bluuebunny/crossref_metadata_2025 huggingface dataset:
Interactive Heuristic for Practical Vehicle Routing Problem with Solution Shape Constraints
Authors: Tang Hao , Miller-Hooks Elise
Published: May 2018

The vehicle routing problem (VRP) with solution shape constraints is defined, and an interactive heuristic is proposed for its solution. A set of tours with desirable shapes–-that is, that are visually attractive–-possesses two characteristics. Each tour of a visually attractive set of tours is compact, and tours within the set do not cross one another. The visual attractiveness of tours is of great importance in practical routing applications and plays a central role in whether tours are adopted in actual freight transportation operations in many industries, including courier operations of large package delivery companies. Numerical experiments were conducted on real-world data to assess the proposed heuristic. Results of the experiments show that the heuristic, coupled with effective shape measures, is able to provide solutions with significantly improved layout while maintaining satisfactory results in terms of conventional VRP measures (e.g., required fleet size and total cost).
Variable Toll Pricing and Heterogeneous Users
Authors: Lu Chung-Cheng , Zhou Xuesong , Mahmassani Hani S.
Published: May 2018

A dynamic traffic assignment model and its solution algorithm for the bicriterion dynamic user equilibrium (BDUE) problem that allows for heterogeneous users with different value-of-time (VOT) preferences are presented. Assuming the VOT as a continuously distributed random variable across the population of trips, the BDUE problem is formulated as a system of infinite-dimensional variational inequalities (VIs). Rather than solving the VI formulation directly, this study employs a generalized Frank–Wolfe algorithm to find the BDUE flow pattern. A bicriterion time-dependent least-cost path algorithm is applied to generate the extreme efficient path set, and the corresponding breakpoints naturally define the multiple user classes and thereby generate the descent direction for a multiclass dynamic network loading. A traffic simulator is used to describe the traffic flow propagation and the spatial and temporal interactions. To circumvent the difficulty of storing the memory-intensive path set and routing policies for large-scale network applications, a vehicle-based implementation technique is proposed, with the vehicle path set as a proxy for keeping track of the path assignment results. A set of numerical experiments is conducted to explore the convergence behavior of the BDUE algorithm and investigate how VOT distributions affect the path flow pattern and toll road usage under different dynamic road pricing scenarios.
Interactive Learning in Transportation Networks with Uncertainty, Bounded Rationality, and Strategic Choice Behavior
Authors: Han Qi , Timmermans Harry
Published: May 2018

Existing learning and adaptive behavior models are typically derived from reinforcement learning from actual experiences in dynamic non-stationary environments. When the dynamics involve uncertainty with respect to the choice behavior of other travelers, travelers might make particular choice options by taking into account their expectations about the behavior of other travelers. Consequently, they will learn not only from their own experiences but also from the extent to which their conjectures about the behavior of other travelers are consistent with actual choices. A general model of interactive learning behavior that evolves toward equilibrium in such strategic situations is described. The properties of the model are examined by using numerical computer simulations. The results of the simulations support the face validity of the formulated model.
New Reserve Capacity Model of Signal-Controlled Road Network
Authors: Chen Anthony , Chootinan Piya , Wong S. C.
Published: May 2018

The aim of this study is to examine further the new capacity–reliability index recently proposed for the design of a new reserve capacity model for a signal-controlled road network. This new reliability index explicitly accounts for the probability that all network links would be operated below their capacities when serving different traffic patterns deviating from the average condition. Specifically, the reserve capacity model is reformulated by using the new reliability index in a bilevel optimization framework. In addition, the reliability-based design is compared with that of the reserve capacity model to gain insights between the deterministic and stochastic network design problems.
Proposed Framework for Simultaneous Optimization of Evacuation Traffic Destination and Route Assignment
Authors: Yuan Fang , Han Lee D. , Chin Shih-Miao , Hwang Holing
Published: May 2018

