{"title":"是什么促使驾驶员开始寻找停车位?开始寻找过程的模型","authors":"Siavash Saki, Tobias Hagen","doi":"10.1016/j.trb.2024.103058","DOIUrl":null,"url":null,"abstract":"<div><p>This study investigates the starting point of parking search, presenting new findings through empirical and theoretical approaches. It introduces a probabilistic model that describes the transition from normal driving to actively searching for parking, aiming to minimize journey costs. The model is tested using real-world data collected via a smartphone app that tracks the start of parking searches. Results validate the model, showing that drivers are more likely to begin searching for parking earlier when parking spaces are scarce and driving speeds are reduced (e.g., by congestion). Additionally, various factors influence the start of the parking search, including driver age, vehicle class, and familiarity with the destination. Specific conditions such as proximity to amenities, rush hour timing, and destination familiarity prompt earlier search initiation. The study also identifies scenarios where drivers skip the search process and park immediately, influenced by factors like driving home, short parking durations, and destination familiarity.</p></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"188 ","pages":"Article 103058"},"PeriodicalIF":5.8000,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0191261524001826/pdfft?md5=ffa7fe89e0b35e67a94e6097a3c33052&pid=1-s2.0-S0191261524001826-main.pdf","citationCount":"0","resultStr":"{\"title\":\"What drives drivers to start cruising for parking? Modeling the start of the search process\",\"authors\":\"Siavash Saki, Tobias Hagen\",\"doi\":\"10.1016/j.trb.2024.103058\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study investigates the starting point of parking search, presenting new findings through empirical and theoretical approaches. It introduces a probabilistic model that describes the transition from normal driving to actively searching for parking, aiming to minimize journey costs. The model is tested using real-world data collected via a smartphone app that tracks the start of parking searches. Results validate the model, showing that drivers are more likely to begin searching for parking earlier when parking spaces are scarce and driving speeds are reduced (e.g., by congestion). Additionally, various factors influence the start of the parking search, including driver age, vehicle class, and familiarity with the destination. Specific conditions such as proximity to amenities, rush hour timing, and destination familiarity prompt earlier search initiation. The study also identifies scenarios where drivers skip the search process and park immediately, influenced by factors like driving home, short parking durations, and destination familiarity.</p></div>\",\"PeriodicalId\":54418,\"journal\":{\"name\":\"Transportation Research Part B-Methodological\",\"volume\":\"188 \",\"pages\":\"Article 103058\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2024-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0191261524001826/pdfft?md5=ffa7fe89e0b35e67a94e6097a3c33052&pid=1-s2.0-S0191261524001826-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part B-Methodological\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0191261524001826\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part B-Methodological","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0191261524001826","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
What drives drivers to start cruising for parking? Modeling the start of the search process
This study investigates the starting point of parking search, presenting new findings through empirical and theoretical approaches. It introduces a probabilistic model that describes the transition from normal driving to actively searching for parking, aiming to minimize journey costs. The model is tested using real-world data collected via a smartphone app that tracks the start of parking searches. Results validate the model, showing that drivers are more likely to begin searching for parking earlier when parking spaces are scarce and driving speeds are reduced (e.g., by congestion). Additionally, various factors influence the start of the parking search, including driver age, vehicle class, and familiarity with the destination. Specific conditions such as proximity to amenities, rush hour timing, and destination familiarity prompt earlier search initiation. The study also identifies scenarios where drivers skip the search process and park immediately, influenced by factors like driving home, short parking durations, and destination familiarity.
期刊介绍:
Transportation Research: Part B publishes papers on all methodological aspects of the subject, particularly those that require mathematical analysis. The general theme of the journal is the development and solution of problems that are adequately motivated to deal with important aspects of the design and/or analysis of transportation systems. Areas covered include: traffic flow; design and analysis of transportation networks; control and scheduling; optimization; queuing theory; logistics; supply chains; development and application of statistical, econometric and mathematical models to address transportation problems; cost models; pricing and/or investment; traveler or shipper behavior; cost-benefit methodologies.