Uncovering Distribution Patterns of High Performance Taxis from Big Trace Data
| Autor: | Luling Cheng, Zihan Kan, Chang Ren, Fei Sun, Luliang Tang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
050210 logistics & transportation
business.industry Downtown Computer science 05 social sciences Geography Planning and Development taxi performance taxi efficiency GPS big data space-time distribution data mining 0211 other engineering and technologies Taxis Distribution (economics) InformationSystems_DATABASEMANAGEMENT 021107 urban & regional planning 02 engineering and technology Transport engineering Ranking 0502 economics and business Traffic conditions Earth and Planetary Sciences (miscellaneous) Global Positioning System Operational efficiency Computers in Earth Sciences business Simulation TRACE (psycholinguistics) |
| Zdroj: | ISPRS International Journal of Geo-Information; Volume 6; Issue 5; Pages: 134 |
| ISSN: | 2220-9964 |
| DOI: | 10.3390/ijgi6050134 |
| Popis: | The unbalanced distribution of taxi passengers in space and time affects taxi driver performance. Existing research has studied taxi driver performance by analyzing taxi driver strategies when the taxi is occupied. However, searching for passengers when vacant is costly for drivers, and it limits operational efficiency and income. Few researchers have taken the costs during vacant status into consideration when evaluating taxi driver performance. In this paper, we quantify taxi driver performance using the taxi’s average efficiency. We propose the concept of a high-efficiency single taxi trip and then develop a quantification and evaluation model for taxi driver performance based on single trip efficiency. In a case study, we first divide taxi drivers into top drivers and ordinary drivers, according to their performance as calculated from their GPS traces over a week, and analyze the space-time distribution and operating patterns of the top drivers. Then, we compare the space-time distribution of top drivers to ordinary drivers. The results show that top drivers usually operate far away from downtown areas, and the distribution of top driver operations is highly correlated with traffic conditions. We compare the proposed performance-based method with three other approaches to taxi operation evaluation. The results demonstrate the accuracy and feasibility of the proposed method in evaluating taxi driver performance and ranking taxi drivers. This paper could provide empirical insights for improving taxi driver performance. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|