Journal articles on the topic 'Trip mode'
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Yang, S., Wei Deng, D. X. Wu, and W. Gong. "Analysis of the Interrelationship between Trip Chain Pattern and Trip Mode Choice Based on Multinomial Logistic Model." Applied Mechanics and Materials 743 (March 2015): 407–12. http://dx.doi.org/10.4028/www.scientific.net/amm.743.407.
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This paper explores the interrelationship between trip chain pattern and trip mode choice based on multinomial logistic model, using 2010 Nanjing resident trip survey data. Unlike previous literatures, trip mode choice is divided into single-mode and multi-modes in this study. Estimation coefficients verify trip chain pattern and trip mode selection are a pair of choices that influence each other. Trip mode is great positively associated with trip chain pattern of HW+WH, HO+OH, HW+OH, however, in return trip chain pattern is the most significant negative factor that affects trip mode choice, which means that no trip chain pattern would provoke travelers to select multi-modes. Despite the results seem to reach a contradiction between trip chain pattern and trip mode choice, still two facets of views try to explain the phenomenon, in addition, discussion on the interrelationship between complex trip chain pattern and multi-modes which might put forward more challenges to urban planning is also proposed as well in the paper.
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Shalaby, Amer S., and Gerald N. Steuart. "Trip End Mode Split." Transportation Research Record: Journal of the Transportation Research Board 1556, no. 1 (January 1996): 58–66. http://dx.doi.org/10.1177/0361198196155600108.
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Trip interchange models and their underlying assumption that relative level of service (LOS) of travel modes is a major determinant of mode choice for the work trip are examined. The investigation is done through a comparative analysis of trip end and trip interchange mode split for work trips in the greater Toronto area (GTA). Two model sets are developed; one includes trip end models and the other includes trip interchange models. The models are developed using a relatively new statistical procedure for nonparametric analysis of data referred to as classification and regression trees. The results show that the explanatory power enjoyed by trip end models is virtually the same as that of trip interchange models. Relative LOS is found to have an insignificant role in explaining heterogeneity in mode split, particularly outside the central business district of the study area. It is recommended that predictions made by trip interchange models of mode shift following changes in LOS attributes be approached with caution. Trip end models, which attribute less significance to relative LOS than trip interchange models and are thus conservative with respect to mode shift, could be considered in planning studies, particularly in areas of low transit use. The interaction between the decisions of residential and employment locations, car ownership, and mode choice is emphasized, and the need for more research to investigate and model such interactions is stressed.
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Liao, Yong, and Tao Wu. "The Research on Share Rate of Trip Mode Choice Based on Bayesian Theory." Applied Mechanics and Materials 373-375 (August 2013): 2262–65. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.2262.
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Based on Bayes analysis, a new model of trip mode choice is presented. Trip mode choice is divided into three phases: calculating prior distribution, obtaining conditional distribution by sampling and calculating share rate of trip modes. Supply characteristics of trip modes are taken as prior information. Unity value takes the place of unity function in MNL, and then prior distribution is achieved. Condition distribution is gained from sampling information. Bayes analysis is introduced into calculating posterior distribution. Share rates of trip modes, is calculated by total probability formula. Compared with other choice models, Model proposed in this paper improves the forecast accuracy of share rate without the need of parameter calibration like Logit model.
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Busari, Ayobami A. "Non-Motorized Trip Pattern in Sub-Saharan Africa: Assessment of Walk Trip." Open Transportation Journal 13, no. 1 (December 13, 2019): 194–202. http://dx.doi.org/10.2174/1874447801913010194.
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Background: Walking as a parent mode of transportation has received little or no attention regarding planning, design, and development, thereby leading to chaotic outcomes when it comes to controlling and future estimation in most sub-Saharan Africa countries. This necessitated the research on the pertinent factors and variables that affect walking as a means of transportation in the study area, a semi-urban industrial cluster in South-Western Nigeria. Methods: One Thousand five hundred (1500) information cards were distributed for seven months. This was done to accumulate information on trip patterns, modal split, walk trip volume and so on. The data obtained was analysed using SPSS version 23. Results: The result revealed that 53.2% of the respondent engages in a walk trip every day either to access mode, access sub-mode or for recreation purposes. The commercial zone showed the highest percentage of walk trips of 40%. The mathematical model showed that age and walk trips are inversely proportional. Based on the result of the analysis, cost, safety and exercise are the primary reason why people engage in a walking trip. The R2 value of 0.83 established the robustness of the model. Conclusion: The created model can be utilized for anticipating the future modular part by inputting anticipated future estimation of exploratory variables, which will also aid the planning of a better transport system for the locality. The lack of essential infrastructure poses a big problem for the utilisation of this mode of transportation.
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Goulias, Konstadinos, Werner Brog, and Erhard Erl. "Perceptions in Mode Choice Using Situational Approach “Trip-by-Trip Multivariate Analysis for Public Transportation”." Transportation Research Record: Journal of the Transportation Research Board 1645, no. 1 (January 1998): 82–93. http://dx.doi.org/10.3141/1645-11.
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Objective and subjective constraints that trip makers face are analyzed by using a trip-by-trip multivariate unbalanced panel analysis. These constraints emerge from trip makers’ stated reasons and dispositions for why a given mode was not used for their trips. A finite set of behavioral dimensions (situations), which are general, system, and service constraints, lack of information about the modes, negative disposition toward a mode, and time, comfort, and cost considerations were derived from open-ended questions on the respondents’ stated reasons. The presence of these situations, for each trip a person made in a day, is explained in terms of social and economic characteristics of the trip maker, place of residence, household resources, and trip characteristics. As expected, stated reasons for not using a specific mode vary with respect to the mode chosen, and they change within a day in a nonlinear manner depending on a person’s schedule. Illustrated is another facet of unobserved heterogeneity represented in the radically different individual perceptions, which have been recognized as important components in dynamic behavior simulation studies.
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Qi, Cong, Zhenjun Zhu, Xiucheng Guo, Ruiying Lu, and Junlan Chen. "Examining Interrelationships between Tourist Travel Mode and Trip Chain Choices Using the Nested Logit Model." Sustainability 12, no. 18 (September 12, 2020): 7535. http://dx.doi.org/10.3390/su12187535.
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As tourism grows, determining methods to ease traffic problems as a result of domestic tourism holidays has become a central issue in traffic planning and management. Trip chain and travel mode choices as well as their interplays are crucial in analysing and understanding the travel behaviour of tourists, which can help to address these problems. Therefore, this study explored the relationship between destination transportation modes and trip chain choices using nested logit models wherein two nest structures were used to analyse the decision processes of travellers. Empirical analysis confirmed the effectiveness of the rational model using survey data collected from 350 respondents in Nanjing, China in 2020. The results showed that tourists preferred deciding on the trip chain prior to the travel mode, and higher time and costs were acceptable when tourists selected a complex trip chain with tour activities. Moreover, non-local tourists owning a driver’s licence, travelling with companions, and staying for longer periods were more likely to use public transport with trip chains comprising tour activities; however, the relationship for trip chains with non-tour activities was the reverse. These findings are valuable for designing effective transport management strategies to ease traffic during holiday periods.
