Taxi Drivers’ Cruising Patterns—Insights from Taxi GPS Traces

Zong, Fang; Wu, Ting; Jia, Hongfei

doi:10.1109/tits.2018.2816938

Cited by 31 publications

(19 citation statements)

References 11 publications

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“…It is an important supplement for other transit options, especially at night when the most transit options stop operating. Taxi trajectory data that record a series of GPS points and other information such as instantaneous velocity, status and time, which has been widely used in analyzing characteristics of taxicab movement [8]- [10], travelers' mobility [11]- [13], travel pattern [14], [15], traffic congestion [16], [17], route choice [18]- [20], taxi trip characteristics [21], [22] etc. Taxi operates without fixed line, schedule and stations, which can achieve the spatiotemporal characteristic of travelers.…”

Section: Introductionmentioning

confidence: 99%

Revealing Urban Traffic Demand by Constructing Dynamic Networks With Taxi Trajectory Data

Zhang

Zhang²,

Che

et al. 2020

IEEE Access

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As a crucial travel mode, taxi plays a significant role in residents' daily travel. Uncovering taxi traffic demand has become a hotspot in transport studies. Previous researchers pay more attention to the statistical characteristics of taxi trips, while few studies focus on the dynamic features in different periods of a day. In this paper, we study the taxi travel demand by constructing dynamic networks based on taxi trajectory data. In addition, relationship between travel intensity and point of interest (POI) in Xiamen, China is discussed. Firstly, the study area is divided by 1km×1km uniform cells. The pickup and drop-off activities of passengers are recorded for each cell. Secondly, the networks are constructed by regarding each cell as a node and regarding taxi trips from a cell to another cell as an edge. On this basis, we divide a day into 12 periods by two hours and construct the networks for different periods. Finally, correlation between travel intensity and POI intensity is detected with regression analysis. Results show that the taxi trip networks have large clustering coefficient and small shortest path length, which indicates they are 'small world' networks. Moreover, the taxi trip networks are disassortative networks that hotspot areas tend to connect with the common areas. Furthermore, the taxi trip length in a day follows a lognormal distribution and the peak hour of taxi trip appears around midnight. Finally, a cubic polynomial curve could fit the relationship between travel intensity and POI intensity. Our findings provide a new insight for understanding the traffic demand of taxi. INDEX TERMS Urban traffic demand, dynamic spatial-interaction network, spatiotemporal characteristics of taxi trips, taxi GPS trajectory data, point of interest This work is licensed under a Creative Commons Attribution 4.

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Section: Introductionmentioning

confidence: 99%

Revealing Urban Traffic Demand by Constructing Dynamic Networks With Taxi Trajectory Data

Zhang

Zhang²,

Che

et al. 2020

IEEE Access

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“…This method focused on the state of the road network traffic, which could obtain the traffic state and demand in a specific site in advance. For highway managers, this is an indirect method of controlling traffic states [24].…”

Section: Related Work a Traffic Demand Analysismentioning

confidence: 99%

Improved Manpower Planning Based on Traffic Flow Forecast Using a Historical Queuing Model

et al. 2019

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In order to promote travel safety and efficiency, many management staff are engaged to provide service to avoid long queues. Those manpower demands unavoidably introduce overstaffing, which is a great waste during off-peak period. However, it is not easy to precisely forecast the traffic flow to better arrange road management manpower and eliminate queuing phenomenon. In this paper, vehicle flow is first predicted with high accuracy based on the historical multi-source traffic data. The traffic data are collected for one month to establish a forecasting model. The forecasted traffic flow is tested on the following week and shows that the hourly traffic flow can be predicted in high accuracy. Improved manpower planning strategy is proposed based on the predicted results for arranging working schedule correspondingly. The proposed method is tested on a randomly selected toll gate in a real scenario as an example. A manpower planning strategy is verified with scheduled number of operating toll lanes. The improved manpower planning shows that the proposed method effectively reduces manpower by 40% at the toll gate and saves 67.5 working hours in one week compared with the current schedule. The successful application of the manpower planning method can be extended to other toll gates and service plazas to save manpower for more efficient and intelligent operation manner. INDEX TERMS Manpower planning, toll gate, forecast, traffic flow, queuing model.

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“…However, the delay that occurs during the space searching process varies due to the number of parking spaces, the layout of the parking lot, the efficiency of the parking guidance system, and the OL. Some research also indicated that the cruising time would vary according to land use [30]. When the parking facilities are chosen, the searching delay can be estimated based on a function with the OL as the only variable.…”

Section: Indexes For Evaluating the Qos Of Parking Facilitiesmentioning

confidence: 99%

Impact Analysis of Parking Price Adjustment on the Quality of Service of Airport Parking Lots for Light Vehicles

CHENG

2019

Journal of Advanced Transportation

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Pricing is a common measure for parking demand management that has been implemented worldwide. However, the impact of parking price on a parking lot’s quality of service is seldom discussed. This study investigated the impacts of a ladder daily maximum fee charging strategy on the quality of service of the Hongqiao International Airport parking lot based on automatic transaction data before and after the strategy was implemented. An evaluation framework considering managers’ and users’ perspectives was designed. The estimation results show that the new price regulation method largely discouraged long-term parking demand and improved the availability of airport parking facilities, especially during long holidays. As a consequence, throughput and income largely increased in the airport, and there were extra time costs during vehicle departures. The price elasticity of parkers with different parking durations was further estimated. The results showed that price sensitivity is relatively inelastic but varies based on parking duration.

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Taxi Drivers’ Cruising Patterns—Insights from Taxi GPS Traces

Cited by 31 publications

References 11 publications

Revealing Urban Traffic Demand by Constructing Dynamic Networks With Taxi Trajectory Data

Revealing Urban Traffic Demand by Constructing Dynamic Networks With Taxi Trajectory Data

Improved Manpower Planning Based on Traffic Flow Forecast Using a Historical Queuing Model

Impact Analysis of Parking Price Adjustment on the Quality of Service of Airport Parking Lots for Light Vehicles

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