In the conventional evacuation planning process, evacuees are assigned to fixed destinations mainly on the basis of geographical proximity. However, the use of such prespecified destinations (an origin–destination table) almost always results in less-than-optimal evacuation efficiency because of uncertain road conditions, including traffic congestion, road blockage, and other hazards associated with the emergency. By relaxing the constraint of assigning evacuees to prespecified destinations, a one-destination evacuation (ODE) concept has the potential to improve evacuation efficiency greatly. To this end, a framework for the simultaneous optimization of evacuation traffic distribution and assignment is proposed. The ODE concept can be used to obtain an optimal destination and route assignment by solving a one-destination (1 D) traffic assignment problem on a modified network representation. When tested for a countywide special event–based evacuation case study, the proposed 1 D model presents substantial improvement over the conventional multiple-destination ( nD) model and can potentially reduce overall evacuation time by more than 60%. More important, this framework can be easily implemented and its efficiency enhanced simply by instructing evacuees to head for destinations resulting from the 1 D simulations run beforehand.
Stochastic Heuristic Dynamic Assignment Based on AIMSUN Microscopic Traffic Simulator
Authors: Barceló Jaime , Casas Jordi
Published: May 2018

The deployment of intelligent transportation systems must be assisted by suitable tools to conduct the feasibility studies required to test the designs and evaluate the expected impacts. Microscopic traffic simulation has proved to be the suitable methodological approach to achieve these goals. One of the most critical aspects of the dynamic simulation of road networks based on a microscopic approach–-namely, how to perform a heuristic dynamic assignment, the implied route choice models, and whether under certain criteria the approach can achieve stochastic user equilibrium–-is discussed.
Reliable Network Design Problem
Authors: Sumalee Agachai , Watling David P. , Nakayama Shoichiro
Published: May 2018

In the reliable network design problem (RNDP) the main sources of uncertainty are variable demand and route choice. The objective is to maximize network total travel time reliability (TTR), which is defined as the probability that the network total travel time will be less than a threshold. A framework is presented for a stochastic network model with Poisson-distributed demand and uncertain route choice. The travelers are assumed to choose their routes to minimize their perceived expected travel cost following the probit stochastic user equilibrium condition. An analytical method is presented for approximation of the first and second moments of the total travel time. These moments are then fitted with a log-normal distribution. Then the design problem is tackled in which the analytical derivative of the TTR is derived with the sensitivity analysis of the equilibrated path choice probability. This derivative is then supplied to a gradient-based optimization algorithm to solve the RNDP. The algorithm is tested with a small network example.
Cell-Based Network Optimization Model for Staged Evacuation Planning under Emergencies
Authors: Liu Ying , Lai Xiaorong , Chang Gang-Len
Published: May 2018

Staged evacuation is widely used in emergency situations in which different parts of the target network may suffer different levels of severity over different time windows. By evacuating those populations in the network via an optimized sequence, the staged evacuation strategy can best use available roadway capacity, optimally distribute the total demand over the evacuation time horizon, and thus minimize the network congestion level. This study proposes a cell-based network model to capture critical characteristics associated with staged evacuation operations. The proposed model shows the ability to reflect incident impacts and arrival patterns of evacuees in computing the optimal starting time and routes for each evacuation zone. Preliminary numerical results have demonstrated the potential for applying the proposed staged evacuation model in real-world emergency management and planning.
Combined Model for Intermodal Networks with Variable Transit Frequencies
Authors: Peric Krunoslav , Boilé Maria
Published: May 2018

The formulation and solution of a combined mode choice and assignment, intermodal network equilibrium model with asymmetric link cost interactions are presented. Automobile, bus, and rail are the modes considered as travel options in the proposed formulation, along with the combined automobile-to-bus and automobile-to-rail intermodal options. Using park-and-ride facilities as transfer points, travelers may switch from automobile to transit. There is a two-way interaction between automobile and bus transit. The presence of transit vehicles on the highway links is registered through a bus–car equivalency factor, and the transit travel time depends on the highway link congestion level. Transit travel times are also subject to congestion at the transit stops because of boarding and alighting. Transit frequencies vary, depending on the level of congestion. The solution algorithm for the variational inequality and the derivation of the descent direction for the diagonalized problem are also presented. A test network is developed, and several tests are presented to show the convergence of the algorithm as well as the changes in the transit level of service due to transit and highway congestion.
Single-Point Approximations for Traffic Equilibrium Problem under Uncertain Demand
Authors: Ukkusuri Satish V. , Waller S. Travis
Published: May 2018