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Xiang, Yun, Chengcheng Xu, Weijie Yu, Shuyi Wang, Xuedong Hua, and Wei Wang. "Investigating Dominant Trip Distance for Intercity Passenger Transport Mode Using Large-Scale Location-Based Service Data." Sustainability 11, no. 19 (September 26, 2019): 5325. http://dx.doi.org/10.3390/su11195325.
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Intercity transport systems have been plagued by low efficiency and overutilization for a long time, due to unhealthy competition among multi-transport modes. Hence, this study aims to estimate the dominant trip distance of intercity passenger transport modes to optimize the allocation of intercity passenger transport resources and improve the efficiency of intercity transport systems. Dominant trip distance was classified into two types: Absolute dominant trip distance and relative dominant trip distance; and their respective models were developed using passenger transport mode share functions and fitting curves. Particularly, the big data of intercity passenger transport mode share rate of more than 360 cities in China was obtained using a network crawler and each passenger transport mode share function and their curves were proposed. Furthermore, the dominant trip distances estimation models of intercity passenger transport were developed and solved. The results show that there are significant differences in dominant trip distance between the transport modes. For example, the absolute and relative dominant trip distances of highway are 8–119 km and 8–463 km, respectively, while those of airway are 1594–3000 km and 2477–3000 km, respectively.
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Zhou, Zhuping, Wei Wang, and Qizhou Hu. "An Application of Hierarchical Structure Model for Trip Mode Choice Forecasting in China." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/925963.
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Trip mode split is the result of interrelated and mutually independent factors, such as city scale, urban form, economic level, trip distance, and travel time. In order to analyze the formation of traffic structure, it is necessary to make a comprehensive study on the mechanism of these factors and obtain the basic causal relationship of them. Based on this, by using the hierarchical structure model in system engineering, this paper firstly clarifies the logical relationship of different factors. Then, the existing trip survey data of several cities is used to establish the mathematical relationship of various factors of the structure model. Finally, the mode choice forecasting method is proposed based on the structure model of influencing factors. The case study result of six cities shows small bias, indicating that the proposed method is of great practical value. Policy makers can use the results to discover the trip structure feature and grasp the direction of transportation development policy.
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Westrom, Ryan, Stephanie Dock, Jamie Henson, Mackenzie Watten, Anjuli Bakhru, Matthew Ridgway, Jennifer Ziebarth, et al. "Multimodal Trip Generation Model to Assess Travel Impacts of Urban Developments in the District of Columbia." Transportation Research Record: Journal of the Transportation Research Board 2668, no. 1 (January 2017): 29–37. http://dx.doi.org/10.3141/2668-04.
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The research effort described in this paper aims to develop a state-of-the-practice methodology for estimating urban trip generation from mixed-use developments. The District Department of Transportation’s initiative focused on ( a) developing and testing a data collection methodology, ( b) collecting local data to complement the ITE’s national data in trip rate estimation, and ( c) developing a model–tool that incorporates contextual factors identified as affecting overall trip rate as well as trip rate by mode. The final model accurately predicts total person trips and mode choice. The full set of models achieves better statistical performance in relation to average model error and goodness of fit than either ITE rates alone or other existing research. The model includes sensitivity to local environment and on-site components. The model advances site-level trip generation research in two major ways: first, it calculates total person trips independent of mode choice; second, it calculates mode choice with sensitivity to the amount of parking provided on site—a major finding in the connection between parking provision and travel behavior at a local-site level. The methodology allows agencies to improve their assessment of expected trips from proposed buildings and therefore the level of impact a planned building may have on the transportation system.
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Qin, Shi Huan, Mo Song, Jian Ming Ying, and Li Neng Xu. "Bayesian Dynamic Model of Generalized Trip Cost Based on Traveler Perception." Advanced Materials Research 1030-1032 (September 2014): 2223–26. http://dx.doi.org/10.4028/www.scientific.net/amr.1030-1032.2223.
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Research on trip choice has been a hotspot in the area of traffic science. Daily trip choice behavior can be regard as a reiterative process and each choice represent a process during which travelers’ experience accumulated. The consequence of each choice will affect the next trip choice and the most direct one is the influence on the change of generalized trip cost traveler perceived. Therefore, the generalized trip cost traveler perceived is defined as the gist of the choice on trip mode and trip route and Bayesian dynamic model of generalized trip cost based on traveler perception is established in this paper.
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Horowitz, Joel L. "Semiparametric estimation of a work-trip mode choice model." Journal of Econometrics 58, no. 1-2 (July 1993): 49–70. http://dx.doi.org/10.1016/0304-4076(93)90113-j.
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Chen, Xiaoxu, Xiangdong Xu, and Chao Yang. "Trip mode inference from mobile phone signaling data using Logarithm Gaussian Mixture Model." Journal of Transport and Land Use 13, no. 1 (November 12, 2020): 429–45. http://dx.doi.org/10.5198/jtlu.2020.1554.
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Trip mode inference plays an important role in transportation planning and management. Most studies in the field have focused on the methods based on GPS data collected from mobile devices. While these methods can achieve relatively high accuracy, they also have drawbacks in data quantity, coverage, and computational complexity. This paper develops a trip mode inference method based on mobile phone signaling data. The method mainly consists of three parts: activity-nodes recognition, travel-time computation, and clustering using the Logarithm Gaussian Mixed Model. Moreover, we compare two other methods (i.e., Gaussian Mixed Model and K-Means) with the Logarithm Gaussian Mixed Model. We conduct experiments using real mobile phone signaling data in Shanghai and the results show that the proposed method can obtain acceptable accuracy overall. This study provides an important opportunity to infer trip mode from the aspect of probability using mobile phone signaling data.
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Day, Nicholas, Khandker Nurul Habib, and Eric J. Miller. "Analysis of work trip timing and mode choice in the Greater Toronto Area." Canadian Journal of Civil Engineering 37, no. 5 (May 2010): 695–705. http://dx.doi.org/10.1139/l10-008.
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This paper focuses on examining and analyzing observed trends in work trip making in the Greater Toronto Area (GTA). Commuter trip timing and mode choice behaviour are investigated to explain the main reasons behind peak spreading observed in cordon count data from 1975 through 2004 and to better understand the relationship between modal and temporal decisions. From analysis it becomes clear that significant differences exist in the trip timing trends of individuals choosing different modes. Multinomial logit mode choice models are developed for separate occupation groups, revealing significant differences in the mode choice preferences between occupation groups. Such differences are related to the differences in occupation-specific factors, including labour rates, work hour rules, free parking availability, and the spatial distribution of work locations. Overall, the investigations of this paper indicate that a joint analysis and modelling of trip timing and mode choice has considerable merit in travel demand models.
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Yang, Fei, Zhenxing Yao, and Peter J. Jin. "GPS and Acceleration Data in Multimode Trip Data Recognition Based on Wavelet Transform Modulus Maximum Algorithm." Transportation Research Record: Journal of the Transportation Research Board 2526, no. 1 (January 2015): 90–98. http://dx.doi.org/10.3141/2526-10.
