Capacity Gains of Splitting Cross-Traffic into Multiple Sub-Streams

Traffic flow might be limited by cross-traffic which has priority. A typical example of such a situation is a location where cyclists or pedestrians cross a stream of car traffic. Splitting the cross-traffic into two separate sub-streams (for instance left?right and right?left) can increase the capacity of the main stream. This is because it is...

A novel method about the representation and discrimination of traffic state

The representation and discrimination of various traffic states play an essential role in solving traffic accidents and congestion as the foundation of traffic state prediction. However, the existing representation of the traffic state usually only considers the road congestion layer and divides the traffic state into congested and unblocked....

Voronoi densities for bicylists: adaptation for finite object size and speed

Density is one of the most relevant variables in a traffic flow description. For objects in 2 dimensions, density can be determined by the space that is allocated to each of the objects. This paper introduces a new way of computing the space available for a bicyclist, accounting for speed and accounting for the non-zero size of a bicycle. This...

Empirical MFDs using Google Traffic Data

<br/>The Macroscopic Fundamental Diagram (MFD) describes the relation between accumulation and speed in a zone. While theoretically expected, empirical validations have been done with limited numbers of floating car (e.g., taxi) data, and loop detectors. This paper will verify existence, shape and crispness of the MFD using Floating Car Data ...

Multi-class traffic flow on a partially space-shared road

Scarce urban space makes urban streets have to be partly shared by cars and cyclists. Traffic flow can be considerably influenced by cyclists, which are comparatively slower than cars. The fundamental diagram (FD) can change greatly, correlating to bike lane length and the cyclist flow. Models for the traffic dynamics on the space-shared streets...

Evaluation and modelling of the traffic flow effects of truck platooning

With automated and cooperative driving making its breakthrough, and related systems in fast development, their future influence and impact on roads and traffic may be extensive. Truck platooning is such an application that relies on the development of Cooperative Adaptive Cruise Control (CACC) and is said to be practice ready. While the main...

Capacity drop through reaction times in heterogeneous traffic

The capacity drop forms a major reason why the prevention of congestion is targeted by traffic management, as lower capacities are detrimental to traffic throughput. Various reasons describing the dynamics behind the capacity have been described, however one of these, reaction times, has had less explicit attention when modelling on a...

Improving traffic management through consideration of uncertainty and stochastics in traffic flow

In a bid to cost-effectively tackle congestion, traffic management is often seen as a key option to utilise road capacity. Prior to the application of traffic management measures, a-priori analysis allows the effectiveness of measures to be judged and where necessary adapted. However, current approaches do this without considering the effects...

A geometric Brownian motion car-following model: towards a better understanding of capacity drop

Traffic flow downstream of the congestion is generally lower than the pre-queue capacity. This phenomenon is called the capacity drop. Recent empirical observations show a positive relationship between the speed in congestion and the queue discharge rate. Literature indicates that variations in driver behaviors can account for the capacity drop....

A kinematic wave model in Lagrangian coordinates incorporating capacity drop: Application to homogeneous road stretches and discontinuities

On freeways, congestion always leads to capacity drop. This means the queue discharge rate is lower than the pre-queue capacity. Our recent research findings indicate that the queue discharge rate increases with the speed in congestion, that is the capacity drop is strongly correlated with the congestion state. Incorporating this varying...