A new scenario based approach for designing driver support systems applied to the design of a lane change support system

Designing a new driver support system that meets the expectations of drivers is a difficult and time-consuming process. Despite the availability of various types of design support, it has essentially remained a process in which designers are forced to make assumptions about what other people want. This paper presents a new approach for determining users’ preferences and finding the best compromise between those preferences when designing a new driver support system. Using scenarios, virtual reality simulation, and gaming principles, the new approach gives users a pro-active role in the design process. To evaluate the new approach, it was applied to the design of a lane change support system. This resulted in a hierarchy of information that is a detailed, consistent and reliable image of users’ preferences. By combining this hierarchy with a manufacturing and marketing constraint, the design specification of a lane change support system was deduced. One of the many findings was that a lane change support system should be modular and that modules for the left side should be different from modules for the right side of the vehicle. The paper concludes with reasoning why the new approach offers added value for the design of driver support systems.     

Developing freeway lane‐changing support systems using artificial neural networks

Lane‐changing involves many concerns about safety and efficiency which makes it one of the most difficult tasks of driving. It is indeed quite personal since drivers operate vehicles according to their integrated perception of comprehensive circumstances rather than individual rules. A lane‐changing decision support model is developed in this study using artificial neural networks (ANN). The advantages of the ANN approach lie in the learning capability. Due to its nature, an ANN model can consolidate various kinds of information surrounding the vehicle for the drivers and generate reliable results to help control vehicles. It then becomes a useful mechanism to assist drivers in judging current situations and making the right decisions. Several preliminary validations and comparisons are conducted with the field survey data. It is confirmed that the ANN model mimics traffic characteristics more accurately than conventional methods. This product would expedite the implementation of relevant applications in the intelligent transportation systems context. In particular, the ANN model can be adapted to individual driver characteristics. This reveals practical feasibility and significant market potential for customized in‐vehicle equipment.     

Improved waveform‐feature‐based vehicle classification using a single‐point magnetic sensor

Vehicle classification systems have important roles in applications related to real‐time traffic management. They also provide essential data and necessary information for traffic planning, pavement design, and maintenance. Among various classification techniques, the length‐based classification technique is widely used at present. However, the undesirable speed estimates provided by conventional data aggregation make it impossible to collect reliable length data from a single‐point sensor during real‐time operations. In this paper, an innovative approach of vehicle classification will be proposed, which achieved very satisfactory results on a single‐point sensor. This method has two essential parts. The first concerns with the procedure of smart feature extraction and selection according to the proposed filter–filter–wrapper model. The model of filter–filter–wrapper is adopted to make an evaluation on the extracted feature subsets. Meanwhile, the model will determine a nonredundant feature subset, which can make a complete reflection on the differences of various types of vehicles. In the second part, an algorithm for vehicle classification according to the theoretical basis of clustering support vector machines (C‐SVMs) was established with the selected optimal feature subset. The paper also uses particle swarm optimization (PSO), with the purpose of searching for an optimal kernel parameter and the slack penalty parameter in C‐SVMs. A total of 460 samples were tested through cross validation, and the result turned out that the classification accuracy was over 99%. In summary, the test results demonstrated that our vehicle classification method could enhance the efficiency of machine‐learning‐based data mining and the accuracy of vehicle classification. Copyright © 2014 John Wiley & Sons, Ltd.     

Optimizing route choice for lowest fuel consumption – Potential effects of a new driver support tool

Today, driver support tools intended to increase traffic safety, provide the driver with convenient information and guidance, or save time are becoming more common. However, few systems have the primary aim of reducing the environmental effects of driving. The aim of this project was to estimate the potential for reducing fuel consumption and thus the emission of CO₂ through a navigation system where optimization of route choice is based on the lowest total fuel consumption (instead of the traditional shortest time or distance), further the supplementary effect if such navigation support could take into account real-time information about traffic disturbance events from probe vehicles running in the street network. The analysis was based on a large database of real traffic driving patterns connected to the street network in the city of Lund, Sweden. Based on 15 437 cases, the fuel consumption factor for 22 street classes, at peak and off-peak hours, was estimated for three types of cars using two mechanistic emission models. Each segment in the street network was, on a digitized map, attributed an average fuel consumption for peak and off-peak hours based on its street class and traffic flow conditions. To evaluate the potential of a fuel-saving navigation system the routes of 109 real journeys longer than 5 min were extracted from the database. Using Esri’s external program ArcGIS, Arcview and the external module Network Analysis, the most fuel-economic route was extracted and compared with the original route, as well as routes extracted from criterions concerning shortest time and shortest distance. The potential for further benefit when the system employed real-time data concerning the traffic situation through 120 virtual probe vehicles running in the street network was also examined. It was found that for 46% of trips in Lund the drivers spontaneous choice of route was not the most fuel-efficient. These trips could save, on average, 8.2% fuel by using a fuel-optimized navigation system. This corresponds to a 4% fuel reduction for all journeys in Lund. Concerning the potential for real-time information from probe vehicles, it was found that the frequency of disturbed segments in Lund was very low, and thus so was the potential fuel-saving. However, a methodology is presented that structures the steps required in analyzing such a system. It is concluded that real-time traffic information has the potential for fuel-saving in more congested areas if a sufficiently large proportion of the disturbance events can be identified and reported in real-time.     