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The GPS-based travel survey is an emerging data collection method in transportation planning. The survey's application in trip mode detection has been explored in many studies. Most research on trip mode detection methods based on GPS data has been developed and tested with data collected from European and American countries. The methods cannot be easily adapted to Asian countries such as China, India, and Japan, which have much higher population densities, more complex road networks, and highly mixed travel modes during daily commuting. Furthermore, for trip segment division in multimode travel, existing algorithms use travel time and distance thresholds that are highly dependent on local travel behavior and lack universality across traffic environments. This paper proposes an innovative framework for detecting trip modes in complex urban environments. First, a smartphone application, GPSurvey, was developed to collect passive GPS trace data. Then a wavelet transform modulus maximum algorithm was developed for trip segment division. The algorithm has outstanding capabilities for identifying singularity features of a signal; this factor suits the task of detecting mode changes in a complex traffic environment. A neural network module was developed for mode detection on the basis of cell phone GPS location and acceleration data. The results indicate that the proposed method has promising performance. The average absolute detection error of mode transfer time was within 1 min, and the accuracy for detecting all modes was greater than 85%.
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Wang, Jian, Zhu Bai, and Xiaowei Hu. "The Effect of the Integrated Service Mode and Travel Time Uncertainty on Taxis Network Equilibrium." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/641418.
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This paper aims to discuss the trip mode choice problem by using cumulative prospect theory (CPT) rather than utility maximization from the network uncertainty perspective and evaluates the effect of the integrated service mode on taxi network equilibrium. The integrated service mode means taxis either are actively moving through traffic zones to pick up customers (cruising mode) or are queued at the center of a zone waiting for customers (dispatch mode). Based on this, CPT models are adopted to analyze the choice of customers’ trip mode. The travel time uncertainty of the network and the applicability of CPT are considered first, and the Nested Logit model was used to complete the trip mode split problem. Further, several relevant relationships including supply-demand equilibrium, network conditions, taxi behavior, and customer behavior perspectives were analyzed with respect to the integrated mode. Moreover, a network equilibrium model was established and its algorithm was designed. Finally, this paper presented a numerical example and discussed the taxi network equilibrium’s characteristic after introducing the integrated service mode.
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Fatima, Kaniz, Sara Moridpour, and Tayebeh Saghapour. "Spatial and Temporal Distribution of Elderly Public Transport Mode Preference." Sustainability 13, no. 9 (April 23, 2021): 4752. http://dx.doi.org/10.3390/su13094752.
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The elderly population is increasing rapidly. Understanding travel behaviour for this group of commuters (in terms of the trip purpose and travel time) is necessary for future transport planning. Many researchers are working on travel’s spatial and temporal analysis to provide operational decision making and transport network planning. This research study’s primary purpose is to identify the influence of trip duration (using public transport), time of the day (usage of public transport), and public transport (PT) accessibility over public transport mode preference by elderly (over 65 years of age) commuters. The methodology of this study is divided into two parts as spatial analysis and temporal analysis. The research identified the dependency of trip duration, time of the day, geographical areas, and PT access over transport mode preference of elderly. The temporal study shows that transport mode preference can vary depending on trip purposes. However, for specific trip durations and times of the day, the elderly sometimes choose PT as a mobility mode. For instance, on shopping trips between 10:00 and 11:00 a.m., the elderly have a greater possibility of choosing public transport over private vehicles. Moreover, the results show the public transport mode preference based on different times of the day and trip purposes. Urban and transport planner can use the results to modify/plan public transport schedule, which can be easily accessible by the elderly population.
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Bard, Erin A. "Transit and Carpool Commuting and Household Vehicle Trip Making: Panel Data Analysis." Transportation Research Record: Journal of the Transportation Research Board 1598, no. 1 (January 1997): 25–31. http://dx.doi.org/10.3141/1598-04.
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Most of the evaluation of commute trip reduction programs centers on the effect on reducing driveway trips at the work site. Little has been done to explore the effects of such programs on overall trip making. This work is meant to help understand this relationship by determining the association between transit and carpool commuting and overall household vehicle trip making. Household activity models have indicated that an individual's travel decisions influence (and are influenced by) the decisions of other household members. It is thus postulated that one household member's choice of transit or carpool for the morning trip to work will affect the mode choices of the other household members. In addition, the choice of mode to work will affect the individual's mode choices for trips other than the morning trip to work. The analysis uses the first four waves of the Puget Sound Transportation Panel survey to construct linear econometric longitudinal trip generation models (random effects models). The results of the modeling indicate that one household member's mode choice to work does affect overall household vehicle travel. Compared with driving alone to work, if one household member chooses transit to work, overall household vehicle trips are reduced (on average). Carpooling by one household member is associated with little change in overall household travel, with average daily household vehicle trips ranging between one trip fewer and one trip greater than households where each driver in the household drives to work in a separate, single-occupant vehicle. The analysis strengthens the associations to imply causal links. The model results suggest that an improved understanding of interactions among household members is necessary to define strategies in support of commute trip reduction policies to better meet air quality and congestion-management goals.
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Bao, Danwen, and Songyi Hua. "Flight Time and Frequency-Optimization Model for Multiairport System Operation." Mathematical Problems in Engineering 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/7371461.
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This study’s goal is to reduce the number of flights and alleviate congestion in hub airports. It proposes a flight time and frequency-optimization method for multiairport systems. A flight time and frequency-optimization model for multiairport system operation is created to minimize loss of passenger trip time. A k-means clustering algorithm is designed to solve the model and calculate indexes such as flight time and frequency, passenger trip-time loss, and distribution of airplane models and quantity. The calculation results of an example in China are as follows. Under multiairport system operation mode, passenger demands are divided into 7 categories; 11 flights satisfy all passenger demands; passenger trip-time loss is 129,573 min; and the average passenger load factor is 90.1%. Under an independent operation mode, passenger demands are divided into 8 categories; 13 flights satisfy all passenger demands; passenger trip-time loss is 173,705 min; and the average passenger load factor is 87.4%. The multiairport system operation mode not only improves passenger trip efficiency but also benefits airlines by improving the passenger load factor and reducing flights. Moreover, comparative analysis of a genetic algorithm versus a clustering algorithm further proves the accuracy of the clustering algorithm.
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Zhao, Xing, Yan Li, and Han Xia. "Behavior decision model for park-and-ride facilities utilization." Advances in Mechanical Engineering 9, no. 7 (July 2017): 168781401770890. http://dx.doi.org/10.1177/1687814017708907.
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With the accelerated process of urbanization and traffic development, especially the urban rail transit system’s great improvement, Park-and-Ride provides an effective mode for trips between suburbs and downtown. In this research, online and field survey is carried out on the use of Park-and-Ride facilities. Analyses are conducted on personal attributes containing gender, age, and income; the travel characteristics such as driving time during departing from origin to parking lot, parking duration, transfer mode, transfer walking time and waiting time, and transfer times; Park-and-Ride users’ intentions concerned walking time, waiting time, and time looking for parking space; and reasons for Park-and-Ride trip mode not be chosen. On the basis of decomposition for travel procedures, impedance models for different trip modes including public transport, private car, and Park-and-Ride are built and then the multinomial logit model for choice probability of trip modes and Park-and-Ride demand model is established. After further analysis on the survey data, calibrations and tests for the impedance models above are performed. Finally, a case is shown to demonstrate application of the proposed model.
