Modeling and Analyzing Taxi Congestion Premium in Congested Cities

Abstract

Traffic congestion is a significant problem in many major cities. Getting stuck in traffic, the mileage per unit time that a taxicab travels will decline significantly. Congestion premium (or so-called low-speed fare) has become an increasingly important income source for taxi drivers. However, the impact of congestion premium on the taxicab market is not widely understood yet. In particular, modeling and analyzing of the taxi fare structure with congestion premium are extremely limited. In this paper, we developed a taxi price equilibrium model, in which the adjustment mechanism of congestion premium on optimizing the taxi driver's income, balancing the supply and demand, and eventually improving the level of service in the whole taxicab market was investigated. In the final part, we provided a case study to demonstrate the feasibility of the proposed model. The results indicated that the current taxi fare scheme in Beijing is suboptimal, since the gain from the raise of congestion premium cannot compensate for the loss from the demand reduction. Conversely, the optimal fare scheme suggested by our model can effectively reduce the excessive demand and reach the supply-demand equilibrium, while keeping the stability of the driver's income to the maximum extent.

Uncovering Urban Mobility and City Dynamics from Large-Scale Taxi Origin-Destination (O-D) Trips: Case Study in Washington DC Area

“…3a), and their medians are respectively $1.27 and $0.97 per minute. This result is consistent with the recent study showing that the congestion often reduces the income of taxi drivers [55].…”

“…Donovan and Work [7] proposed quantitative methods measuring the resilience of transportation systems, by using the deviations of historical distribution in normalized travel time of taxi among various regions of a city. Regarding traffic congestion -a significant problem in major cities [33], a few studies [11,31,55] presented pricing schemes to support offering taxi drivers extra incentives so that they would work in congested peak hours. Concerning road safety, Boufous and Williamson [4] and Wu et al [44] investigated some safety issues of taxi trips.…”

Vehicle Movement Analyses Considering Altitude Based on Modified Digital Elevation Model and Spherical Bilinear Interpolation Model: Evidence from GPS-Equipped Taxi Data in Sanya, Zhengzhou, and Liaoyang

“…us, it is necessary for taxi companies improve their service to meet the demand of passengers. Yuan et al proposed a price equilibrium model for taxi market to improve the service level [54]. Song et al proposed a planning concept from the perspective of supply and demand economic equilibrium to optimize the transportation markets [55].…”

Taxi High-Income Region Recommendation and Spatial Correlation Analysis

“…Considering the aggravation of traffic jam, Changwei Yuan divided the taxi drivers' income into three groups, i.e., starting fee, mileage fee and waiting fee based on the economic demand theory, and proposed an optimization model of taxi waiting fee to analyze the influence of waiting fee on taxi demand and income. The author pointed out that the waiting time becomes longer as the expected profit arises [11,15]. These studies are basically based on the theoretical level of research on charging methods.…”

“…Especially during peak hours, since being trapped in congested traffic for a long time usually reduces the driver's income substantially and congestion premium cannot effectively offset the loss of the driver's income. This is because a hot-spot may not be a high-income region, which may be due to the traffic conditions or drivers habits [11].…”