A data-driven traffic modeling for analyzing the impacts of a freight departure time shift policy

This paper proposes a data-driven transport modeling framework to assess the impact of freight departure time shift policies. We develop and apply the framework around the case of the port of Rotterdam. Container transport demand data and traffic data from the surrounding network are used as inputs. The model is based on a graph convolutional...

Unraveling Gap Selection Process during Discretionary Lane Changing by Vehicle Class

This paper studies and compares the gap selection process of multiple vehicle classes (passenger cars, delivery vans, and trucks) within their discretionary lane changing activities. Given a trajectory or a sequence of gap selection decisions, we aim to predict whether a vehicle will change or keep a lane. For this purpose, we use a large...

Optimizing Road Networks for Automated Vehicles with Dedicated Links, Dedicated Lanes, and Mixed-Traffic Subnetworks

This study focuses on network configurations to accommodate automated vehicles (AVs) on road networks during the transition period to full automation. The literature suggests that dedicated infrastructure for AVs and enhanced infrastructure for mixed traffic (i.e., AVs on the same lanes with conventional vehicles) are the main alternatives so...

Multi-stage optimal design of road networks for automated vehicles with elastic multi-class demand

With the advent of automated vehicles (AVs), new infrastructure planning concepts such as subnetworks of AV-ready roads have been proposed to improve the performance of transportation networks and to promote the adoption of AVs. However, these subnetworks should evolve over time in response to the growing AV demand, which necessitates a multi...

Short-term prediction of outbound truck traffic from the exchange of information in logistics hubs: A case study for the port of Rotterdam

Short-term traffic prediction is an important component of traffic management systems. Around logistics hubs such as seaports, truck flows can have a major impact on the surrounding motorways. Hence, their prediction is important to help manage traffic operations. However, The link between short-term dynamics of logistics activities and the...

Mobility Impacts of Automated Driving and Shared Mobility: Explorative Model and Case Study of the Province of North-Holland

This paper presents a model specifically developed to explore the mobility impacts of connected and automated driving and shared mobility. It is an explorative iterative model that uses an elasticity model for destination choice, a multinomial logit model for mode choice and a network fundamental diagram to assess traffic impacts. To the best...

Mobility Impacts of Automated Driving and Shared Mobility: Explorative Model and Case Study of the Province of North-Holland

This paper presents a model specifically developed to explore the mobility impacts of connected and automated driving and shared mobility. It is an explorative iterative model that uses an elasticity model for destination choice, a multinomial logit model for mode choice and a network fundamental diagram to assess traffic impacts. To the best of...

Assessing the travel impacts of subnetworks for automated driving: An exploratory study

This study explores a network configuration concept for vehicle automation levels 3–4 (according to SAE classifications) in an urban road network having mixed traffic and demonstrates its potential impacts. We assume automated driving will be allowed on a selection of roads. For the remaining roads, manual driving (although supported by...

Quantifying the impact of adverse weather conditions on road network performance

Adverse weather conditions regularly lead to severe congestion and large travel time delays on road networks all over the world. Different climate scenarios indicate that in the future adverse weather conditions are likely to become more frequent, last longer and will be more extreme. Although climate mitigation measures are being taken, it...

Designing Robust Road Networks: A general design method applied to the Netherlands

The Dutch road network is, like many other road networks in the world, congested in the morning and evening peaks. The locations of congestion are quite often the same; this makes it relatively easy to take the delay of this regular congestion into account when planning a trip. However, as a result of disturbances, also unexpectedly large delays...

Algorithm for designing robust road networks: Combining the best of two worlds: modelling and expert knowledge

There is a growing awareness that road networks, especially in major urban areas, are becoming more and more vulnerable to unforeseen disturbances like incidents because of the fact that the level of congestion keeps growing. Therefore, robustness measures have to be taken. In this paper the robust road network design problem is presented as...

Quantifying the full reliability benefits of road network improvements

The vulnerability of road networks: Now and in the future

Transport networks in major urban areas are becoming more and more vulnerable to unforeseen disturbances in transport networks, like incidents. For the near future, we expect an increasing number of incidents with a large impact due to the overall increase of the traffic load. In this paper the hypothesis is tested that, if no measures are taken...

Optimal Redesign of the Dutch Road Network

The Dutch national road network has been developed over several decades. In the past, roads were constructed according to the then current spatial and transportation planning philosophies. Because the existing road network is a result of a long process of successive developments, the question can be asked whether this network is the most...