Context-dependent influence of road attributes and pricing policies on route choice behavior of truck drivers: results of a conjoint choice experiment

In this paper, we report the results of a stated choice experiment, which was conducted to examine truck drivers?? route choice behavior. Of particular interest are the questions (i) what is the relative importance of road accessibility considerations via-a-vis traditional factors influencing route choice behavior, (ii) what are the influences of particular personal and situational variables on the evaluation of route attributes, (iii) how sensitive are truck drivers for possible pricing policies, and (iv) is there a difference in impact if environmental concerns are framed as a bonus or as a pricing instrument. The main findings indicate that road accessibility characteristics have a substantial impact on route preferences which is of the same order of magnitude as variation in travel times. This suggests that provision of adequate travel information in itself can be an effective instrument to prevent negative externalities of good transport associated with shortest routes. Furthermore, the results indicate that truck drivers/route planners when choosing a route are relatively sensitive to road pricing schemes and rather insensitive to environmental bonuses.     

Development of a driving simulator based eco-driving support system

This research developed an eco-driving feedback system based on a driving simulator to support eco-driving training. This support system could provide both dynamic and static feedback to improve drivers’ eco-driving behavior. In the process of driving, drivers could get voice prompts (e.g., please avoid accelerating rapidly) once non-eco-driving behavior appeared, and also could see the real-time CO₂ emissions curves. After driving, drivers could receive an eco-driving evaluation report including their fuel consumption rank, potential of fuel saving and driving advice corresponding to their driving behavior. In this support system, five items of non-eco-driving behavior (i.e., quick accelerate, rapid decelerate, engine revolutions at a high level, too fast or unstable speed on freeways and idling for a longer time) were defined and could be detected. To validate this support system’s effectiveness in reducing fuel consumption and emissions, 22 participants were recruited and three driving tests were conducted, first without using the support system, then static feedback and then dynamic feedback utilized respectively. A reduction of 5.37% for CO₂ emissions and 5.45% for fuel consumption was obtained. The results indicated that the developed eco-driving support system was an effective training tool to improve drivers’ eco-driving behavior in reducing emissions and fuel consumption.     

Multi‐objective highway alignment optimization using a genetic algorithm

The available highway alignment optimization algorithms use the total cost as the objective function. This is a single objective optimization process. In this process, travel‐time, vehicle operation accident earthwork land acquisition and pavement construction costs are the basic components of the total cost. This single objective highway alignment optimization process has limited capability in handling the cost components separately. Moreover, this process cannot yield a set of alternative solutions from a single run. This paper presents a multi‐objective approach to overcome these shortcomings. Some of the cost components of highway alignments are conflicting in nature. Minimizing some of them will yield a straighter alignment; whereas, minimizing others would make the alignment circuitous. Therefore, the goal of the multiobjective optimization approach is to handle the trade‐off amongst the highway alignment design objectives and present a set of near optimal solutions. The highway alignment objectives, i.e., cost functions, are not continuous in nature. Hence, a special genetic algorithm based multi‐objective optimization algorithm is suggested The proposed methodology is demonstrated via a case study at the end.     

盾构机刀盘驱动系统动力计算分析

通过对广州地铁西草区间两台盾构机现场实测刀盘转速、刀盘扭矩数据,结合盾构配置的电机、液压泵、马达、减速箱的铭牌标定参数,计算分析得出制造商配置的减速箱并不能满足招投标时的产品承诺和现场实际需要。     

Dynamic system‐optimal traffic assignment for a city using the continuum modeling approach

This paper presents a continuum dynamic traffic assignment model for a city in which the total cost of the traffic system is minimized: the travelers in the system are organized to choose the route to their destinations that minimizes the total cost of the system. Combined with the objective function, which defines the total cost and constraints such as certain physical and boundary conditions, a continuum model can be formulated as an optimization scheme with a feasible region in the function space. To obtain an admissible locally optimal solution to this problem, we first reformulate the optimization in discrete form and then introduce a heuristic method to solve it. This method converges rapidly with attractive computational cost. Numerical examples are used to demonstrate the effectiveness of the method. Copyright © 2013 John Wiley & Sons, Ltd.     