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Tang, Chunyan, Ying-En Ge, Jiyu Zhang, and Qi Xu. "Modeling Limited-Stop Bus Corridor Services with Fare Payment Mode Choice and Trip Purpose Consideration." Computational Intelligence and Neuroscience 2022 (November 2, 2022): 1–16. http://dx.doi.org/10.1155/2022/4329943.
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This paper proposes a novel model for optimizing limited-stop bus corridor services with consideration of varied payment modes and different trip purposes. In the proposed model, the bus dwell time at a stop is dependent on the fare payment modes and the number of passengers getting off and waiting at the stop while those with the similar trip purpose are grouped into one user class. Given an origin–destination (OD) passenger trip matrix and a set of candidate bus lines serving a corridor, the proposed model is to minimize the total social cost that consists of the cost to the bus operator and the cost to the passengers. In the formulation of the optimization problem, a weighting parameter is adopted to balance the operator cost and the passenger cost. Numerical examples are presented to illustrate the importance of considering passenger flow impacts on bus (and passenger) travel times in the proposed model. We also investigate effects on the optimal limited-stop services (e.g., short-turn, skip-stop, and express) taking into account the choice of fare payment modes (e.g., on-board fare collection including payment by cash, magnetic strip or smart card, off-board fare collection) and different values of travel time due to passenger trip purposes. It is shown that the off-board payment mode would be more efficient in a high-demand corridor, that more passengers prefer to express and skip-stop services rather than normal regular services in the four collection systems, and that different limited-stop service plans should be used for different periods of the day in response to temporal variation in OD passenger travel patterns. The intellectual merit of this paper is not the seemingly obvious conclusions but that the proposed model can handle the problem of limited-stop bus corridor service design with the consideration of fare payment mode choice and trip purposes.
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Khursheed, Salman, and Farhan Ahmad Kidwai. "Post COVID-19 Access-Egress Attributes for Urban Metro Transit Users in Delhi." Journal of Applied Engineering Sciences 12, no. 1 (May 1, 2022): 53–60. http://dx.doi.org/10.2478/jaes-2022-0009.
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Abstract The BLUE line of Delhi Metro (DM) has been examined to identify the post COVID-19 access–egress attributes of users. An on-board survey of metro commuters is conducted in February and March 2021. The respondents reported six different modes for access and egress trips to nearest metro stations with 38.7% and 43% users opting for walking for access-egress trip respectively. The E-rickshaw is observed to be most preferred para-transit mode whereas private vehicle has small mode share for access-egress trip. It is revealed that 46.5% of respondents are captive riders whereas 51% owns at least one motorized private vehicle. The average access and egress distance covered by walking is (0.81+ 0.32/0.35) Km respectively. The average access and egress trip time by walking is (11.19+3.73) and (11.07+4.45) minutes respectively. The average access and egress trip time by E-rickshaw is (13.21+4.09) and (12.56+2.95) minutes respectively. The access and egress trip time by motorized modes are in the range of (12.36-14.39) and (10.41-13.56) minutes respectively. The average main haul distance across all access-egress modes is observed to be (19.69+11.19) Km. To understand the factors influencing the access–egress mode choice multinomial logistic (MNL) regression models are proposed. The access-egress time and distance are observed to be significant factors in access-egress mode choice. Less parking facility offered by DM is significant factor in access mode choice. Occasional commuters are only significant factor in context with frequency of travelling in DM.
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Nasri, Arefeh, and Lei Zhang. "How Urban Form Characteristics at Both Trip Ends Influence Mode Choice: Evidence from TOD vs. Non-TOD Zones of the Washington, D.C. Metropolitan Area." Sustainability 11, no. 12 (June 20, 2019): 3403. http://dx.doi.org/10.3390/su11123403.
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Understanding travel behavior and its relationship with built environment is crucial for sustainable transportation and land-use policy-making. This study provides additional insights into the linkage between the built environment and travel mode choice by looking at the built environment characteristics at both the trip origin and destination in the context of transit-oriented development (TOD). The objective of this research is to provide a better understanding of how travel mode choice is influenced by the built environment surrounding both trip end locations. Specifically, it investigates the effect of transit-oriented development policy and the way it affects people’s mode choice decisions. This is accomplished by developing discrete choice models and consideration of urban form characteristics at both trip ends. Our findings not only confirmed the important role the built environment plays in influencing mode choice, but also highlighted the influence of policies, such as TOD, at both trip end locations. Results suggest that the probability of choosing transit and non-motorized modes is higher for trips originating and ending in TOD areas. However, the magnitude of this TOD effect is larger at trip origin compared to destination. Higher residential and employment densities at both trips ends are also associated with lower probability of auto and higher probability of transit and non-motorized mode choices.
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Peng, Hui, and Man Man Xu. "Study on the Model of Intercity Passengers' Trip Mode Choice Based on Cluster Analysis Method." Applied Mechanics and Materials 178-181 (May 2012): 1934–40. http://dx.doi.org/10.4028/www.scientific.net/amm.178-181.1934.
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In order to make the forecasting results of intercity rail transit's passenger volume conform to the actual situation, as well as that the model of intercity passengers' trip mode choice can better reflect the actual situation, this paper will take the following two aspects into account: one is that different socio-economic characterized intercity passengers will choose different ways to travel; the other is that intercity passengers' whole travel is classified into urban trip and transport corridor trip. Therefore, when determine characteristic variables of the utility function, in addition to the travel time and cost, comfort and safety will also be included, and be quantified following the scoring method. After all the above analysis, the logit model based on cluster analysis method will be established, and the reliability and effect of the model will be verified through an example.
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MATSUSHIMA, Kakuya, Kiyoshi KOBAYASHI, and Hiroshi FUKUI. "A TRIP MODE CHOICE MODEL WITH ENDOGENEITY IN EXPLANATORY VARIABLES." Journal of Japan Society of Civil Engineers, Ser. D3 (Infrastructure Planning and Management) 69, no. 5 (2013): I_511—I_521. http://dx.doi.org/10.2208/jscejipm.69.i_511.
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LIU, Gang. "A behavioral model of work-trip mode choice in Shanghai." China Economic Review 18, no. 4 (January 2007): 456–76. http://dx.doi.org/10.1016/j.chieco.2006.09.001.
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Iwamoto, Takeshi, Shiro Yamanaka, and Alexis Rusinek. "Deformation Mode Dependency on Strain Rate Sensitivity of Volume Resistivity in TRIP Steel." Key Engineering Materials 535-536 (January 2013): 473–76. http://dx.doi.org/10.4028/www.scientific.net/kem.535-536.473.
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With a phenomenon of strain-induced martensitic transformation, TRIP steel is expected to show excellent impact energy absorption characteristic. It is important for an improvement of a reliability of TRIP steel to evaluate an amount of martensite. In this study, AISI304, which is a kind of TRIP steel, is deformed plastically by a conventional material testing machine and the split Hopkinson pressure bar apparatus. During the deformation of TRIP steel, a circuit based on the Kevin double bridge measures change in volume resistivity which has a correlation with the amount of martensite. Experimental results show that the change in volume resistivity during the process of deformation at various strain rates.
