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Mode choice behaviour is often modelled by discrete choice models, in which the utility of each mode is characterized by mode-specific parameters reflecting how strongly the utility of that mode depends on attributes such as travel speed and cost, and a mode-specific constant value. For new modes, the mode-specific parameters and the constant in the utility function of discrete choice models are not known and are difficult to estimate on the basis of stated preferences data/choice experiments and cannot be estimated on the basis of revealed preference data. This paper demonstrates how revealed preference data can be used to estimate a discrete mode choice model without using mode-specific constants and mode-specific parameters. This establishes a method that can be used to analyze any new mode using revealed preference data and discrete choice models and is demonstrated using the OViN 2017 dataset with trips throughout the Netherlands using a multinomial and nested logit model. This results in a utility function without any alternative specific constants or parameters, with a rho-squared of 0.828 and an accuracy of 0.758. The parameters from this model are used to calculate the future modal split of shared autonomous vehicles and electric steps, leading to a potential modal split range of 24-30% and 37-44% when using a multinomial logit model, and 15-20% and 33-40% when using a nested logit model. An overestimation of the future modal split occurs due to the partial similarities between different transport modes when using a multinomial logit model. It can therefore be concluded that a nested logit model is better suited for estimating the potential modal split of a future mode than a multinomial logit model. To the authors' knowledge, this is the first time that the future modal split of shared autonomous vehicles and electric steps has been calculated using revealed preference data from existing modes using an unlabelled mode modelling approach., Author(s): Gijsbert Koen de Clercq (corresponding author) [1]; Arjan van Binsbergen [1]; Bart van Arem [1]; Maaike Snelder [1] 1. Introduction In the last decade, numerous mobility systems, such as [...]

In this paper, we study the deployment potential of automated minibuses (AmBs) on the first-mile part of public transport (PT) trips or short (sub)urban commutes by comparing 'regular' (fixed route and fixed schedule) and 'flexible' (door-to-door and on-demand) service types. For reaching that goal, we run a stated choice experiment in the Netherlands. The participants have assessed the referred two AmB alternatives compared to their current travel mode (car, PT, or active modes (AM) - bicycle and walking) used as the main mode for unimodal travellers or as access travel mode to transit lines for multimodal travellers. The results of a joint mixed logit model estimation based on data obtained from Dutch travellers show that there are similarities and differences in the preferences for the AmBs service type within and between the segments of travellers (car, PT, and AM) and that these are mostly in instrumental variables (cost and time) and attitudes. Current PT users prefer the flexible service to regular service based on their perception of in-vehicle travel time and waiting time, while current users of car and AM do not show a difference in preference between the two services concerning these variables. Moreover, their perception of in-vehicle travel time and waiting time is not significantly different from PT users' perception of those variables in the regular service. This may mean that for non-PT users (car and AM), AmB's flexibility of door-to-door transport is not seen as offering a significant advantage over what they think about public transport. When looking at the preferences of potential users explained by underlying psychological factors, we conclude that a positive attitude towards riding in AmBs is a significant factor in all three segments of travellers. Trust, usefulness, and enjoyment in using AmBs are important prerequisites for car and PT users to choose either service type. The experience with technology positively influences the preferences of current PT users for both AmB services., Author(s): Maryna Öztürker (corresponding author) [1]; Gonçalo Homem de Almeida Correia [1]; Arthur Scheltes [2]; Marie-José Olde Kalter [2]; Bart van Arem [1] 1. Introduction In the last several decades, [...]

Control measures at merging locations aimed at either the mainline traffic or on-ramp traffic do not lead to a fairness in the distribution of total delay across the two streams. This paper presents a control strategy of combining a lane change control with a ramp metering system at motorway merges. The control strategy presents the opportunity to control the delays incurred at the two traffic streams of the merge. An optimization problem is formulated for a multilane motorway with an on-ramp with the aim to minimize the total travel time of the system. The proposed strategy is tested using an incentive-based lane-specific traffic flow model. Results revealed a 17% reduction in the total travel time due to the proposed strategy. Moreover, it was shown that the distribution of delays over the mainline and on-ramp could be controlled via the proposed strategy. The performance of the combined control was also compared to the individual control measures. It was observed that the individual control measures (lane change only and ramp metering only) lead to high delays on either the mainline or on-ramp compared to the combined control, where the balance between the delay for the drivers on the mainline and on-ramp could be regulated. The combined lane change and ramp metering control presents opportunities for the road authorities to manage the total delay distribution across the two traffic streams., Author(s): Hari Hara Sharan Nagalur Subraveti (corresponding author) [1,2]; Victor L. Knoop [1]; Bart van Arem [1] 1. Introduction Motorway merging sections are recurrent bottlenecks prone to congestion due to [...]