Evaluating critical lines and stations considering the impact of the consequence using transit assignment model ‐case study of London's underground network

As the problem of full transit vehicles is encountered daily by passengers in most of the big cities, previous research evaluated the consequence of overcrowding in terms of on‐board crowding and passengers not being able to board with full vehicles. The impact of overcrowding in the real world is, however, not necessarily proportional to these numbers. This paper attempts to specify the critical lines and stations of a network by considering the number of passengers failing to board and attempting to evaluate its impact on service quality and safety risks. The hypothesis is that larger stations with wider platforms can often cope better with overcrowding than smaller stations. Therefore a station size dependent satisfaction function is proposed, which takes values from 0 to 1. The method is applied to London's underground network with a number of scenarios which show critical stations in the network if delays occur.     

Apron capacity at hub airports—the impact of wave‐system structure

At hub airports, dominant airlines/alliance coordinate their flights in time with the aim of increasing the number (and quality) of connections, thus producing a wave‐system in traffic schedules. This paper addresses the impact of concentrating aircraft into waves on airport apron capacity. Existing models for apron capacity estimation are based on the number of stands, stand occupancy time, and demand structure, differing between representative groups of aircraft served at an airport. Criteria for aircraft grouping are aircraft type and/or airline and/or type of service (domestic, international, etc.). Modified deterministic analytical models proposed in this paper also take into account the wave‐system parameters, as well as runway capacity. They include the impact of these parameters on the number of flights in wave, stand occupancy time, and consequently apron capacity. Numerical examples illustrate the difference between apron capacity for an origin–destination airport and a hub airport, under the same conditions; utilization of the theoretical apron capacity at a hub airport, given the wave‐system structure; and utilization of the apron capacity at a hub airport when point‐to‐point traffic is allowed to use idle stands. Furthermore, the influence of different assignment strategies for aircraft stands in the case of hub airports is also discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

Service effectiveness of prt vs collective ‐ corridor transport

A generalised model is used to provide estimates of overall trip times and speed for conventional corridor‐collective transport and PRT. The results demonstrate why traditional forms of transport find difficulty providing an effective service in a city. Short separations between stops are required to minimise walk times but on conventional transport this leads to significant reductions in achievable speed because of the need for frequent stops. It is also shown that there is very little benefit in service effectiveness from LRT/APM/Monorail over buses. PRT is immune to these effects. The present calculations typically show a benefit for PRT of a factor of two or greater in trip time over either bus or LRT/APM.     

An agent‐based simulation model to assess the impacts of introducing a shared‐taxi system: an application to Lisbon (Portugal)

This paper presents a new concept of urban shared‐taxi services. The proposed system has a new organisational design and pricing scheme that aims to use the capacity in traditional taxi services in a more efficient way. In this system, a taxi acting in ‘sharing’ mode offers lower prices to its clients, in exchange for them to accept sharing the vehicle with other persons who have compatible trips (time and space). The paper proposes and tests an agent‐based simulation model in which a set of rules for space and time matching between a request of a client and the candidate shared taxis is identified. It considers that the client is only willing to accept a maximum deviation from his or her direct route and establishes an objective function for selecting the best candidate taxi. The function considers the minimum travel time combination of pickup and drop‐off of all the pool of clients sharing each taxi while allowing to establish a policy of bonuses to competing taxis with certain number of occupants. An experiment for the city of Lisbon is presented with the objectives of testing the proposed simulation conceptual model and showing the potential of sharing taxis for improving mobility management in urban areas. Results show that the proposed system may lead to significant fare and travel time savings to passengers, while not jeopardising that much the taxi revenues. Copyright © 2014 John Wiley & Sons, Ltd.     

Sequential optimization approach for the multi‐class user equilibrium problem in a continuous transportation system

We consider a city region with several facilities that are competing for customers of different classes. Within the city region, the road network is dense, and can be represented as a continuum. Customers are continuously distributed over space, and they choose a facility by considering both the transportation cost and market externalities. More importantly, the model takes into account the different transportation cost functions and market externalities to which different customer classes are subjected. A logit‐type distribution of demand is specified to model the decision‐making process of users' facility choice. We develop a sequential optimization approach to decompose the complex multi‐class and multi‐facility problem into a series of smaller single‐class and single‐facility sub‐problems. An efficient solution algorithm is then proposed to solve the resultant problem. A numerical example is given to demonstrate the effectiveness and potential applicability of the proposed methodology.     

