Efficiency of a highway use reservation system for morning commute

This paper examines the design and efficiency of a highway use reservation system where commuters need reservations to access a highway facility at specific times. We show that, by accommodating reservation requests to the level that the highway capacity allows, traffic congestion can be relieved. Generally, a more differentiated design of the reservation system yields a higher reduction of travel cost and thus achieves a higher efficiency. The efficiency bound of the system is established. We also show that braking or tactical waiting behaviors of drivers would cause a loss of efficiency, which thus need be proactively accommodated. Given that user heterogeneity cause further loss of efficiency, we explore how two specific types of user heterogeneity affect the system efficiency. Auction-based reservation is then proposed to mitigate the efficiency loss.     

Dynamic congestion pricing with day-to-day flow evolution and user heterogeneity

This paper investigates evolutionary implementation of congestion pricing schemes to minimize the system cost and time, measured in monetary and time units, respectively, with the travelers’ day-to-day route adjustment behavior and their heterogeneity. The travelers’ heterogeneity is captured by their value-of-times. First, the multi-class flow dynamical system is proposed to model the travelers’ route adjustment behavior in a tolled transportation network with multiple user classes. Then, the stability condition and properties of equilibrium is examined. We further investigate the trajectory control problem via dynamic congestion pricing scheme to derive the system cost, time optimum, and generally, Pareto optimum in the sense of simultaneous minimization of system cost and time. The trajectory control problem is modeled by a differential–algebraic system with the differential sub-system capturing the flow dynamics and the algebraic one capturing the pricing constraint. The explicit Runge–Kutta method is proposed to calculate the dynamic flow trajectories and anonymous link tolls. The method allows the link tolls to be updated with any predetermined periods and forces the system cost and/or time to approach the optimum levels. Both analytical and numerical examples are adopted to examine the efficiency of the method.     

Complementarity formulations for the cell transmission model based dynamic user equilibrium with departure time choice, elastic demand and user heterogeneity

In this paper we formulate the dynamic user equilibrium problem with an embedded cell transmission model on a network with a single OD pair, multiple parallel paths, multiple user classes with elastic demand. The formulation is based on ideas from complementarity theory. The travel time is estimated based on two methods which have different transportation applications: (1) maximum travel time and (2) average travel time. These travel time functions result in linear and non-linear complementarity formulations respectively. Solution existence and the properties of the formulations are rigorously analyzed. Extensive computational experiments are conducted to demonstrate the benefits of the proposed formulations on various test networks.     

Interactive travel choices and traffic forecast in a doubly dynamical system with user inertia and information provision

This study models the joint evolution (over calendar time) of travelers’ departure time and mode choices, and the resulting traffic dynamics in a bi-modal transportation system. Specifically, we consider that, when adjusting their departure time and mode choices, travelers can learn from their past travel experiences as well as the traffic forecasts offered by the smart transport information provider/agency. At the same time, the transport agency can learn from historical data in updating traffic forecast from day to day. In other words, this study explicitly models and analyzes the dynamic interactions between transport users and traffic information provider. Besides, the impact of user inertia is taken into account in modeling the traffic dynamics. When exploring the convergence of the proposed model to the dynamic bi-modal commuting equilibrium, we find that appropriate traffic forecast can help the system converge to the user equilibrium. It is also found that user inertia might slow down the convergence speed of the day-to-day evolution model. Extensive sensitivity analysis is conducted to account for the impacts of inaccurate parameters adopted by the transport agency.     

Prioritizing bicycle paths in Belo Horizonte City,Brazil: Analysis based on user preferences and willingness considering individual heterogeneity

Using bicycles as a commuting mode has proven to be beneficial to both urban traffic conditions and travelers’ health. In order to efficiently design facilities and policies that will stimulate bicycle use, it is necessary to first understand people’s attitudes towards bicycle use, and the factors that may influence their preferences. Such an understanding will enable reliable predictions of bicycle use willingness level, based on which cycling facility construction can be reasonably prioritized.As people often have different perceptions on exercising, green transportation, and traffic conditions, effects of potentially influencing factors on people’s willingness of using bicycles tend to be highly heterogeneous. This paper uses a random parameter ordered probit model to analyze how travelers’ willingness of using bicycles is influenced by various socio-economic factors in Belo Horizonte City, Brazil, with the consideration of individual heterogeneity. The data was collected through the 2010 bicycle use survey in Belo Horizonte City. Results show that, first, the willingness of using bicycle is favored by middle income class household, and negatively related with commuting time. Second, people who rent apartments tend to be more willing to use bicycles. Third, if a person is currently walking a long time to work, he/she would be most willing to commute with a bicycle in the future. Those currently commuting a relatively short distance by motorcycle and bus follow this group in terms of willingness to commute by bicycle in the future. Car users seem to be difficult to convert to bicycle users. Moreover, the estimation shows clear evidence that significant individual heterogeneity indeed exists, especially for education level, necessitating the consideration of such an effect. With the calibrated model, residents’ willingness of using bicycle commuting is then estimated for the entire Belo Horizonte City using the 2010 Census and the 2012 O/D survey data. The results are cross validated using the bicycle path preference information, also obtained from the 2010 bicycle use survey.