Inferring temporal motifs for travel pattern analysis using large scale smart card data

Lei, Da; Chen, Xuewu; Cheng, Long; Zhang, Lin; Ukkusuri, Satish V.; Witlox, Frank

doi:10.1016/j.trc.2020.102810

Cited by 43 publications

(18 citation statements)

References 56 publications

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“…Depending on the nature of the data (call detail records, GPS, travel surveys) and the definition of the motif (location-or activity-based), motif-related research shows between 10 and 17 motifs that can capture 90% of the population activity-travels. These motifs also show spatio-temporal regularity and stability over several months [16][17][18][19][20]. This tends to confirm that typical locational and activity patterns exist and can be leveraged to capture a greater diversity of activity-travel behaviors.…”

Section: A Heterogeneous Demand In Time and Space With Differentiated...mentioning

confidence: 52%

Assessment of the Bus Transit Network: A Perspective from the Daily Activity-Travel Organization of Travelers

Schultheiss

2022

Sustainability

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In a context where daily car use is a spontaneous and habitual choice for a wide majority of the population, the quality of the alternatives to individual motorized vehicles is a major factor in encouraging modal shift. The ease of access to public transport can influence the mode choice decision process. However, the diversity of activity-travel patterns questions the definition of a unique and homogeneous accessibility and level-of-service to all travelers. The aim of this paper is to identify, with the help of standard data (micro-census and open data), for whom, when and where the transit supply is adequate or not. The approach is based on a twofold methodology. First, we aim to identify differentiated typical activity-travel patterns among the population. Second, to decompose them in transit supply in time and space. Combined, these two elements synthesize a spatially- and temporally-based demand-supply gap index. The results show for which territories, time slots and population groups the supply is defective or excessive with respect to the demand. Generally speaking, the supply is particularly well dimensioned for the dominant groups, such as commuters, including long-distance travelers, who are mainly men. The imbalances in supply over time and space reveal a differentiated accessibility but also significant socio-spatial inequalities.

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Section: A Heterogeneous Demand In Time and Space With Differentiated...mentioning

confidence: 52%

Assessment of the Bus Transit Network: A Perspective from the Daily Activity-Travel Organization of Travelers

Schultheiss

2022

Sustainability

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“…Literature Review. In the last decades, considerable effort has been made to identify and describe travel behavior, including travel duration, travel distance, travel modes, trip sequences or complex trip-chains, trip destinations, travel companions [6][7][8][9][10], etc. Past travel behavior studies have applied mobile phone data to detect stops and extract trips.…”

Section: Introductionmentioning

confidence: 99%

Extracting the Complete Travel Trajectory of Subway Passengers Based on Mobile Phone Data

Zhang

Cheng

et al. 2022

Journal of Advanced Transportation

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The usage of mobile phones has undergone tremendous growth in the past decades. Large amounts of mobile-phone signaling data (MSD) are generated while using various mobile phone applications. The large-scale MSD presents opportunities for transport planners to utilize it for better planning and management of the transportation system. In this paper, we use MSD to analyze subway passengers’ travel behavior and extract their complete travel trajectories. The complete travel trajectories of subway passengers include their trajectories, both inside and outside the subway system. In the first stage, the MSD from the subway base stations is selected, sorted by time, and the rough trajectory in the subway system is extracted. The ground base stations around the subway station are then considered to correct the boarding and alighting subway stations in order to obtain a more detailed trajectory. In the second stage, the service range of the base station is determined according to the Thiessen polygon, and a temporal dynamic threshold is proposed to extract the passenger’s stop point outside the subway system. Finally, the complete trajectories of subway passengers are obtained. The proposed algorithms are verified using a set of MSD collected in Suzhou, China. The results show that the proposed algorithms can effectively extract the complete travel trajectory of subway passengers.

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“…Bus is a basic mode of urban transit, which establishes the initial network structure for a city's public transport system (e.g., Ibarra-Rojas et al, 2015; [1][2][3][4][5][6]; among many others). With the advancement of urbanization, rail transit is now being rapidly constructed in many large cities so as to relieve the pressure of passenger flow.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Bus Rerouting to Alleviate the Impact of Rail Transit Construction

Wang

Chen

et al. 2022

Journal of Advanced Transportation

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In urban areas, rail transit construction affects the travel time and the efficiency of bus lines along the surrounding roads. To ensure service qualities, this study proposes a two-stage optimization method for bus rerouting to alleviate the impact of rail construction. In the first stage, the effect of the construction on bus operation is evaluated based upon one indicator, namely the increased rate of bus turnaround time. The affected lines that need rerouting are sifted by the indicator. For each rerouting line, we design two adjustment patterns and associated candidate alternative rerouting sets. In the second stage, the bus network alteration optimization model is developed to maximize the number of passengers served. The model considers several practical constraints, including service connectivity, rationality of bus travel time, and budget for building new bus stops. It realizes a systematic optimization of bus rerouting lines affected by rail transit construction. The proposed method is applied to Ning-Ma intercity railway in Ma’anshan, China to analyze the impact of construction on the surrounding bus lines and obtain the optimal adjustment scheme. The results show that the proposed method is capable of effectively reducing the negative effects caused by rail transit construction and meantime guaranteeing bus service quality.

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Inferring temporal motifs for travel pattern analysis using large scale smart card data

Cited by 43 publications

References 56 publications

Assessment of the Bus Transit Network: A Perspective from the Daily Activity-Travel Organization of Travelers

Assessment of the Bus Transit Network: A Perspective from the Daily Activity-Travel Organization of Travelers

Extracting the Complete Travel Trajectory of Subway Passengers Based on Mobile Phone Data

Optimization of Bus Rerouting to Alleviate the Impact of Rail Transit Construction

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