectively reduces start-up delay, saturated headway, and cumulative start-up delay at 4.5 months after-RSCD installation. Thus, RSCD enhances intersection efficiency. RSCD is clearly less controversial and more beneficial than GSCD. (C) 2009 Elsevier Ltd. All rights reserved.
DYNAMIC FUZZY DATA ENVELOPMENT ANALYSIS MODELS: CASE OF BUS TRANSPORT PERFORMANCE ASSESSMENT
(2019-07-01)
Yen, Barbara T. H.
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Chiou, Yu-Chiun
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交大名義發表
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National Chiao Tung University
In the transport field, two characteristics-inter-temporal dependency and fuzziness-need to be considered when assessing transport performance. First, input and output levels are inter-temporal dependent due to heavy capital investment and because quasi-fixed input can influence output levels over multiple periods. Second, conventional Data Envelopment Analysis (DEA) models are, in nature, formulated with quantitative variables. However, qualitative measurements that are characterized with "vagueness" or "fuzziness" are as important as quantitative variables for multi-period transport performance assessment. To rectify these problems, the present study extends previous research by proposing a Dynamic Fuzzy Data Envelopment Analysis (DFDEA) method for assessing the comparative efficiency where inter-temporal dependence exists in operating production processes with some "fuzzy" variables. An case study was conducted to evaluate the performance of city bus transport companies in Taipei, Taiwan. Results showed the superiority of the proposed DFDEA model by comparing the results with static models.
ESTIMATION OF FREEWAY DYNAMIC ORIGIN-DESTINATION MATRICES: A NOVEL APPROACH
(2010)
Chiou, Yu-Chiun
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Lan, Lawrence W.
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Tseng, Chun-Ming
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This paper proposes a novel approach to estimate medium-to-long term freeway dynamic origin-destination (O-D) matrices. The proposed approach includes a two-stage prediction model with an integrated algorithm. The two-stage prediction model uses K-means algorithm to extract clusters of traffic patterns and then employs genetic programming to predict the traffic in each cluster. The integrated algorithm combines cell transmission model with extended Kalman filtering to estimate the arrival distributions and the O-D proportions. To demonstrate the applicability of the proposed approach, a field study of on-ramp traffic patterns on a freeway is examined. The results show that the proposed approach can accurately predict the traffic and satisfactorily estimate the O-D proportions along a freeway.
Factors affecting public transportation usage rate: Geographically weighted regression
(2015-08-01)
Chiou, Yu-Chiun
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Jou, Rong-Chang
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Yang, Cheng-Han
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
As the number of private vehicles grows worldwide, so does air pollution and traffic congestion, which typically constrain economic development. To achieve transportation sustainability and continued economic development, the dependency on private vehicles must be decreased by increasing public transportation usage. However, without knowing the key factors that affect public transportation usage, developing strategies that effectively improve public transportation usage is impossible. Therefore, this study respectively applies global and local regression models to identify the key factors of usage rates for 348 regions (township or districts) in Taiwan. The global regression model, the Tobit regression model (TRM), is used to estimate one set of parameters that are associated with explanatory variables and explain regional differences in usage rates, while the local regression model, geographically weighted regression (GWR), estimates parameters differently depending on spatial correlations among neighbouring regions. By referencing related studies, 32 potential explanatory variables in four categories, social-economic, land use, public transportation, and private transportation, are chosen. Model performance is compared in terms of mean absolute percentage error (MAPE) and spatial autocorrelation coefficient (Moran\' I). Estimation results show that the GWR model has better prediction accuracy and better accommodation of spatial autocorrelation. Seven variables are significantly tested, and most have parameters that differ across regions in Taiwan. Based on these findings, strategies are proposed that improve public transportation usage. (C) 2015 Elsevier Ltd. All rights reserved.
FACTORS AFFECTING USAGE OF HIGH-EMITTING CARS AND MOTORCYCLES IN TAIWAN
(2008)
Chiou, Yu-Chiun
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Lan, Lawrence W.
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Chen, Tai-Chieh
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
To investigate the significant factors affecting the usage of high-emitting cars and motorcycles in Taiwan, this paper conducts a nationwide post-mailed questionnaire survey on the owners of cars and motorcycles; each vehicle type contains 45 thousand samples drawn from Taiwan's Vehicle Registration Database. A total of 3,454 car samples and 2,856 motorcycle samples are returned. We further match these returned samples with Taiwan's Vehicle Inspection and Management Database according to the license plate number. Some 748 car samples and 1,322 motorcycle samples have been successfully matched, which are further used to build up structural equation models for testing the cause-effect hypotheses between the latent constructs (sets of factors) and the usage of high-emitting vehicles. Our results show that the most influencing construct is the vehicle characteristics, which include old, small engine, manual transmission, high mileage, and 2-stroke engine (only for motorcycle) vehicles. The second most influencing construct is the driver/rider demographics, which includes aged, male, low-educated, high-income, and long-driving-experience people. Our results also show that emissions of cars are more serious in small cities than in large and medium cities; however, this relationship is not significantly existent in the motorcycle model.