A dynamic lane-changing trajectory planning model for automated vehicles

This paper focuses on the lane-changing trajectory planning (LTP) process in the automatic driving technologies. Existing studies on the LTP algorithms are primarily the static planning method in which the states of the surrounding vehicles of a lane-changing vehicle are assumed to keep unchanged in the whole lane-changing process. However, in real-world traffic, the velocities of the surrounding vehicles change dynamically, and the lane-changing vehicle needs to adjust its velocity and positions correspondingly in real-time to maintain safety. To address such limitations, the dynamic lane-changing trajectory planning (DLTP) model is proposed in the limited literature. This paper proposes a novel DLTP model consisting of the lane-changing starting-point determination module, trajectory decision module and trajectory generation module. The model adopts a time-independent polynomial trajectory curve to avoid the unrealistic assumptions on lane-changing velocities and accelerations in the existing DLTP model. Moreover, a rollover-avoidance algorithm and a collision-avoidance algorithm containing a reaction time are presented to guarantee the lane-changing safety of automated vehicles, even in an emergent braking situation. The field lane-changing data from NGSIM data are used to construct a real traffic environment for lane-changing vehicles and verify the effectiveness of the proposed model, and CarSim is applied to investigate the traceability of the planned lane-changing trajectories using the proposed model. The results indicate that an automated vehicle can complete the lane-changing process smoothly, efficiently and safely following the trajectory planned by the proposed model, and the planned velocity and trajectory can be well-tracked by automated vehicles.     

A kinematic wave theory of lane-changing traffic flow

Frequent lane-changes in highway merging, diverging, and weaving areas could disrupt traffic flow and, even worse, lead to accidents. In this paper, we propose a simple model for studying bottleneck effects of lane-changing traffic and aggregate traffic dynamics of a roadway with lane-changing areas. Based on the observation that, when changing its lane, a vehicle affects traffic on both its current and target lanes, we propose to capture such lateral interactions by introducing a new lane-changing intensity variable. With a modified fundamental diagram, we are able to study the impacts of lane-changing traffic on overall traffic flow. In addition, the corresponding traffic dynamics can be described with a simple kinematic wave model. For a location-dependent lane-changing intensity variable, we discuss kinematic wave solutions of the Riemann problem of the new model and introduce a supply–demand method for its numerical solutions. With both theoretical and empirical analysis, we demonstrate that lane-changes could have significant bottleneck effects on overall traffic flow. In the future, we will be interested in studying lane-changing intensities for different road geometries, locations, on-ramp/off-ramp flows, as well as traffic conditions. The new modeling framework could be helpful for developing ramp-metering and other lane management strategies to mitigate the bottleneck effects of lane-changes.     

A multiple discrete-continuous model for independent- and joint-discretionary-activity participation decisions

This paper presents a multiple discrete-continuous econometric structure to model the daily time-investment decisions of couples in solo- and joint-discretionary activities incorporating intra-personal and inter-personal inter-dependencies. The empirical model was estimated using data from the 2000 Bay Area Travel Survey. The results indicate evidence of the positive impact of vehicle availability on independent activity participation and the negative impacts of the presence of children and mandatory time investments on the joint discretionary-activity engagement of the spouses. In addition, we also find the mandatory- and maintenance-activity-participation characteristics of the spouse to influence the discretionary activity choices of individuals. Finally, the analysis also indicates a strong impact of common unobserved factors on the decisions of couples. From a policy analysis perspective, these results imply that demand-management actions directly impacting one adult could also result in changes to the activity patterns of his/her spouse and to changes in joint activity participation characteristics. Dr. Sivaramakrishnan Srinivasan is an Assistant Professor in the Department of Civil and Coastal Engineering at the University of Florida. His research interests include travel-behavior analysis, activity-based travel-demand modeling, and the application of advanced econometric methods for transportation problems. Dr. Chandra R. Bhat has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE).     

