Using Behavioral Economics to Identify Potential Managed Lane Users

TRANSPORTATION RESEARCH RECORD(2022)

引用 0|浏览2
暂无评分
摘要
Priced managed lanes (MLs) offer travelers an option to choose to pay a toll to travel on the MLs for a generally faster, more reliable travel than on the adjacent, toll-free general-purpose lanes (GPLs). Recent research has shown that many travelers on freeways with MLs choose the same lane type every trip regardless of travel time savings and toll rate. In this paper, a classic experimental economics traffic game was replicated and re-examined to model traveler choice by classifying travelers as "choosers" (people who frequently choose between MLs and GPLs) and "non-choosers" (people who use only one type of lane). This traffic experiment was then augmented with a travel survey to find the individual differences (psychological traits), trip-related variables, and socio-demographic variables that help differentiate travelers into the above two categories. Based on the traffic experiment and travel survey, it was found that: (1) the experiment could identify real life choosers and (2) many more travelers indicate that they are choosers in a survey than in actual travel. Features that are related to the choosing behavior were the time taken by the subject to answer a survey section and time used to verify their answers before submitting. Participants who spent more time on those things tended to be choosers. Travelers who were direct responders in the experiment tended to be choosers. Other factors that differentiated choosers from non-choosers were trip duration, familiarity with the ML facilities, and education level.
更多
查看译文
关键词
Congestion pricing, decision-making, driver perception, economics, revenue, express lanes, machine learning (artificial intelligence), operations, human factors, planning and analysis, pricing models, supervised learning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要