The focus of this study is on developing solutions for the traffic equilibrium problem (TEP) when origin–destination demand is assumed to be uncertain. Instead of developing and solving an expensive stochastic solver, it proposes single-point approximate measures that provide a reasonably good estimate of the network performance. Seven approximation schemes that utilize the deterministic TEP to account for uncertain demand and illustrate how these approaches can be used to solve the problem are proposed. The performance of the different approximation measures on different demand distributions for the Sioux Falls, South Dakota, network is reported, and a consistent approximation scheme is identified that performs well for the problem. Such an approximation scheme can be used in solving the TEP accounting for stochastic demand when computational resources are scarce or when a stochastic solver is unavailable.
Dynamic Origin-Destination Trip Demand Estimation for Subarea Analysis
Authors: Zhou Xuesong , Erdoğan Sevgi , Mahmassani Hani S.
Published: May 2018

Subarea analysis capability is needed in conjunction with dynamic network analysis models to allow consideration and rapid evaluation of a large number of scenarios and to support transportation network planning and operations decisions for situations that may not require analysis on a complete network representation. With a focus on how to provide an up-to-date time-dependent origin–destination (O-D) demand matrix for the subarea network, a two-stage subarea demand estimation procedure is described. The first stage uses path-based traffic assignment results from the original network to generate an induced O-D demand matrix for the subarea network. The second stage incorporates an iterative bilevel subarea O-D updating procedure to find a consistent network flow pattern, using the induced O-D demand information and archived traffic measurements in the subarea network. An excess-demand traffic assignment formulation is adopted to model the external trips that traverse or bypass the subarea network. This formulation allows vehicular flow to respond to traffic conditions resulting from network and operational changes in the subarea, and it can be adequately interpreted in an entropy maximization framework. The proposed procedure is illustrated in a case study using the Los Angeles subarea network extracted from the Southern California Association of Governments regional transportation planning network.
Decomposition Scheme for Continuous Network Design Problem with Asymmetric User Equilibria
Authors: Ban Xuegang , Liu Henry X. , Lu Jiangang , Ferris Michael C.
Published: May 2018

The continuous network design problem is formulated as a mathematical program with complementarity constraints (MPCC) and a Gauss–Seidel decomposition scheme is presented for the solution of the MPCC model. The model has an upper level as a nonlinear programming problem and the lower level as a nonlinear complementarity problem. With the application of the complementarity slackness condition of the lower-level problem, the original bilevel formulation can be converted into a single-level nonlinear programming problem. To solve the single-level problem, a decomposition scheme that can resolve the possible dimensionality problem (i.e., a large number of defining variables) is developed. The decomposition scheme is tested, and promising results are shown for well-known test problems.
Arriving-on-Time Problem
Authors: Nie Yu , Fan Yueyue
Published: May 2018

Finding optimal paths in stochastic networks is an important topic in many scientific and engineering fields. To cope with uncertainty, various performance measures, including expected travel time, reliability, value at risk, and expectation with chance constraint, have been introduced. The literature has shown that adaptive strategies that incorporate both anticipation and real-time information are more efficient than a preplanned strategy in a stochastic environment. Most adaptive optimal-path algorithms focus on least-expected travel time. Recently, an adaptive path-finding strategy, named the stochastic on-time arrival (SOTA) algorithm, was proposed to maximize the travel time reliability for any given time threshold. However, the originally proposed SOTA algorithm is based on the classic successive approximation. Whether this algorithm converges within a finite number of successive approximation steps is an open question. In this study, the proposed discrete SOTA algorithm runs in an optimal polynomial time and thus improves the computational efficiency significantly. Numerical examples are provided, and future extensions are proposed.
Survival Analysis–Based Dynamic Travel Demand Models for Hurricane Evacuation
Authors: Fu Haoqiang , Wilmot Chester G.
Published: May 2018