A microscopic analysis of speed deviation impacts on lane-changing behavior

Driving behavior models that capture drivers’ tactical maneuvering decisions in different traffic conditions are essential to microscopic traffic simulation systems. This paper focuses on a parameter that has a great impact on road users’ aggressive overtaking maneuvers and directly affects lane-changing models (an integral part of microscopic traffic simulation models), namely, speed deviation. The objective of this research is to investigate the impacts of speed deviation in terms of performance measures (delay time, network mean speed, and travel time duration) and the number of lane-change maneuvers using the Aimsun traffic simulator. Following calibration of the model for a section of urban highway in Tehran, this paper explores the sensitivity of lane-changing maneuvers during different speed deviations by conducting two types of test. Simulation results show that, by decreasing speed deviation, the number of lane changes reduces remarkably and so network safety increases, thus reducing travel time due to an increase in network mean speed.     

Modeling the impacts of mandatory and discretionary lane-changing maneuvers

In this paper, a novel mesoscopic multilane model is proposed to enable simultaneous simulation of mandatory and discretionary lane-changing behaviors to realistically capture multilane traffic dynamics. The model considers lane specific fundamental diagrams to simulate dynamic heterogeneous lane flow distributions on expressways. Moreover, different priority levels are identified according to different lane-changing motivations and the corresponding levels of urgency. Then, an algorithm is proposed to estimate the dynamic mandatory and discretionary lane-changing demands. Finally, the lane flow propagation is defined by the reaction law of the demand–supply functions, which can be regarded as an extension of the Incremental-Transfer and/or Priority Incremental-Transfer principles. The proposed mesoscopic multilane cell transmission model is calibrated and validated on a complex weaving section of the State Route 241 freeway in Orange County, California, showing both the positive and negative impact of lane changing maneuvers, e.g., balancing effect and capacity drop, respectively. Moreover, the empirical study verifies that the model requires no additional data other than the cell transmission model does. Thus, the proposed model can be deployed as a simple simulation tool for accessing dynamic mesoscopic multilane traffic state from data available to most management centers, and also the potential application in predicting the impact of traffic incident or lane control strategy.     

Closed-form multiclass cell transmission model enhanced with overtaking,lane-changing,and first-in first-out properties

A novel multiclass macroscopic model is proposed in this article. In order to enhance first-in, first-out property (FIFO) and transmission function in the multiclass traffic modeling, a new multiclass cell transmission model with FIFO property (herein called FM-CTM) is extended from its prior multiclass cell transmission model (M-CTM). Also, to enhance its analytical compactness and resultant computational convenience, FM-CTM is formulated in this paper as a set of closed-form matrix equations. The objective is to improve the accuracy of traffic state estimation by enforcing FIFO property when a fast vehicle cannot overtake a slow vehicle due to a limitation of a single-lane road. Moreover, the proposed model takes into account a different priority for vehicles of each class to move forward through congested road conditions, and that makes the flow calculation independent from their free-flow speeds. Some hypothetical and real-world freeway networks with a constant or varying number of lanes are selected to verify FM-CTM by comparing with M-CTM and the conventional CTM. Observed densities of VISSIM and real-world dataset of I-80 are selected to compare with the simulated densities from the three CTMs. The numerical results show that FM-CTM outperforms the other two models by 15% of accuracy measures in most cases. Therefore, the proposed model is expected to be well applicable to the road network with a mixed traffic and varying number of lanes.     

Modeling lane-changing behavior in a connected environment: A game theory approach

Vehicle-to-Vehicle communications provide the opportunity to create an internet of cars through the recent advances in communication technologies, processing power, and sensing technologies. A connected vehicle receives real-time information from surrounding vehicles; such information can improve drivers’ awareness about their surrounding traffic condition and lead to safer and more efficient driving maneuvers. Lane-changing behavior, as one of the most challenging driving maneuvers to understand and to predict, and a major source of congestion and collisions, can benefit from this additional information. This paper presents a lane-changing model based on a game-theoretical approach that endogenously accounts for the flow of information in a connected vehicular environment. A calibration approach based on the method of simulated moments is presented and a simplified version of the proposed framework is calibrated against NGSIM data. The prediction capability of the simplified model is validated. It is concluded the presented framework is capable of predicting lane-changing behavior with limitations that still need to be addressed. Finally, a simulation framework based on the fictitious play is proposed. The simulation results revealed that the presented lane-changing model provides a greater level of realism than a basic gap-acceptance model.     

