Changes In Headways Research Articles

Simulated Relationships between Highway Capacity, Transit Ridership, and Service Frequency

This article analyzes the relationships between highway capacity additions and transit patronage, both in the short and long run. A methodology using a model of schedule disutility is shown to provide a technique to account for transit service frequency. This technique, combined with a supply-side model of a highway corridor is used to evaluate the impact of transit headway changes and highway capacity, increases on total transit ridership, using a synthetic sample of commuters. Simulation results are used to evaluate the impact on travel times and utility of the two modes and the long-run degradation of transit service predicted by the Downs-Thomson paradox.While the results do not show congestion as necessarily being worse than before capacity expansion, they do show that transit service frequency could be reduced significantly over time.

Nonlinear analysis of the car-following model considering headway changes with memory and backward looking effect

In order to research the effects of headway changes with memory and backward looking effect on traffic flow, in the light of the full velocity difference model (FVDM), a novel car-following model that considers backward looking effect and headway changes with memory is proposed. The use of linear stability theory is to obtain the stability criterion that can judge traffic flow stability. In addition, on the basis of nonlinear theory, the time-dependent Ginzburg–Lan (TDGL) equation and the modified Korteweg–de Vries (mKdV) equation near the critical stability point are inferred. The kink–antikink solutions of the above two equations can be used to describe the traffic jam. In the end, numerical simulation is carried out, and the results further demonstrate that the novel model can stabilize traffic flow and eliminate traffic jam better.

Nonlinear analysis of an improved continuum model considering headway change with memory

Considering the effect of headway changes with memory, an improved continuum model of traffic flow is proposed in this paper. By means of linear stability theory, the new model’s linear stability with the effect of headway changes with memory is obtained. Through nonlinear analysis, the KdV–Burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line. Numerical simulation is carried out to study the improved traffic flow model, which explores how the headway changes with memory affected each car’s velocity, density and energy consumption. Numerical results show that when considering the effects of headway changes with memory, the traffic jams can be suppressed efficiently. Furthermore, research results demonstrate that the effect of headway changes with memory can avoid the disadvantage of historical information, which will improve the stability of traffic flow and minimize car energy consumption.

Multiperiod-based timetable optimization for metro transit networks

This paper tackles the train timetable optimization problem for metro transit networks (MTN) in order to enhance the performance of transfer synchronization between different rail lines. Train timetables of connecting lines are adjusted in such a way that train arrivals at transfer stations can be well synchronized. This study particularly focuses on the timetable optimization problem in the transitional period (from peak to off-peak hours or vice versa) during which train headway changes and passenger travel demand varies significantly. A mixed integer nonlinear programming model is proposed to generate an optimal train timetable and maximize the transfer synchronization events. Secondly, an efficient hybrid optimization algorithm based on the Particle Swarm Optimization and Simulated Annealing (PSO-SA) is designed to obtain near-optimal solutions in an efficient way. Meanwhile, in order to demonstrate the effectiveness of the proposed method, the results of numerical example solved by PSO-SA are compared with a branch-and-bound method and other heuristicalgorithms. Finally, a real-world case study based on the Beijing metro network and travel demand is conducted to validate the proposed timetabling model. Computational results demonstrate the effectiveness of adjusting train timetables and the applicability of the developed approach to real-world metro networks.

An improved car-following model considering headway changes with memory

To describe car-following behaviors in complex situations better, increase roadway traffic mobility and minimize cars’ fuel consumptions, the linkage between headway changes with memory and car-following behaviors was explored with the field car-following data by using the gray correlation analysis method, and then an improved car-following model considering headway changes with memory on a single lane was proposed based on the full velocity difference model. Some numerical simulations were carried out by employing the improved car-following model to explore how headway changes with memory affected each car’s velocity, acceleration, headway and fuel consumptions. The research results show that headway changes with memory have significant effects on car-following behaviors and fuel consumptions and that considering headway changes with memory in designing the adaptive cruise control strategy can improve the traffic flow stability and minimize cars’ fuel consumptions.

Tradeoffs between costs and greenhouse gas emissions in the design of urban transit systems

Recent investments in the transit sector to address greenhouse gas emissions have concentrated on purchasing efficient replacement vehicles and inducing mode shift from the private automobile. There has been little focus on the potential of network and operational improvements, such as changes in headways, route spacing, and stop spacing, to reduce transit emissions. Most models of transit system design consider user and agency cost while ignoring emissions and the potential environmental benefit of operational improvements. We use a model to evaluate the user and agency costs as well as greenhouse gas benefit of design and operational improvements to transit systems. We examine how the operational characteristics of urban transit systems affect both costs and greenhouse gas emissions. The research identifies the Pareto frontier for designing an idealized transit network. Modes considered include bus, bus rapid transit (BRT), light rail transit (LRT), and metro (heavy) rail, with cost and emissions parameters appropriate for the United States. Passenger demand follows a many-to-many travel pattern with uniformly distributed origins and destinations. The approaches described could be used to optimize the network design of existing bus service or help to select a mode and design attributes for a new transit system. The results show that BRT provides the lowest cost but not the lowest emissions for our large city scenarios. Bus and LRT systems have low costs and the lowest emissions for our small city scenarios. Relatively large reductions in emissions from the cost-optimal system can be achieved with only minor increases in user travel time.

An Intervehicular Spacing Display for Improved Car-Following Performance

A driver's inability to detect small headway changes and small relative velocities is a primary reason for his poor car-following performance. This can be greatly improved if he is given information?headway and relative velocity?concerning the state of a lead car. This may be provided visually, tactually, or audibly. In the study reported, a control stick with a built-in kinesthetictactile display was tested in a car-following situation. Performances with this display were compared to those obtained when no aiding was used in a similar situation. Sizable reductions in velocity variance and headway variance were obtained for the aided case relative to the unaided case. These were obtained for headways of 23 feet at 30 mi/h and 33 feet at 40 mi/h. Thus, this display can be effectively used at short headways.