Implementing the street-turn strategy by an optimization model

The street-turn option represents a major strategy for the profitability of shipping companies supplying container-based transportation. This option consists in the distribution of trucks delivering loaded containers to import customers, the subsequent allocation of empty containers to export customers and the final dispatch of loaded containers to departure ports. However, the determination of truck routes is a time-consuming activity for shipping companies, because available information can suddenly change while they are making their decisions. In this paper we aim to propose a decision support tool to quickly determine truck routes and implement the street-turn strategy. This tool is based on an optimization model determining the allocation of empty containers between customers and defining truck routes in a post-optimization phase. We compare routes resulting from the proposed model to the decisions of a real shipping company. Early results indicate that this approach represents a promising support for shipping companies in dealing with street-turns. It can significantly reduce distances travelled by trucks and times requested to determine routes.     

Network economies in liner shipping: the role of home markets

This paper deals with the measurement of the network complexity of some selected shipping groups, also identifying the contribution of co-operative agreements among carriers. The empirical investigation is focused on: (i) the analysis of the distribution of the carrying capacity per range; and (ii) the comparison of that capacity with the throughput handled in the port facilities of the group. These variables are interpreted in the light of the impact that alliances have on the geographical wideness of the services supplied by each partner. This factor also allows to depict how the cultural and political origin of shipping lines affects the decision of joining an alliance and the outcomes deriving from such co-operation.     

An assignment model with modified Logit,which obviates enumeration and overlapping problems

One of the main components of stochastic assignment models is the route choice model solved with implicit or explicit path enumeration algorithms. Such models are used both for congested networks within equilibrium or dynamic models and for non-congested networks within static or pseudo-dynamic network loading models. This paper proposes a C-Logit model specification within a Dial algorithm structure for the implicit assignment of network flows. The model and its solution algorithm, called D-C-Logit, combine several positive features found in the literature for choice set generation and choices from a given choice set: generation of a set of alternatives with a selective approach; calculation of the path choice probability in a closed form; simulation of the overlapping effect among alternative paths; computation of just one tree for each origin avoiding explicit path enumeration.This paper has two main objectives: the proposition of a Dial-like algorithm to solve a C-Logit assignment model and application of the algorithm to different networks in order to demonstrate certain properties.     

Driver's braking behavior approaching pedestrian crossings: a parametric duration model of the speed reduction times

The driver's braking behavior while approaching zebra crossings under different safety measures (curb extensions, parking restrictions, and advance yield markings) and without treatment (baseline condition) was examined. The speed reduction time was the variable used to describe the driver's behavior. Forty‐two drivers drove a driving simulator on an urban scenario in which the baseline condition and the safety measures were implemented. The speed reduction time was modeled with a parametric duration model to compare the effects on driver's braking behavior of vehicle dynamic variables and different countermeasures. The parametric accelerated failure time duration model with a Weibull distribution identified that the vehicle dynamic variables and only the countermeasure curb extensions affected, in a statistically significant way, the driver's speed reduction time in response to a pedestrian crossing. This result shows that the driver, because of the improved visibility of the pedestrian allowed by the curb extensions, was able to receive a clear information and better to adapt his approaching speed to yield to the pedestrian, avoiding abrupt maneuvers. This also means a reduction of likelihood of rear‐end collision due to less aggressive braking. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

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.     

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.     

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.     

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.