A flexible model structure approach for discrete choice models

Multi-dimensional discrete choice problems are usually estimated by assuming a single-choice hierarchical order for the entire study population or for pre-defined segments representing the behavior of an “average” person and by indicating either limited differences or a variety in choices among the study population. This study develops an integral methodological framework, termed the flexible model structure (FMS), which enhances the application of the discrete choice model by developing an optimization algorithm that segment given data and searches for the best model structure for each segment simultaneously. The approach is demonstrated here through three models that conceptualize the multi-dimensional discrete choice problem. The first two are Nested Logit models with a two-choice dimension of destination and mode; they represent the estimation of a fixed-structure model using pre-segmented data as is mostly common in multi-dimensional discrete choice model implementation. The third model, the FMS, includes a fuzzy segmentation method with weighted variables, as well as a combination of more than one model structure estimated simultaneously. The FMS model significantly improves estimation results, using fewer variables than do segmented NL models, thus supporting the hypothesis that different model structures may best describe the behavior of different groups of people in multi-dimensional choice models. The implementation of FMS involves presenting the travel behavior of an individual as a mix of travel behaviors represented by a number of segments. The choice model for each segment comprises a combination of different choice model structures. The FMS model thus breaks the consensus that an individual belongs to only one segment and that a segment can take only one structure.     

Reaching decisions about technological projects with social consequences: A normative model

Among the crises facing our society is the public's loss of confidence in technical professionals and their ability to make decisions about large-scale projects (such as highways) in the public interest. To overcome this crisis of confidence, this paper hypothesizes a model for the role of the technical professional in the process of reaching decisions about public actions.In evaluating technological projects with social consequences, one key issue is the differential incidence of impacts. Typically, some groups are hurt in order that others may benefit. Social equity must be considered explicitly. Such presently-used techniques as benefit-cost analysis and point-rating schemes are unsatisfactory. New techniques are needed, reflecting a more comprehensive model for the role of the technical team in the political process.A normative model is outlined. First, the objective of the technical process is defined: to achieve substantial effective community agreement on a course of action which is feasible, equitable, and desirable. Second, a process for achieving this objective is proposed. A key element of this process is a four-phase strategy of technical and community interaction activities to achieve the objective. The basic premise of this approach is that the role of the technical team is to clarify the issues of choice, to assist the community in determining what is best for itself.This theoretical model has resulted in several practical products. A procedural guide for use by highway and transportation agencies has been prepared, and a number of specific operational techniques have been developed and are included in the guide. The procedural guide is now being field-tested in several state highway departments. The theoretical model has already been useful in identifying, in one highway department, opportunities for significant changes in the agency's mission, organization and procedures to enable it to be more responsive to public concerns. The theoretical model also has served as the basis for the development of federal guidelines for consideration of social, economic and environmental factors in highway planning and decision-making, in all of the state highway departments in the U.S.This is a revised version of a paper presented to the Seventeenth North American Meeting, Regional Science Association, November 6–8, 1970.     

