This paper describes a location specific cell transmission model of freeway traffic based on the observed variability of fundamental diagrams both along and across freeway segments. This model extends the original cell transmission model （CTM） mechanism by defining various shapes of fundamental diagrams to reproduce more complex traffic phenomena, including capacity drops, lane-by-lane variations, nonho- mogeneous wave propagation velocities, and temporal lags. A field test on a Canadian freeway was used to demonstrate the validity of the location specific CTM. The simulated spatio-temporal evolutions of traffic flow show that the model can be used to describe the traffic dynamics near bottlenecks more precisely than the original model.
Two characteristics of Chinese mixed traffic invalidate the conventional queuing delay estimates for western countries. First, the driving characteristics of Chinese drivers lead to different delays even though the other conditions are the same. Second, urban traffic flow in China is often hindered by pedestrians at intersections, such that imported intelligent traffic control systems do not work appropriately. Typical delay estimates for Chinese conditions were obtained from data for over 500 vehicle queues in Beijing collected using charge coupled device （CCD） cameras. The results show that the delays mainly depend on the pro- portion and positions of heavy vehicles in the queue, as well as the start-up situations （with or without interference）. A simplified delay estimation model considers vehicle types and positions that compares well with the observed traffic delays.
The modeling of headway/spacing between two consecutive vehicles in a queue has many applications in traffic flow theory and transport practice. Most known approaches have only studied vehicles on freeways. This paper presents a model for the spacing distribution of queuing vehicles at a signalized junction based on random-matrix theory. The spacing distribution of a Gaussian symplectic ensemble （GSE） fits well with recently measured spacing distribution data. These results are also compared with measured spacing distribution observed for the car parking problem. Vehicle stationary queuing and vehicle parking have different spacing distributions due to different driving patterns.
