Understanding the discretionary lane-changing behaviour in the connected environment.

Discretionary lane-changing (DLC) is one of the complex driving manoeuvres that requires surrounding traffic information for efficient and safe manoeuvring. The connected environment not only provides such information but also increases situational awareness, which is useful for DLC decision-making. However, the literature is devoid of any concrete evidence of such impact of the connected environment on DLC decision-making. As such, this paper analyses the effects of the connected environment on DLC behaviour. Seventy-eight participants from a diverse background performed DLCs in randomised driving conditions using the CARRS-Q advanced driving simulator. These driving conditions are: baseline (without driving messages), connected environment with perfect communication (fully functioning and uninterrupted supply of driving messages), and connected environment with communication delay (impaired communication). Various key driving behaviour indicators are analysed and compared using a linear mixed model. To analyse the effects of the connected environment on DLC decision-making, two Generalised Estimation Equation (GEE) models are developed for gap acceptance and DLC duration. In addition, a Weibull accelerated failure time hazard-based duration model is developed to investigate the impact of the connected environment on safety associated with DLC manoeuvres. We find that drivers in the connected environment have a larger spacing, larger lead and lag gaps, a longer DLC duration, and a lower acceleration noise compared to the baseline condition. The GEE model on gap acceptance reveals that drivers tend to select relatively bigger gap sizes when the connected environment offers them the subsequent gap information. Similarly, the GEE model for DLC duration suggests that the connected environment increases DLC durations by 2.22 s and 2.11 s in perfect communication and communication delay driving conditions, respectively. Finally, the hazard-based duration model provides insights into the probability of avoiding a lane-changing collision, and indicates that the probability of a lane-changing collision is less in the connected environment driving conditions than in the baseline scenario. Overall, the connected environment improves the DLC driving behaviour and enhances traffic safety.

Searching for empirical evidence on traffic equilibrium.

Cities around the world are inundated by cars and suffer traffic congestion that results in excess delays, reduced safety and environmental pollution. The interplay between road infrastructure and travel choices defines the level and the spatio-temporal extent of congestion. Given the existing infrastructure, understanding how the route choice decisions are made and how travellers interact with each other is a crucial first step in mitigating traffic congestion. This is a problem with fundamental importance, as it has implications for other limited supply systems where agents compete for resources and reach an equilibrium. Here, we observe the route choice decisions and the traffic conditions through an extensive data set of GPS trajectories. We compare the actual paths followed by travellers to those implied by equilibrium conditions (i) at a microscopic scale, where we focus on individual path similarities, and (ii) at a macroscopic scale, where we perform network-level comparison of the traffic loads. We present that non-cooperative or selfish equilibrium replicates the actual traffic (to a certain extent) at the macroscopic scale, while the majority of individual decisions cannot be reproduced by neither selfish nor cooperative equilibrium models.

Modeling work zone crash frequency by quantifying measurement errors in work zone length.

Work zones are temporary traffic control zones that can potentially cause safety problems. Maintaining safety, while implementing necessary changes on roadways, is an important challenge traffic engineers and researchers have to confront. In this study, the risk factors in work zone safety evaluation were identified through the estimation of a crash frequency (CF) model. Measurement errors in explanatory variables of a CF model can lead to unreliable estimates of certain parameters. Among these, work zone length raises a major concern in this analysis because it may change as the construction schedule progresses generally without being properly documented. This paper proposes an improved modeling and estimation approach that involves the use of a measurement error (ME) model integrated with the traditional negative binomial (NB) model. The proposed approach was compared with the traditional NB approach. Both models were estimated using a large dataset that consists of 60 work zones in New Jersey. Results showed that the proposed improved approach outperformed the traditional approach in terms of goodness-of-fit statistics. Moreover it is shown that the use of the traditional NB approach in this context can lead to the overestimation of the effect of work zone length on the crash occurrence.