Two dynamic travel demand models for hurricane evacuation based on survival analysis are presented: a Cox proportional hazards model and a piecewise exponential model. These models were used to estimate the probability of a household's evacuating within discrete time intervals before hurricane landfall as a function of the household's socioeconomic characteristics, the characteristics of the hurricane, and management practice in terms of the issuance of an evacuation order. Data from southeast Louisiana collected following Hurricane Andrew were applied. Both models reproduced the evacuation behavior satisfactorily, although the piecewise exponential model was slightly more accurate. Both appear capable of modeling dynamic hurricane evacuation travel demand. However, the Cox model cannot accommodate certain time-dependent variables because of its structure. The piecewise exponential model does not have such a limitation. The piecewise exponential model also has the advantage of estimating the baseline hazards endogenously.
Optimal Scheduling of Evacuation Operations
Authors: Sbayti Hayssam , Mahmassani Hani S.
Published: May 2018

Evacuations necessitated by extreme events are usually envisioned as taking place with all people evacuating simultaneously; this leads to premature congestion on the surface streets and excessive delays. With the evacuating load onto the network staggered, the onset of congestion may be delayed, and people can evacuate more quickly. In this study, the problem of scheduling evacuation trips between a selected set of origin nodes and (safety) destinations was considered, with the objective of minimizing network clearance time. A modified system-optimal dynamic traffic assignment formulation is proposed; in it the total system evacuation time, as opposed to the total system trip time, is minimized. An iterative heuristic procedure is used to solve this problem: the method of successive averages is used to find the flow assignments for the next iteration; a traffic simulator, DYNASMART-P, is used to propagate the vehicles on their prescribed paths and determine the state of the system. Therefore, the simulator serves as a tool to satisfy the dynamic traffic assignment constraints implicitly while evaluating the objective function. The output of this model will be the departure time, route, and destination choices for each evacuee. The output is then aggregated to produce a time-dependent staging policy for each selected origin.
Number and Location of Sensors for Real-Time Network Traffic Estimation and Prediction
Authors: Eisenman Stacy M. , Fei Xiang , Zhou Xuesong , Mahmassani Hani S.
Published: May 2018

Installing and maintaining sensors in a transportation network can be expensive. The motivation for this research is finding the best way to deploy finite resources and generate a network detection system in a manner that produces minimal estimation errors. The analysis uses a simulation-based real-time network traffic estimation and prediction system based on dynamic traffic assignment (DTA) methodology to analyze different levels of detection and different sensor locations in a portion of the Chesapeake Highway Advisories Routing Traffic (CHART) network (between Washington, D.C., and Baltimore, Maryland). This study provides a conceptual framework of the sensor location problem and a theoretical description of the objectives associated with the sensor location problem. A sensitivity analysis of the estimation and prediction quality with the DYNASMART-X real-time DTA system in relation to sensor number and location is conducted in the Maryland CHART network. The analysis considers both randomly generated location scenarios and scenarios based on engineering judgment. The analysis reveals the importance of providing detection in specific locations of the network and the dependence of the value of additional detection on the specific location selected.
Derivation of Origin–Destination Distributions from Traffic Counts
Authors: Watson James R. , Prevedouros Panos D.
Published: May 2018

Origin–destination (O-D) traffic flows are an essential element in several freeway and network traffic models. In general, it is impossible to identify a unique O-D matrix from volume counts alone. Several methods for deriving O-D data exist, and they vary in complexity, cost, and analysis time. O-D matrices were generated with five methods that were applied to the same set of volume data. The resulting O-D matrices were used as the only variable input component in traffic simulation with INTEGRATION. Traffic simulation output was used to assess the implications of the O-D distribution. The O-D data produced by the deterministic method were clearly different from those of the other four methods. The proportionate and QueensOD (with default seed) output were somewhat dissimilar. All other combinations were similar, and the proportionate and FREQ O-D output were statistically identical. The simulation output with the proportionate-method O-D data met the 10/75 speed criterion at all five of the cross-section locations [it was within 10 mph (16 km/h) of field speed for 75% of the time periods]. Pearson's correlation of speeds at five locations indicated that all O-D methods except the deterministic one have a strong correlation with each other. A similar outcome was obtained with t-tests of the total travel time output.
Short-Term Traffic Flow Prediction with Regime Switching Models
Authors: Cetin Mecit , Comert Gurcan
Published: May 2018