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Upahita, Dwi Phalita, Maharani Almira Salsabila, Meiyanne Lestari, Sucipto Sucipto, and Djoko Prijo Utomo. "The Influence of Trip Purpose on the Mode Choice Between High-Speed Train and Airplane: Leisure Vs. Non-Leisure Trip." RSF Conference Series: Engineering and Technology 2, no. 2 (November 29, 2022): 222–31. http://dx.doi.org/10.31098/cset.v2i2.576.
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Jakarta – Surabaya Corridor plays an important role in connecting two major metropolitan cities in Java Island on each end and other cities in between the corridors. The corridor is currently served by highway, conventional rail network, and air transport mode. However, due to high trip demand, this corridor almost reaches its capacity. Developing a high-speed train network between Jakarta – Surabaya is one of the priority programs stated in the National Railway Masterplan (RIPNAS). The Jakarta – Surabaya high-speed train will be a competitor to the existing air transportation services, as both modes have competitive travel time and pricing. Previous studies have shown that operation HSR could have an adverse effect on the demand for airplane passengers. Passenger mode choice can be influenced by several factors, including the trip’s purpose. This study aims to understand the differences between leisure and non-leisure trip maker in choosing their mode. Specifically, this study focuses on the competition between a high-speed train and existing air transport service on Jakarta – Surabaya Corridor. A stated preference survey was used to collect data on passenger mode choice. The logit binomial model was used to model the mode choice, with time and cost differences as the quantitative independent variables and trip purpose as the qualitative variable. This study used a dummy variable to represent the different trip purposes, leisure and non-leisure. The result found that the odds ratio is 0.646, which indicated that passengers on leisure trips are less likely to move to HST from the airplane. This result is useful for the planner as it can indicate the potential passenger demographic and come up with services that suit their needs.
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Anderson, Michael D., and Dilip N. Malave. "Dynamic Trip Generation for a Medium-Sized Urban Community." Transportation Research Record: Journal of the Transportation Research Board 1858, no. 1 (January 2003): 118–23. http://dx.doi.org/10.3141/1858-17.
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Traditional transportation modeling activities in medium-sized urban communities follow the four-step planning process: trip generation, trip distribution, mode split, and traffic assignment. These models forecast daily traffic volumes on major roadways of the communities to support infrastructure investment decisions. Recently, researchers have focused on dynamic traffic-assignment models, which provide time as a measure in the trip-modeling process, to support incident management and intelligent transportation system–based decisions. As a methodology to support the dynamic traffic-assignment models, development of a dynamic trip-generation model for a medium-sized urban community is considered. An overview of the need for dynamic trip-generation data is presented, and a methodology and a data-collection effort to develop a dynamic trip-generation model are discussed. Results are included of a validation study performed on the model. It is concluded that the models developed in the effort can provide dynamic trip-generation data and represent a first step toward making the dynamic transportation model a viable resource.
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Wang, Bo Bin, Chun Fu Shao, Juan Li, Xun Ji, and Chong Zi Xiao. "Influence of Integrated Multimodal Travel Information on Holiday Trip Chain Characteristics." Applied Mechanics and Materials 433-435 (October 2013): 1392–95. http://dx.doi.org/10.4028/www.scientific.net/amm.433-435.1392.
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Based on the RP-SP data collected in the holiday travel behavior survey in 2013, this paper analyzed the impact effect of integrated multimodal travel information (IMTI) on the holiday trip chain characteristics. General statistical analysis is adopted to compare the trip chain structural characteristics, spatial-temporal characteristics and the mode split under the IMTI service or not. The results show that, under the influence of IMTI, 9% of the travelers will cancel their trips and 13% will change their trip mode. Moreover, the pre-trip information has a significant influence on the activity point number, trip chain length and travel time, has moderate influence on activity duration, and has weak influence on transfer time and trip distance. On the other hand, the en-route information has weak influence on the trip chain structure and spatiotemporal characteristics.
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Usanga, I. N., R. K. Etim, and V. Umoren. "Estimation of trip generation rates for residential land use in Uyo, Nigeria." Nigerian Journal of Technology 39, no. 4 (March 23, 2021): 972–80. http://dx.doi.org/10.4314/njt.v39i4.2.
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Change in trip rates affects a transportation system and could lead to the redesign of the transport infrastructure in order to satisfy the new demand. This study estimates trip generation rates for residential land use in Uyo using cross classification method. Five (5) residential estates were considered and household survey carried out to collect trip data from 500 households on purpose and mode of travel through household interview and their response recorded in questionnaire. Four independent variables (household size, household income, car ownership, number of employed persons) were used for the study based on the prevailing conditions of theresidential land use. Cross-classification trip rates were developed from the most significant variables; household size, household income and car ownership. The analysis indicated that work trip produced the highest reported trip rates of 29.6% followed by religious trip of 24.7%. Similarly, private car trips contributed 42.8% of trips made by mode of travel as the highest trip. It was found that household size is the strongest socio-economic variable that influence trip generation in residential land use in Uyo. The cross-classification trip rates developed in this study could provide basis for the estimation of trip generation in residential land use in Uyo.
Keywords: Trip generation; analysis of variance, ANOVA; cross classification
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Suraharta, I. Made. "PENGEMBANGAN MODEL TRANSPORTASI PENUMPANG ANTAR KOTA/KABUPATEN DI PROPINSI JAWA BARAT." Jurnal Teknik Sipil Unaya 1, no. 1 (January 31, 2015): 77–94. http://dx.doi.org/10.30601/jtsu.v1i1.9.
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Transport models are crucial in the transportation planning process. Transport model is made by adjusting the needs and availability of data and capability models in representing the real conditions and the future. Transportation models commonly used in transportation planning mechanism is the sequential demand models, which include the trip generation, trip distribution, mode choice, and traffic assignment. This model is suitable to be applied to various situations study areas, especially areas of the city. For intercity regional planning needs, modeling the sequential demand can be simplified into a direct demand model, the record is not much involved in modeling mode. In this study, the authors tried to develop a model of a direct demand models to represent the pattern of movement of people with other modes of road in West Java. The proposed transport model is a function of population, GDP, total number of trip generation traffic zone, the total transportation costs (generalized cost). Model results show the validity of the development of significant and can be used as a travel demand model for transportation planning.
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Deka, Devajyoti. "An explanation of the relationship between adults’ work trip mode and children’s school trip mode through the Heckman approach." Journal of Transport Geography 31 (July 2013): 54–63. http://dx.doi.org/10.1016/j.jtrangeo.2013.05.005.
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Chao, Jie, and Jing Yi Sun. "Research on Residents’ Trip Structure Based on Low Carbon Transport Mode." Applied Mechanics and Materials 744-746 (March 2015): 2115–19. http://dx.doi.org/10.4028/www.scientific.net/amm.744-746.2115.