A test of inter-modal performance measures for transit investment decisions

Choices among alternative transit capital investments are often complex and politically controversial. There is renewed interest in the use of performance indicators to assist in making rational and defensible choices for the investment of public funds. To improve the evaluation of rail and bus performance and provide more useful information for transit investment decision-makers, it is important to use performance indicators that fairly and efficiently compare different transit modes. This paper proposes a set of inter-modal performance indicators in which service input, service output, and service consumption are measured by total cost, revenue capacity miles/hours, and unlinked passenger trips/miles respectively based on economic principles and evaluation objectives. The proposed improvements involve the inclusion of capital as well as operating costs in such comparisons, and the recognition of the widely varying capacities of transit vehicles for seated and standing passengers. Two California cases, the Los Angeles – Long Beach Corridor and the Market/Judah Corridor in San Francisco, are used for testing their usefulness in the evaluation of the efficiency and effectiveness of rail and bus services. The results show substantial differences between performance indicators in current use and those proposed in this study. The enhanced inter-modal performance indicators are more appropriate for comparing the efficiency and effectiveness of different modes or a combination of transit modes at the corridor and system levels where most major investment decisions are made. This revised version was published online in June 2006 with corrections to the Cover Date.     

A rough-cut approach for evaluating location-routing decisions via approximation algorithms

The first step in most location-routing projects involves bringing the primary stakeholders on board and securing funding for implementation of the required changes. To this end, practitioners often need a good feasible solution together with a lower bound on the cost of any solution to the problem at hand, rather than exact solutions based on detailed and accurate parameter estimates. In this article, we present a simple methodology for assessing the quality of the current distribution network as well as for identifying opportunities for improvement. We incorporate the potential use of different transportation technologies at different layers of the network. We demonstrate the versatility of the proposed rough-cut approach by means of two real life implementations: (i) redesigning the supply network of the Casino Group, a supermarket chain in southeast France, and (ii) redesigning the household material recycling network of the city of Calgary, in Canada.     

A behavioral analysis of freight mode choice decisions

This paper develops a behavioral analysis of freight mode choice decisions that could provide a basis for an acceptable analytical tool for policy assessment. The paper specifically examines the way that truck and rail compete for commodity movement in the US. Two binary mode choice models are introduced in which some shipment-specific variables (e.g. distance, weight and value) and mode-specific variables (e.g. haul time and cost) are found to be determinants. The specifications of the non-selected choice are imputed in a machine learning module. Shipping cost is found to be a central factor for rail shipments, while road shipments are found to be more sensitive to haul time. Sensitivity of mode choice decisions is further analyzed under different fuel price fluctuation scenarios. A low level of mode choice sensitivity is found with respect to fuel price, such that even a 50% increase in fuel cost does not cause a significant modal shift between truck and rail.     

A decision support system for integrated hazardous materials routing and emergency response decisions

Hazardous materials routing constitutes a critical decision in mitigating the associated transportation risk. This paper presents a decision support system for assessing alternative distribution routes in terms of travel time, risk and evacuation implications while coordinating the emergency response deployment decisions with the hazardous materials routes. The proposed system provides the following functionalities: (i) determination of alternative non-dominated hazardous materials distribution routes in terms of cost and risk minimization, (ii) specification of the hazardous materials first-response emergency service units locations in order to achieve timely response to an accident, and (iii) determination of evacuation paths from the impacted area to designated shelters and estimation of the associated evacuation time. The proposed system has been implemented, used and evaluated for assessing alternative hazardous materials routing decisions within the heavily industrialized area of Thriasion Pedion of Attica, Greece. The implementation of the aforementioned functionalities is based on two new integer programming models for the hazardous materials routing and the emergency response units location problems, respectively. A simplified version of the routing model is solved by an existing heuristic algorithm developed by the authors. A new Lagrangean relaxation heuristic algorithm has been developed for solving the emergency response units location problem. The focus of this paper is on the exposition of the proposed decision support system components and functionalities. Special emphasis is placed on the presentation of the two new mathematical models and the new solution method for the location model.     