Accurate short-term prediction of traffic parameters is a critical component for many intelligent transportation system applications. Traffic flow is subject to abrupt disturbances because of various unexpected events (e.g., accidents, weather-induced disruption) that may change the underlying dynamics and the stability of the data generation process. Short-term prediction models that do not account for these changes produce biased and less accurate predictions. This paper proposes a new adaptive approach to short-term prediction that explicitly accounts for occasional regime changes by using statistical change-point detection algorithms. In this context, the expectation maximization and the CUSUM (cumulative sum) algorithms are implemented to detect shifts in the mean level of the process in real time. Autoregressive integrated moving average models are used for developing the forecasting models while the process mean is monitored by the two detection algorithms. The intercept of the forecasting models is updated on the basis of the detected shifts in the mean level to adapt to any potential new regimes. The proposed approach is tested on real-world loop data sets. The results show significant improvements in prediction accuracy compared with traditional autoregressive integrated moving average models with fixed parameters.
Equilibrium of Lane Flow Distribution on Motorways
Authors: Wu Ning
Published: May 2018

The distribution of traffic flow in the individual lanes of multilane motorways is an important investigation task in traffic engineering, because the lane flow distribution directly affects the capacity of the motorway section under investigation. Following the basic idea of the work of Heidemann, the flow distribution in the individual lanes was rederived and extended to carriageways with more than three lanes. The model was then calibrated with field data obtained from Germany. In addition, the proposed model was extended to congested traffic conditions. The proposed model can therefore be applied for entire flow conditions in reality.
Point Constriction, Interface, and Boundary Conditions for Kinematic-Wave Model
Authors: Nelson Paul , Kumar Nishant
Published: May 2018

The entropy solutions of the Riemann problem for the kinematic-wave model are described for (entrant and exiting) boundary conditions, interfaces (e.g., lane drops), and point constrictions (e.g., bottlenecks or signalized intersections) for kinematic-wave models. These results are used to obtain analytic solutions and computational solutions, by the method of Godunov, for the three test scenarios earlier suggested by Ross. Results show that the kinematic-wave model, with a correct computational solution (i.e., converging to the entropy solution), correctly produces the analytic (entropy) solutions of the kinematic-wave model and that analytic and computational solutions both satisfy intuitive expectations at least as well as the novel model suggested by Ross and even avoid some acknowledged deficiencies of the latter. They also emphasize the necessity of using discrete approximations that satisfy the entropy condition and of exercising care in ensuring that the discretization parameters are sufficiently small.
Probabilistic Breakdown Phenomenon at On-Ramp Bottlenecks in Three-Phase Traffic Theory
Authors: Kerner Boris S. , Klenov Sergey L.
Published: May 2018

A nucleation model for the breakdown phenomenon at an on-ramp bottleneck is presented. This model is based on Kerner's three-phase traffic theory. In this theory, traffic breakdown is associated with a first-order phase transition from the free-flow phase to the synchronized-flow phase. It is suggested that because of merging of a flow on the main road with an on-ramp inflow, free flow is spatially nonhomogeneous in the neighborhood of a bottleneck. This permanent and motionless nonhomogeneity can be considered a deterministic vehicle cluster localized at the bottleneck. Because of the deterministic cluster, the breakdown phenomenon can also occur if there were no fluctuations in free flow. At a lower flow rate, traffic breakdown nucleation occurs through a random increase in vehicle number within the deterministic vehicle cluster. The mean time delay and the associated nucleation rate of traffic breakdown at the bottleneck were found and investigated. The model and a nucleation rate of traffic breakdown exhibit qualitatively different features compared with previous results.
Feedback Route Guidance Applied to a Large-Scale Express Ring Road
Authors: Wang Yibing , Papageorgiou Markos , Sarros George , Knibbe Willem Jan
Published: May 2018