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In order to ease the traffic problem, traffic jam, safety and pollution, arisen and been getting serious with urban development, low carbon transport was used generally on building frame of urban traffic. Based on deep research and analyze for the relationship between low carbon transport and the urban, the essay discussed the residents’ trip structure under plans of low carbon transport.Building the indicator system that the influence factors of residents’ trip structure under plans of low carbon transport was the first and key progress. Meanwhile, Analytical Hierarchy Process was used to the importance of each factor. Better frame was built by finished steps. With the frame, probability theory was used by analyzing options for residents’ trip structure option. And low carbon transport demonstration area of Kunming Chenggong was chosen to be the case that offered a real environment to test the model. The test proved that the model can guide the residents’ trip structure, which provided an outline to the department of transportation.
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Wang, Wenjing, Yanyan Chen, Haodong Sun, and Yusen Chen. "Multiple Binary Classification Model of Trip Chain Based on the Fusion of Internet Location Data and Transport Data." Sustainability 13, no. 21 (November 8, 2021): 12298. http://dx.doi.org/10.3390/su132112298.
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Observing and analyzing travel behavior is important, requiring understanding detailed individual trip chains. Existing studies on identifying travel modes have mainly used some travel features based on GPS and survey data from a small number of users. However, few studies have focused on evaluating the effectiveness of these models on large-scale location data. This paper proposes to use travel location data from an Internet company and travel data from transport department to identify travel modes. A multiple binary classification model based on data fusion is used to find out the relationship between travel mode and different features. Firstly, we enlisted volunteers to collect travel data and record their travel trip process using a custom-developed WeChat program. Secondly, we have developed three binary classification models to explain how different attributes can be used to model travel mode. Compared with one multi-classification model, the accuracy of our model improved significantly, with prediction accuracies of 0.839, 0.899, 0.742, 0.799, and 0.799 for walk, metro, bike, bus, and car, respectively. This suggests that the model could be applied not only in engineering practice to identify the trip chain from Internet location data but also in decision support for transportation planners.
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Syafriharti, Romeiza, B. Kombaitan, Iwan P. Kusumantoro, and Ibnu Syabri. "Relationship between train users’ perceptions of walkability with access and egress mode choice." MATEC Web of Conferences 147 (2018): 02004. http://dx.doi.org/10.1051/matecconf/201814702004.
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The purpose of this study is to understand whether there is a relationship between train users’ perceptions of walkability in built environment of trip origin with access mode choice and between train users’ perceptions of walkability in built environment of trip destination with egress mode choice. Train users are who ride from Cicalengka station Bandung Regency, West Java, Indonesia. To analyze the relationship is used crosstab method. The perceptual factors about walkability are those perceived by the train users consisting of walking distance, safety, comfort, and secure from crime, both in origin and destination of the built environment. The mode choice consist of walking, paratransit, motorcycle taxi, and own vehicles (or others for egress mode). To better understand the relationship is used several control variables, that are trip purposes, train usage, gender, and age. For access trip there is another control variable, that is vehicle ownership. Train users' perceptions of walkability have a relationship with both the access and the egress mode choice, except for the security aspect. The influence of control variables on the relationship between perceptions of walkability with access/egress mode choice varies for walking distance, safety, and comfort.
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Bindar, Muhammad Abdul Mubdi. "FAKTOR PEMILIHAN MODA PENGUNJUNG CAR-FREE DAY KOTA BANDUNG." Jurnal Perencanaan dan Pengembangan Kebijakan 2, no. 3 (December 10, 2022): 239. http://dx.doi.org/10.35472/jppk.v2i3.1017.
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This paper aims to reveal the dimension underlying variables that affect the trip makers; mode choice to reach Car-Free Day location, taking Bandung as a case study. Twelve variables are gathered from several works of literature, namely trip cost, parking cost, trip duration, trip distance, number of people on the trip, the highest number of lanes in the trip, the age of the trip maker(s), number of vehicle ownership, whether those are motorized or non-motorized, and the number of household member. Correlations between variables are more than possible to find in that amount. Therefore, a principal component analysis is used to group the variables into factors, representing the structure or dimension laid down beneath them. This method shows that five groups of variables, or factors, are generated. The result then is compared to number of literatures that priorly have been reviewed. These factors finally are refined by grouping them into only 3 factors: “trip characteristics”, which consist of trip duration, the highest number of lanes in the trip, and trip distance. The second factor, namely trip-maker characteristics, which is built upon trip maker’s age(s), number of people on the trip, and vehicle ownership of the trip maker(s). The last, but not least, factor is labeled “household structure”, with its variables being the number of adults and kids in the trip maker’s household. Each factor also contains the variables’ factor loadings.
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Roh, Hyuk-Jae. "Mode Choice Behavior of Various Airport User Groups for Ground Airport Access." Open Transportation Journal 7, no. 1 (October 18, 2013): 43–55. http://dx.doi.org/10.2174/1874447820130930002.
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In this research, we used a multinomial logit (MNL) discrete choice analysis technique to deepen the understanding of the mode choice behavior of various airport user groups categorized by trip purpose and trip distance for ground airport access. We used revealed preference (RP) data collected by an on-site-survey administrated by the Korea Transport Institute (KOTI) at the Kimpo International Airport passenger terminal in South Korea. Initially, four basic models were selected from a variety of model specifications, and these were analyzed to address general preferences in mode choice. The models were then evaluated in terms of the resulting estimation. The best-fitting model specification among four models was chosen for further study. Both trip distance models (standard-distance (SD) and long-distance (LD)) and trip purpose models (departing (D) and non-departing (ND)) were estimated. The results analyzed in this study encompass an unambiguous spectrum of mode choice behaviors associated with distinct airport user groups. The fundamental information, either revealed or reflected by modeling ground airport access for various airport user groups, could be essential not only to transportation planners -especially at the first phase of airport planning- but also to airport authorities faced with difficulties in managing ground transportation facilities to effectively serve airport users.
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Kyaing, Ko Ko Lwin, and Yoshihide Sekimoto. "Analysis of Trip Distributions of Human Mobility Patterns and Their Transit Behaviors Using Mobile Call Detail Records." Journal of Disaster Research 15, no. 3 (March 30, 2020): 437–45. http://dx.doi.org/10.20965/jdr.2020.p0437.
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Rapid urbanization and modernization are increasing worldwide, including in Myanmar. Mobile call detail records (CDRs) provide new opportunities for measuring transport demands and problems in transportation planning. This research aims to analyze trip distributions and transit behaviors of mobile phone users based on their call activities. Origin-Destination (O-D) pairs were computed for the entire city, and the trip distributions help understand human mobility. It was found that zone-to-zone flow has the highest flow in commercial and industrial areas. Moreover, the logical assumptions were specified to extract the transit behaviors of users. The results indicate the degree of mode-to-mode transfer behaviors of users. Among the four categories of transit usage, only rail users do not transfer to other modes, having the lowest proportion, with other mode-to-other mode transfers having the highest proportion. The results were validated with the Person Trip Survey for Comprehensive Urban Transport Plan of the Greater Yangon. This study contributes significantly to the expansion of current and potential future transit systems, which can provide a new and improved transport system for Yangon City to meet its demands. This information is helpful in conducting disaster management and emergency preparedness in terms of trip distributions of human mobility patterns changing over space and time and the transit behaviors of the transferring mode in daily trips.
