Impacts of automated vehicles on travel behaviour and land use: an international review of modelling studies

ABSTRACT

Automated vehicles (AVs) could completely change mobility in the coming years and decades. As AVs are still under development and gathering empirical data for further analysis is not yet possible, existing studies mainly applied models and simulations to assess their impact. This paper provides a comprehensive review of modelling studies investigating the impacts of AVs on travel behaviour and land use. It shows that AVs are mostly found to increase vehicle miles travelled and reduce public transport and slow modes share. This particularly applies to private AVs, which are also leading to a more dispersed urban growth pattern. Shared automated vehicle fleets, conversely, could have positive impacts, including reducing the overall number of vehicles and parking spaces. Moreover, if it is assumed that automation would make the public transport system more efficient, AVs could lead to a favouring of urbanisation processes. However, results are very sensitive to model assumptions which are still very uncertain (e.g. the perception of time in AVs) and more research to gain further insight should have priority in future research as well as the development of the models and their further adaptation to AVs.     

Software-in-the-loop development and validation of a Cornering Brake Control logic

In this article, a logic for vehicle dynamics control during partial braking while turning a corner is presented, which only requires knowledge of the instantaneous speed of the four wheels. For this reason, the proposed control algorithm can be adopted on all ABS equipped cars. A scheme of the simulation program for logic validation is described, which is constituted by a loop of software models of the principal vehicle subsystems which are singly illustrated. The proposed logic has been tested both in closed and open-loop maneuvers. The results are provided in the form of time histories of the principal analyzed quantities. The analysis of the results confirms the goodness of the proposed control strategy.     

A Topological Method to Choose Optimal Solutions after Solving the Multi-criteria Urban Road Network Design Problem

The paper proposes and applies a method for systematically sorting and reducing the number of different possible solutions to a network design problem (NDP). This is achieved first by defining a topological similarity measurement and then by applying cluster analysis. The NDP can be derived from the scientific literature. In general, the method consists of some models and subsequent algorithms that generate different solutions (enumerative, branch and bound, genetic, expert panel, ...) and evaluate for each solution an objective function (with deterministic or stochastic network assignment and with elastic or inelastic demand). The NDP, mainly in urban areas, needs multi-criteria evaluation and in each case a large set of non-dominated solutions is generated. In this paper, in order to select solutions and identify latent optimal network layouts, cluster analysis is carried out. The methodology utilises a “cluster” formation in relation to the solution topology and a “best” (representative) solutions extraction in relation to the criteria values. It can be utilised after solving the existing multi-criteria NDP and in other network problems, where the best solutions (for global or local network layouts) are extracted (with respect to the network topology) from a large set. The method is applied in a test system and on different real networks in two Italian towns, in order to analyse the goodness of the solution algorithm and assess its possible application to different networks.     

Automated real-time railway traffic control: an experimental analysis of reliability,resilience and robustness

Railway transportation provides sustainable, fast and safe transport. Its attractiveness is linked to a broad concept of service reliability: the capability to adhere to a timetable in the presence of delays perturbing traffic. To counter these phenomena, real-time rescheduling can be used, changing train orders and times, according to rules of thumb, or mathematical optimization models, minimizing delays or maximizing punctuality. In the literature, different indices of robustness, reliability and resilience are defined for railway traffic. We review and evaluate these indices applied to railway traffic control, comparing optimal rescheduling approaches such as Open Loop and Closed Loop control, to a typical First-Come-First-Served dispatching rule, and following the timetable (no-action). This experimental analysis clarifies the benefits of automated traffic control for infrastructure managers, railway operators and passengers. The timetable order, normally used in assessing a-priori reliability, systematically overestimates unreliability of operations that can be reduced by real-time control.     

Tracking a system of shared autonomous vehicles across the Austin,Texas network using agent-based simulation

This study provides a large-scale micro-simulation of transportation patterns in a metropolitan area when relying on a system of shared autonomous vehicles (SAVs). The six-county region of Austin, Texas is used for its land development patterns, demographics, networks, and trip tables. The agent-based MATSim toolkit allows modelers to track individual travelers and individual vehicles, with great temporal and spatial detail. MATSim’s algorithms help improve individual travel plans (by changing tour and trip start times, destinations, modes, and routes). Here, the SAV mode requests were simulated through a stochastic process for four possible fare levels: $0.50, $0.75, $1, and $1.25 per trip-mile. These fares resulted in mode splits of 50.9, 12.9, 10.5, and 9.2% of the region’s person-trips, respectively. Mode choice results show longer-distance travelers preferring SAVs to private, human-driven vehicles (HVs)—thanks to the reduced burden of SAV travel (since one does not have to drive the vehicle). For travelers whose households do not own an HV, SAVs (rather than transit, walking and biking) appear preferable for trips under 10 miles, which is the majority of those travelers’ trip-making. It may be difficult for traditional transit services and operators to survive once SAVs become available in regions like Austin, where dedicated rail lines and bus lanes are few. Simulation of SAV fleet operations suggest that higher fare rates allow for greater vehicle replacement (ranging from 5.6 to 7.7 HVs per SAV, assuming that the average SAV serves 17–20 person-trips per day); when fares rise, travel demands shift away from longer trip distances. Empty vehicle miles traveled by the fleet of SAVs ranged from 7.8 to 14.2%, across the scenarios in this study. Implications of mobility and sustainability benefits of SAVs are also discussed in the paper.     

Optimal management of human resources in transhipment container ports

Human resources allocation plays a key role in transhipment maritime container terminals to achieve high levels of productivity and provide high quality services to shipping companies. The deep interest of container terminals in this issue can be supported by optimization methods. In this work, an optimization model is proposed to determine the optimal daily allocation of crane operators and trailer drivers. Different requirements are taken into account for permanent staff, external workers and personnel shortfall. Since workforce undermanning is a crucial factor for both shipping companies and container terminals, we aim to show that personnel shortfalls and operation delays can be significantly reduced if the model encompasses a longer-than-1-day planning horizon in a rolling horizon fashion.     

Estimating demand variables of maritime container transport: An aggregate procedure for the Mediterranean area

Demand variables of maritime container transport (throughput, transhipment and origin–destination flows) may be estimated with freight demand models. As their parameters generally vary both in time and space, models may not be transferable to geographical areas and time periods differing from that for which they are calibrated.     

A model system for the ex-ante assessment of city logistics measures

This paper proposes a model system developed in order to support ex-ante assessment of city logistics measures. The model system allows us to simulate the choices of each decision-maker involved in the urban freight transport and logistics and to investigate how the policies and the following measures can influence her/his choices.The model system is an open architecture and consists of two levels: commodity and vehicle. The commodity level allows us to analyse the attraction and acquisition movements taking into account the effects due to city logistics policy implementation affecting the end-consumer and retailer/wholesaler/producer (restocker) choices. The freight sold in each urban shop (or in general urban business) is estimated starting from consumption demand and, then, the restocker’s choices for restocking are analysed in depth. The vehicle level focuses on the restocking process and the links between retailer and wholesaler/producer operating in the study area. This level allows us to investigate the impacts of implementing city logistics measures on journey time, timing and path used for restocking the urban retail businesses.