Extending Adaptive Cruise Control to Adaptive Driving Strategies

Abstract

An adaptive cruise control (ACC) strategy is presented in which acceleration characteristics, that is, driving styles, automatically adapt to different traffic situations. The three components of the concept are the ACC itself, implemented in the form of a car-following model; an algorithm for the automatic real-time detection of the traffic situation based on local information; and a driving strategy matrix to adapt the driving characteristics–that is, the parameters of the ACC controller–to the traffic conditions. As an option, intervehicle and roadside-to-car communication can be used to improve the accuracy for determining the local traffic states. The complete concept was simulated microscopically on a road section with an on-ramp bottleneck by using real loop-detector data for an afternoon peak period as input for the upstream boundary. A small percentage of traffic-adaptive ACC vehicles, a relatively modest local change in the maximum free flow, improves traffic stability and performance significantly. Although the traffic congestion in the reference case was completely eliminated when a proportion of 25% of ACC vehicles was simulated, travel times for the drivers were reduced in a relevant way for much lower penetration rates. The presented results are largely independent of details of the model, the boundary conditions, and the type of road inhomogeneity.

Effects of desired speeds for queuing and delay on single-lane road segments

“…This is verified using the IDM. The simulations only included passenger cars, all with a length of 4.5 m. All cars were controlled by an IDM with parameter values according to table 2 in Kesting et al (2007), which e.g. imply a jam distance of 2 m, a desired following time gap of 1.5 s, a maximum acceleration of 1.4 m/s 2 and a desired deceleration of 2 m/s 2 .…”

Vehicle Trajectory Effects of Adaptive Cruise Control

“…Numerous traffic simulation studies of ACC can also be found in the literature (Minderhoud and Bovy, 1999;Hoogendoorn and Minderhoud, 2002;Davis, 2004Davis, , 2007van Arem et al, 2006;Kesting et al, 2007aKesting et al, , 2007b. Traffic simulation has traditionally been applied for quality-of-service analysis of proposed changes in traffic management or road network design.…”

“…In the simulations, parameter values presented by Kesting et al (2007a) have been used for all vehicles, i. e. T d = 1.5 s, a 0 = 1.4 m/s 2 , b = 2 m/s 2 and s 0 = 2 m. For standard vehicles, limited perception and reaction capabilities and anticipation to compensate for these limitations have been taken into account by extending the IDM model with the Human Driver Model (HDM) presented by Treiber et al (2006). HDM is a meta-model that allows modelling of delayed reactions, perception inaccuracies and anticipation of the future traffic situation.…”

“…Several driver behavioural studies of driving with ACC have been performed (Dragutinovic et al, 2005;Saad et al, 2004). ACC has also been the subject of many traffic simulation experiments (Minderhoud and Bovy, 1999;Hoogendoorn and Minderhoud, 2002;Davis, 2004Davis, , 2007van Arem et al, 2006;Kesting et al, 2007aKesting et al, , 2007b. Most traffic simulation studies of ACC impacts have focused on macroscopic capacity and quality-of-service impacts of the distance keeping functionality of the ACC.…”

Nonlinear dynamics of autonomous vehicles with limits on acceleration

“…The reader is referred to several good references on traffic and ACC [12][13][14][15][16]. However, I will describe the salient developments as they relate to the present work.…”