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Wang, Yanli, Bing Wu, Zhi Dong, and Xin Ye. "A Joint Modeling Analysis of Passengers’ Intercity Travel Destination and Mode Choices in Yangtze River Delta Megaregion of China." Mathematical Problems in Engineering 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/5293210.
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Joint destination-mode travel choice models are developed for intercity long-distance travel among sixteen cities in Yangtze River Delta Megaregion of China. The model is developed for all the trips in the sample and also by two different trip purposes, work-related business and personal business trips, to accommodate different time values and attraction factors. A nested logit modeling framework is applied to model trip destination and mode choices in two different levels, where the lower level is a mode choice model and the upper level is a destination choice model. The utility values from various travel modes in the lower level are summarized into a composite utility, which is then specified into the destination choice model as an intercity impedance factor. The model is then applied to predict the change in passenger number from Shanghai to Yangzhou between scenarios with and without high-speed rail service to demonstrate the applicability. It is helpful for understanding and modeling megaregional travel destination and mode choice behaviors in the context of developing country.
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HE, Juan, Wei DENG, Qizhou HU, and Zhiming LIU. "Urban Road Grade Proportion Based on Trip Mode." Journal of Transportation Systems Engineering and Information Technology 8, no. 5 (October 2008): 88–93. http://dx.doi.org/10.1016/s1570-6672(08)60042-2.
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Lin, Teddy, Siva Srikukenthiran, Eric Miller, and Amer Shalaby. "Subway user behaviour when affected by incidents in Toronto (SUBWAIT) survey — A joint revealed preference and stated preference survey with a trip planner tool." Canadian Journal of Civil Engineering 45, no. 8 (August 2018): 623–33. http://dx.doi.org/10.1139/cjce-2017-0442.
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Transit user behavioural response under disrupted service conditions, specifically how transit riders choose among available mode options to complete their trips, is not well understood. This study aimed to investigate transit user mode choice in response to rapid transit service disruption in the City of Toronto, incorporating such factors as the type of disruption, stage of the passenger’s trip (pre-trip or en-route), weather conditions, and uncertainty of delay duration. A joint revealed preference (RP) and stated preference (SP) survey was designed where the RP part gathered information on the respondent’s actual response to the most recent service disruption while the SP part solicited the respondent’s travel choices under a set of hypothetical service disruption scenarios. A transit trip planner tool was developed to generate alternative transit mode and path options to avoid the disrupted segment. An empirical model using RP data is presented to verify the survey design technique.
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Lan-fen, ZHONG, and WANG Wen-zhong. "Mode shift at bottleneck increasing transit dispatch in peak time." MATEC Web of Conferences 308 (2020): 01001. http://dx.doi.org/10.1051/matecconf/202030801001.
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For attracting more auto commuters to shift to transit mode and mitigating congestion at a bottleneck in morning &rush hour, additional dispatches of transit are operated during peak time. Classical bottleneck model combining with Logit-based discrete choice formula is extended to investigate commuters’ mode choice behaviors between private car and public transit. The existence of bi-mode user equilibrium when tolling auto commuter is proofed, and waiting time and time delay costs are formulated in two modes when additional buses are dispatched. Numerical experiments are conducted to examine mode split patterns and aggregate travel cost when additional dispatching service interval varying. Our results show the system aggregate trip cost would reduce prominently when extra buses are added into runs in appropriate time. Especially when waiting time equals 0.65 hour for auto commuters, the system aggregate trip cost would reduce by 70% in theory.
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REDDY, Kanala Teja Vinay Kumar, and Surya Prakash CHALLAGULLA. "MEASUREMENT OF DELAY USING TRAVEL TIME RELIABILITY STATISTICS IN AN URBAN OUTER CORRIDOR." Scientific Journal of Silesian University of Technology. Series Transport 114 (January 1, 2022): 143–54. http://dx.doi.org/10.20858/sjsutst.2022.114.12.
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Unexpected delay on freeways is the prime cause of dissatisfaction in road users. Increasing traffic, adverse environmental conditions, accidents, time, season, location and many more factors influence travel time and cause delay. There is no direct method to estimate delay. It is calculated from trip time estimates. Thus, it is a very big challenge for transportation professionals to develop a model that accurately estimates the trip time for a trip at a particular time, by a specific mode of transport. Subsequently, the reliability of the delay calculated from those trip time estimates is often doubtful. Further, the measurement of delay using the trip time data is another big thing. This paper is a step toward measuring the delay in an accurate way using travel time reliability measures. The study was conducted on the two modes of public transportation (City bus and Auto) in an urban corridor of length 16.3 km, in Hyderabad city, India. In this study, a license plate survey was conducted for data collection, travel time-based statistical analysis was employed for estimation of trip time and by making use of travel time measures, the delay was measured. The approach was validated graphically to portray its accuracy.
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Nurul Habib, Khandker. "A Heteroscedastic Polarized Logit Model to Investigate the Competition of Bicycle for the Bikeable Trips with the Other Modes." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 49 (September 20, 2018): 58–68. http://dx.doi.org/10.1177/0361198118796357.
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The paper proposes a new discrete choice model, named the Heteroscedastic Polarized Logit (HPL) to investigate choice contexts with one or more alternatives with remarkably low market shares. The proposed model is used to investigate the factors influencing the choice of a bicycle as a travel mode in the National Capital Region (NCR) of Canada. Data from the latest household travel survey of the NCR are used to investigate the mode choices of bikeable trips. Bikeable trips are defined as trips with lengths shorter than 16 km as this is the observed maximum limit of a bicycle trip in the dataset. A large dataset with over 40,000 trip records is used for empirical investigation where the bicycle has the lowest mode share of 3%. The HPL model clearly shows its appropriateness and superiority over comparable models in such a context. The choice to walk is found to be more sensitive to trip length than the choice to cycle, yet walking is found to have three times larger market share than that of cycling. Similarly, motorized modes are found to have low sensitivity to travel time and other impedances and have larger market shares. Women and students are found not to prefer the bicycle as a travel mode. Cycling infrastructure is seen to be effective in increasing the choice of the bicycle as a travel mode, but it also becomes clear that additional soft policy initiatives would be necessary to increase the popularity of cycling among young people, students, and women.
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Lai, Ruxin, Xinwei Ma, Fan Zhang, and Yanjie Ji. "Life Cycle Assessment of Free-Floating Bike Sharing on Greenhouse Gas Emissions: A Case Study in Nanjing, China." Applied Sciences 11, no. 23 (November 29, 2021): 11307. http://dx.doi.org/10.3390/app112311307.