An integrated framework to jointly model decisions of activity time allocation and work-related travel

Five activity-travel choice dimensions, including three activity time allocation decisions and two work-related travel choices, are jointly modeled using the structural equation model in order to accommodate the complex interactions among them. Via a two-step estimation approach, the behavioral pattern underlying activity-travel decisions is explicitly revealed. For example, it demonstrates the priority with respect to subsistence activity, maintenance activity, and recreation activity due to a limited time budget; and bus commuting behavior positively influences the time allocated to the maintenance activity. In addition, two attitudinal factors are constructed and confirmed to have important effects on the five behavioral dimensions, which contribute to reveal the decision-making process from the perspective of psychology. This comprehensive framework is expected to provide important implications for mobility management and urban planning.     

An integrated model for discrete and continuous decisions with application to vehicle ownership,type and usage choices

This paper proposes an integrated econometric framework for discrete and continuous choice dimensions. The model system is applied to the problem of household vehicle ownership, type and usage. A multinomial probit is used to estimate household vehicle ownership, a multinomial logit is used to estimate the vehicle type (class and vintage) choices, and a regression is used to estimate the vehicle usage decisions. Correlation between the discrete (number of vehicles) and the continuous (total annual miles traveled) parts is captured with a full variance–covariance matrix of the unobserved factors. The model system is estimated using Simulated Log-Likelihood methods on data extracted from the 2009 US National Household Travel Survey and a secondary dataset on vehicle characteristics. Model estimates are applied to evaluate changes in vehicle holding and miles driven, in response to the evolution of social societies, living environment and transportation policies.     

Factors influencing the purchasing decisions of low emission cars: A study of Slovenia

This paper presents a study of customer preferences and opinions about alternative fuel vehicles. Nowadays the studies of green technologies, especially in the area of green transport, are interesting for policy makers, vehicle producers, customers and energy suppliers. Many stakeholders from public and private sector are investing a lot of effort to identify consumer behaviour for future improvements in development of their green products and strategies. This study is a modification of previously conducted research on customer behaviour on the same topic in Scotland. The survey includes almost 700 participants to identify the most important parameters of consumer behaviour related to purchase of alternative fuel vehicle. Therefore the questionnaire includes different factors, combining financial and technical aspects, environmental performance and vehicle design. Results have revealed that the most relevant factor for purchasing low emission vehicle is total vehicle price, and that the segment of potential alternative fuel vehicles buyers is much larger than we initially anticipated. Such vehicles are, surprisingly, also more attractive for the older population, according to our results.     

A model for the visualization and analysis of elevator traffic

ABSTRACT

Analysis of elevator traffic in high rise buildings is critical to the performance evaluation of elevator group control systems (EGCS). Elevator dispatching methods or parking algorithms in an EGCS can be designed or modified according to analyses of traffic flow. However, interpretation of traffic flow based solely on numerical data may not be explicit and transparent for EGCS experts as well as for other non-expert building administration. In this study, we present a model for visualization and analysis of elevator traffic. First, we present an alternative approach for traffic analysis which we call route visualization. In the proposed approach, we initially decompose elevator traffic into its component parts and investigate each component independently. Then, using superposition of components we obtain a reconstructed model of overall traffic. This modeling approach provides component-based traffic analysis and representation of routes with intensities through data visualization. In the second part we introduce a multi-dimensional analysis of time parameters in ECGS. This approach provides a comparative analysis of several control algorithms such as dispatch or park algorithms for different combinations of traffic components.     

基坑支挡结构增量法计算模型的研究

增量法是我国目前进行基坑围护结构计算时较常采用的方法,但目前国内对于增量法的研究却不多,尤其是关于"对围护结构施加预加力"这种工况尚无合适的计算模型.文章利用增量法的原理,结合结构计算,研究增量法在对基坑围护墙体施加预加力工况下的计算模型.     

A network model for gate assignment

In this research we developed a network model that will help the airport authorities assign flights to gates both efficiently and effectively. The model was formulated as a multi-commodity network flow problem. An algorithm based on the Lagrangian relaxation, with subgradient methods, accompanied by a shortest path algorithm and a Lagrangian heuristic was developed to solve the problem. The model was tested using data from Chiang Chiek-Shek Airport.