城市化进程中的交通保障体系研究

通过交通与城市化辩证关系的研究,以及城市化进程中交通可持续发展的经验探讨,围绕建立"运输安全型、质量效益型、科技先导型、资源节约型、环境友好型"的可持续交通发展模式,研究构建科学合理的城市化交通保障体系.     

Assessment of the effects of highway geometric design features on the frequency of truck involved crashes using bivariate regression

Given the enormous losses to society resulting from large truck involved crashes, a comprehensive understanding of the effects of highway geometric design features on the frequency of truck involved crashes is needed. To better predict the occurrence probabilities of large truck involved crashes and gain direction for policies and countermeasures aimed at reducing the crash frequencies, it is essential to examine truck involved crashes categorized by collision vehicle types, since passenger cars and large trucks differ in dimensions, size, weight, and operating characteristics. A data set that includes a total of 1310 highway segments with 1787 truck involved crashes for a 4-year period, from 2004 to 2007 in Tennessee is employed to examine the effects that geometric design features and other relevant attributes have on the crash frequency. Since truck involved crash counts have many zeros (often 60–90% of all values) with small sample means and two established categories, car-truck and truck-only crashes, are not independent in nature, the zero-inflated negative binomial (ZINB) models are developed under the bivariate regression framework to simultaneously address the above mentioned issues. In addition, the bivariate negative binomial (BNB) and two individual univariate ZINB models are estimated for model validation. Goodness of fit of the investigated models is evaluated using AIC, SBC statistics, the number of identified significant variables, and graphs of observed versus expected crash frequencies. The bivariate ZINB (BZINB) models have been found to have desirable distributional property to describe the relationship between the large truck involved crashes and geometric design features in terms of better goodness of fit, more precise parameter estimates, more identified significant factors, and improved predictive accuracy. The results of BZINB models indicate that the following factors are significantly related to the likelihood of truck involved crash occurrences: large truck annual average daily traffic (AADT), segment length, degree of horizontal curvature, terrain type, land use, median type, lane width, right side shoulder width, lighting condition, rutting depth (RD), and posted speed limits. Apart from that, passenger car AADT, lane number, and indicator for different speed limits are found to have statistical significant effects on the occurrences of car-truck crashes and international roughness index (IRI) is significant for the predictions of truck-only crashes.     

Quantifying the effects of driver non-compliance and communication system failure in the performance of real-time bus control strategies

Control strategies that prevent bus bunching allow for improvement to the level of service offered by a transit corridor as well as reducing travel time and its variability, thus providing higher reliability to the user. Several optimization models based on the use of real-time information have been shown to achieve this, through the planning of holding of the buses at bus stops. In the majority of the cases the benefits of these models have been estimated assuming ideal operational conditions while only few of them have been tested in real conditions. However, neither the simulation experiment, nor the real implementations have quantified the effects of real-life phenomena that harm the performance of the system, preventing it from achieving the full potential of these control schemes.This paper examines three phenomena that may occur during the operation of a bus service, which would limit the effectiveness of a holding-based control strategy in the sense that some of the planned holdings might not be executed. These phenomena are drivers non-compliance, failure of communication systems with buses, and the combination of both. The objective is to estimate the negative impact these phenomena can have on the benefits of the strategy, and to identify possible measures that could help operators and decision makers to reduce this impact. Both objectives are achieved using the real-time holding model developed by Delgado et al. (2012), which is tested in a simulation environment.     

Optimizing the process of designing and calculating railway catenary support infrastructure using a high-productivity computational tool

The process of designing and calculating railway catenary infrastructure, as the way it is carried out currently, is very complex and time consuming. It is necessary expert knowledge of different fields, like design and structural calculus, technical security, legal normative, topography, etc. This process consists of several stages aimed at choosing a design, checking requirements, and calculating structural feasibility, so the communication among the experts may be quite slow. In order to reduce time and effort invested in this process, we propose a system that allows to automate its stages and tasks. Our system provides a valid solution per structure, that complies with design and structural constraints, and with existing railway regulations. The proposed system has been integrated in a high-productivity software tool, that avoids human mistakes due to hand-calculation, allows users a fast design and calculation, and exploits the ability of current computers to run tasks concurrently so as to speed up the process. The computational performance and complexity of the tool, as well as statistics values, are analysed by designing and calculating up to 2048 heterogeneous support structures. Besides, the tool is evaluated through a study case based on a real railway route, obtaining an overall improvement of 82.33% in time invested over the existing process.