Journal of Transportation Engineering, Part A: Systems

This paper presents a probability distribution model of vehicles’ travel time index (TTI) in urban road segments that depicts traffic flow dispersion. Compared with traditional models, it can depict traffic flow dispersion with a uniform model under conditions of different road speeds or road lengths. Based on it, a dynamic model that depicts how the TTI distribution parameters vary with speed of road segment is proposed. Furthermore, parameters of the dynamic model are used to construct a characteristic vector to reveal a new inherent feature of road segments. The tests of goodness of fit for the two proposed models were carried out with data collected from 66,000 floating cars. The test area covered 40,400 urban road segments in the urban area of Beijing. Test results showed that more than 98% of the tested bins accepted the proposed TTI probability distribution model, and more than 90% of the tested road segments accepted the proposed dynamic model. The proposed models would be applied in traffic simulation, congestion forecast, signal control, and other relevant fields in the future.

Railway transportation has a significant advantage compared to other modes of transportation due to its high level of safety, significant capacity, and environmentally friendly nature, leading to an ever increasing expansion of passenger numbers. To maintain a high safety level and utilize the maximum capacity of this system, maintenance management of railroad is of crucial importance. The most costly part of railroad management is related to track maintenance, and the most crucial parameter of tracks is their geometry. The main objective of this research is to develop a railroad management system to both minimize track-maintenance costs and sustain high track geometrical quality. First, a track-quality database for a sufficient period of time is acquired. Having applied this database, a track degradation model is developed. Cost and improvement models associated with different track-maintenance actions are determined. Using degradation, cost, and improvement models, maintenance planning is conducted through optimum selection of tracks, appropriate time, and suitable maintenance actions in order to minimize cost and maximize the track geometrical quality. This selection is a combinatorial problem with a large number of feasible solutions, which cannot be solved using conventional algorithms. A heuristic method such as the genetic algorithm is proposed herein and utilized as a powerful tool to solve this problem.

Midblock crosswalks are installed mainly at locations with heavy pedestrian traffic to increase the accessibility of points along the streets to pedestrians. However, midblock crosswalks may cause additional delays for vehicles. This paper presents an integrated design method for midblock crosswalks that balances the trade-off between the efficiency of vehicle operation and pedestrian crossing by making full use of the vehicular red time at the downstream intersection. The method combines location selection and signal timing in a unified optimization model that is formulated as a multiobjective linear programming problem. The Pareto frontier of the proposed model is obtained by iterating all possible combinations of the weights of the two objectives. For each combination of weights, the optimization problem becomes a single-objective mixed-integer linear programming problem that can be solved with the standard branch-and-bound technique. The results of extensive numerical analyses and case studies demonstrate the effectiveness of the proposed model and indicate its promising application in providing additional crosswalks for pedestrians while only slightly impacting vehicular operations.

The current highway geometric design guide provides a method for calculating intersection sight distance at two-way stop-controlled intersections by assuming that a departing driver on the minor road that would start from a resting position needs a fixed-time gap for departing the intersection regardless of the design speed or the grade on the major road. However, departing drivers may fail to perceive the speeds of the approaching vehicles on the major road in order to judge the available departure gap and decide whether or not to accept it. In this paper, a novel method is introduced to determine intersection sight distance requirements for two-way stop-controlled intersections based on actual drivers’ behavior and vehicle capabilities. The method incorporates acceleration profiles for vehicles starting from rest, which were developed based on field data collected using global positioning system (GPS) data loggers that recorded the positions (latitudes, longitudes, and altitudes) and the instantaneous speeds of different vehicle types piloted by different drivers at 1 s intervals. Design tables and an application example are presented to help designers select the required intersection sight distance based on the design speed and the grade on the major road.