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 far. We utilize both alternatives and propose a unified mathematical framework for optimizing road networks for AVs by simultaneous deployment of AV-ready subnetworks for mixed traffic, dedicated AV links, and dedicated AV lanes. We model the problem as a bilevel network design problem where the upper level represents road infrastructure adjustment decisions to deploy these concepts and the lower level includes a network equilibrium model representing the flows as a result of the travelers' response to new network topologies. An efficient heuristic solution method is introduced to solve the formulated problem and find coherent network topologies. Applicability of the model on real road networks is demonstrated using a large-scale case study of the Amsterdam metropolitan region. Our results indicate that for low AV market penetration rates (MPRs), AV-ready subnetworks, which accommodate AVs in mixed traffic, are the most efficient configuration. However, after 30% MPR, dedicated AV lanes prove to be more beneficial. Additionally, road types can dictate the viable deployment plan for certain parts of road networks. These insights can be used to guide planners in developing their strategies regarding road network infrastructure during the transition period to full automation., Author(s): Bahman Madadi (corresponding author) [1]; Rob Van Nes [1]; Maaike Snelder [1,2]; Bart Van Arem [1] 1. Introduction Automated vehicles (AVs) are expected to deliver various benefits to transport [...]

Realistic microscopic traffic simulation is essential for prospective evaluation of the potential impacts of new traffic control strategies. Freeway corridors with interacting bottlenecks and dedicated lanes generate complex traffic flow phenomena and congestion patterns, which are difficult to reproduce with existing microscopic simulation models. This paper discusses two alternative driving behavior models that are capable of modeling freeways with multiple bottlenecks and dedicated lanes over an extended period with varying demand levels. The models have been calibrated using archived data from a complicated 13mile long section of the northbound SR99 freeway near Sacramento, California, for an 8-hour time period in which the traffic fluctuated from free-flow to congested conditions. The corridor includes multiple bottlenecks, multiple entry and exit ramps, and an HOV lane. Calibration results show extremely good agreement between field data and model predictions. The models have been cross-validated and produced similar macroscopic traffic performance. The main behavior that should be captured for successful modeling of such a complex corridor includes the anticipative and cooperative driver behavior near merges, lane preference in presence of dedicated lanes, and variations in desired headway along the corridor., 1. Introduction Microscopic traffic simulation is a viable and cost effective approach for prospectively evaluating the potential impacts of traffic control strategies and shifts in demand patterns. To achieve this, [...]

Automated vehicles are designed to free drivers from driving tasks and are expected to improve traffic safety and efficiency when connected via vehicle-to-vehicle communication, that is, connected automated vehicles (CAVs). The time delays and model uncertainties in vehicle control systems pose challenges for automated driving in real world. Ignoring them may render the performance of cooperative driving systems unsatisfactory or even unstable. This paper aims to design a robust and flexible platooning control strategy for CAVs. A centralized control method is presented, where the leader of a CAV platoon collects information from followers, computes the desired accelerations of all controlled vehicles, and broadcasts the desired accelerations to followers. The robust platooning is formulated as a Min-Max Model Predictive Control (MM-MPC) problem, where optimal accelerations are generated to minimize the cost function under the worst case, where the worst case is taken over the possible models. The proposed method is flexible in such a way that it can be applied to both homogeneous platoon and heterogeneous platoon with mixed human-driven and automated controlled vehicles. A third-order linear vehicle model with fixed feedback delay and stochastic actuator lag is used to predict the platoon behavior. Actuator lag is assumed to vary randomly with unknown distributions but a known upper bound. The controller regulates platoon accelerations over a time horizon to minimize a cost function representing driving safety, efficiency, and ride comfort, subject to speed limits, plausible acceleration range, and minimal net spacing. The designed strategy is tested by simulating homogeneous and heterogeneous platoons in a number of typical and extreme scenarios to assess the system stability and performance. The test results demonstrate that the designed control strategy for CAV can ensure the robustness of stability and performance against model uncertainties and feedback delay and outperforms the deterministic MPC based platooning control., 1. Introduction Today's traffic systems are facing serious congestion [1]. Automated vehicles using advanced sensing, communication, and control technologies have the potential to increase road capacity and improve traffic operations [...]

1. Introduction 1.1. The Rise of Driverless Vehicles. Driverless vehicles are currently being developed in a number of commercial and research projects worldwide [1, 2]. Shuttles that function as shared [...], Shuttles that operate without an onboard driver are currently being developed and tested in various projects worldwide. However, there is a paucity of knowledge on the determinants of acceptance of driverless shuttles in large cross-national samples. In the present study, we surveyed 10,000 respondents on the acceptance of driverless vehicles and sociodemographic characteristics, using a 94-item online questionnaire. After data filtering, data of 7,755 respondents from 116 countries were retained. Respondents reported that they would enjoy taking a ride in a driverless vehicle (mean = 4.90 on a scale from 1 = disagree strongly to 6 = agree strongly). We further found that the scores on the questionnaire items were most appropriately explained through a general acceptance component, which had loadings of about 0.7 for items pertaining to the usefulness of driverless vehicles and loadings between 0.5 and 0.6 for items concerning the intention to use, ease of use, pleasure, and trust in driverless vehicles, as well as knowledge of mobility-related developments. Additional components were identified as thrill seeking, wanting to be in control manually, supporting a car-free environment, and being comfortable with technology. Correlations between sociodemographic characteristics and general acceptance scores were small (