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The free-floating bike sharing (FFBS) system appears in the form of low-carbon transport mode. Life cycle assessment (LCA) is a method to analyze the environmental impact of FFBS but has rarely considered the trip chain if the intermodal transport modes were employed. This paper proposes a mathematical formalization of LCA in response to the trip chain. The environmental benefit of FFBS was analyzed by this method considering the production, use, operation, and disposal phases in Nanjing. An online survey was conducted to analyze the mechanism of modal shift influenced by FFBS. The results showed that most respondents only use FFBS in the trip, with savings of 63.726 g CO2-eq/p·km, mainly shifting from lower-emission modes (28.30% from bus, 14.86% from metro, and 33.97% from non-motorized modes), while the trip mode of connecting public transport with FFBS could better replace the motorized transport trip and generate better low-carbon benefits with savings of 300.718 g CO2-eq/p·km. One FFBS should be used for at least 227 days to generate positive environmental benefits based on the current number of FFBS and the assumption of the utilization of each bike, which is once a day on average. The research results can effectively support the environmental benefit analysis of FFBS, the subsequent planning based on the low-carbon concept, and the implementation of relevant incentive policies.
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Moeckel, Rolf, Leta Huntsinger, and Rick Donnelly. "From Macro to Microscopic Trip Generation: Representing Heterogeneous Travel Behavior." Open Transportation Journal 11, no. 1 (March 23, 2017): 31–43. http://dx.doi.org/10.2174/1874447801711010031.
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Background: In four-step travel demand models, average trip generation rates are traditionally applied to static household type definitions. In reality, however, trip generation is more heterogeneous with some households making no trips and other households making more than a dozen trips, even if they are of the same household type. Objective: This paper aims at improving trip-generation methods without jumping all the way to an activity-based model, which is a very costly form of modeling travel demand both in terms of development and computer processing time. Method: Two fundamental improvements in trip generation are presented in this paper. First, the definition of household types, which traditionally is based on professional judgment rather than science, is revised to optimally reflect trip generation differences between the household types. For this purpose, over 67 million definitions of household types were analyzed econometrically in a Big-Data exercise. Secondly, a microscopic trip generation module was developed that specifies trip generation individually for every household. Results: This new module allows representing the heterogeneity in trip generation found in reality, with the ability to maintain all household attributes for subsequent models. Even though the following steps in a trip-based model used in this research remained unchanged, the model was improved by using microscopic trip generation. Mode-specific constants were reduced by 9%, and the Root Mean Square Error of the assignment validation improved by 7%.
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Zhao, Yang, Liang, Guo, Lu, Zhang, and Ren. "Last-Mile Travel Mode Choice: Data-Mining Hybrid with Multiple Attribute Decision Making." Sustainability 11, no. 23 (November 27, 2019): 6733. http://dx.doi.org/10.3390/su11236733.
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Transit offers stop-to-stop services rather than door-to-door services. The trip from a transit hub to the final destination is often entitled as the “last-mile” trip. This study innovatively proposes a hybrid approach by combining the data mining technique and multiple attribute decision making to identify the optimal travel mode for last-mile, in which the data mining technique is applied in order to objectively determine the weights. Four last-mile travel modes, including walking, bike-sharing, community bus, and on-demand ride-sharing service, are ranked based upon three evaluation criteria: travel time, monetary cost, and environmental performance. The selection of last-mile trip modes in Chengdu, China, is taken as a typical case example, to demonstrate the application of the proposed approach. Results show that the optimal travel mode highly varies by the distance of the “last-mile” and that bike-sharing serves as the optimal travel mode if the last-mile distance is no more than 3 km, whilst the community bus becomes the optimal mode if the distance equals 4 and 5 km. It is expected that this study offers an evidence-based approach to help select the reasonable last-mile travel mode and provides insights into developing a sustainable urban transport system.
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Hou, Zhi-Wei, Shijun Yu, and Tao Ji. "Modeling the Trip Distributions of Tourists Based on Trip Chain and Entropy-Maximizing Theory." Applied Sciences 11, no. 21 (October 27, 2021): 10058. http://dx.doi.org/10.3390/app112110058.
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Suburban tourist railway is an emerging transportation mode for tourism. Knowing the travel demand and trip distribution patterns of tourists is an important prerequisite to the planning and construction of suburban tourist railways. However, this issue has attracted very little research attention so far. Therefore, this paper proposes a forecasting model focused on the trip distribution of tourists who travel with the suburban tourist railway. Based on the analysis of the characteristics of tourists’ trips and the use of the trip chain method, the frequency, order, distance, and visiting volume of stay points of the trips of tourists have been intensively studied. Then, a tourist trip distribution forecasting model was built in this paper. It uses the Entropy-Maximizing theory to predict trip chain distribution probability and obtain the distribution of tourists within the city. A case study that takes the H city as an example was conducted to test the proposed model. The results of this case show that the output of the model can reflect the real trip distribution characteristics of tourists very well, which demonstrates the applicability and effectiveness of the proposed model.
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Grisé, Emily, and Ahmed El-Geneidy. "Transferring Matters: Analysis of the Influence of Transfers on Trip Satisfaction." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 9 (May 5, 2019): 254–65. http://dx.doi.org/10.1177/0361198119844964.
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Conventional wisdom in public transport planning suggests that transfers should be minimized because of the negative perceptions associated with them. However, little is known about how transferring affects overall satisfaction levels. This study aims to answer the following three research questions: (1) Are people that require transfers on their daily commute less satisfied with their trips compared with their non-transferring counterparts? (2) How many transfers appear to be too many transfers to remain satisfied with a trip? (3) Do mode-specific transfers have different impacts on overall satisfaction levels? Using data from a 2017/18 commuting survey of students, faculty, and staff at McGill University, Montreal, Canada, this study tries to answer the above questions through two statistical models, general and mode-specific. The general model showed that compared with trips involving zero transfers, no statistical difference in trip satisfaction was observed for one-transfer trips, whereas trip satisfaction declines by 32% when a rider must transfer at least two times. The mode-specific transfers showed that transferring between bus routes, and between a bus and subway, negatively affects trip satisfaction. However, transferring between subway lines did not show an impact in the models. These results show that transferring between high-frequency routes does not affect total trip satisfaction levels in the same way as transfers involving low-frequency services. Findings from this study are expected to contribute to both scholarly and practical discussions of the relationship between transferring and customer satisfaction.
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Moeckel, Rolf, Nico Kuehnel, Carlos Llorca, Ana Tsui Moreno, and Hema Rayaprolu. "Agent-Based Simulation to Improve Policy Sensitivity of Trip-Based Models." Journal of Advanced Transportation 2020 (February 25, 2020): 1–13. http://dx.doi.org/10.1155/2020/1902162.
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The most common travel demand model type is the trip-based model, despite major shortcomings due to its aggregate nature. Activity-based models overcome many of the limitations of the trip-based model, but implementing and calibrating an activity-based model is labor-intensive and running an activity-based model often takes long runtimes. This paper proposes a hybrid called MITO (Microsimulation Transport Orchestrator) that overcomes some of the limitations of trip-based models, yet is easier to implement than an activity-based model. MITO uses microsimulation to simulate each household and person individually. After trip generation, the travel time budget in minutes is calculated for every household. This budget influences destination choice; i.e., people who spent a lot of time commuting are less likely to do much other travel, while people who telecommute might compensate by additional discretionary travel. Mode choice uses a nested logit model, and time-of-day choice schedules trips in 1-minute intervals. Three case studies demonstrate how individuals may be traced through the entire model system from trip generation to the assignment.