This paper addresses the application of real-time feedback route guidance to a large-scale express ring road. The paper starts with a brief introduction of some necessary notions, followed by a short presentation of the feedback routing strategy of the PI type and an ideal iterative routing strategy of the Frank–Wolfe type, as well as of the macroscopic freeway traffic flow modeling tools METANET and METANET-DTA. The Amsterdam express ring road A10 is considered for the route guidance investigation. More specifically, the introduced feedback strategy and iterative strategy were tested in simulation with regard to A10 with the use of METANET and METANET-DTA. The results indicate that real-time route guidance can help reduce heavy nonrecurrent congestion and establish dynamic user equilibrium.
Continuum Traffic Model for Freeway with On- and Off-Ramp to Explain Different Traffic-Congested States
Authors: Ngoduy D. , Hoogendoorn Serge P. , Van Zuylen H. J.
Published: May 2018

This paper presents a multilane continuum traffic flow model for traffic operations at on- and off-ramps, which is based on microscopic principles. One of the main contributions of the derived model is that it takes into account explicitly the impact of ramp length on traffic flow operations, as well as the willingness of drivers to accept smaller gaps when approaching at the end of on-ramps. Different congested states were investigated with the proposed model for specific values of both the upstream main carriageway flow and the on-ramp flow. Several types of congestion states consistent with well-known traffic-congested styles in the literature, such as a moving localized cluster, two moving localized clusters, triggered stop-and-go waves, and homogeneous congested traffic, were found. The simulation results show the stability states of traffic flow for different ramp lengths.
Empirics of Multianticipative Car-Following Behavior
Authors: Hoogendoorn Serge P. , Ossen Saskia , Schreuder M.
Published: May 2018

This paper considers multianticipative car-following behavior (i.e., driver behavior that includes responses to multiple vehicles ahead). Two well-known models incorporating multivehicle stimuli (Bexelius and Lenz) are recalled, and various modifications are proposed to improve their performance. With vehicle trajectories for a motorway collected from a helicopter and a newly developed approach to parameter identification, new empirical evidence of multianticipative car-following is provided with estimates of the driver-specific parameters of the considered multianticipative car-following models. In doing so, one can investigate the nature of multileader stimuli, including insights into the number of vehicles ahead to which drivers react and the kind of stimuli to which drivers respond. Large interdriver variability in multileader driving behavior is also presented. In the last part of the paper, implications of the research findings for microscopic modeling are discussed.
Interdriver Differences in Car-Following
Authors: Ossen Saskia , Hoogendoorn Serge P. , Gorte Ben G. H.
Published: May 2018

This paper examines the car-following behavior of individual drivers in real traffic on the basis of vehicle trajectory data extracted from high-resolution digital images collected at a high frequency from a helicopter. These data are used to cross-compare seven car-following models regarding their average performances as well as their specific performances for all individual drivers observed using a simulation approach. The prime objective of this cross-comparison is to study interdriver differences; both optimal parameter settings and model performances are compared between drivers. Average model performances reveal that the simplest models are generally not able to capture the dynamics of car-following behavior correctly, whereas individual estimates show that the performances of more elaborate models differ between drivers. The most important contribution of this paper is that analysis shows that interdriver differences cannot be caught by different parameter settings alone; driving styles of individual drivers appear to be inherently different in that various car-following models are needed to model them satisfactorily.
Estimation of Driver Reaction Time from Car-Following Data
Authors: Ma Xiaoliang , Andréasson Ingmar
Published: May 2018

Driver behavior plays an important role in modeling vehicle dynamics in a traffic simulation environment. To study one element of general driver behavior, that of car following, an advanced-instrumented vehicle has been applied in dynamic data collection in real-traffic flow on Swedish roads. This paper briefly introduces the car-following data collection and smoothing methods. Moreover, spectrum analysis methods based on Fourier analysis of car-following data are introduced to estimate driver reaction times, a crucial parameter of driver behavior. A generalized general motor–type model was calibrated, an extension of the classic nonlinear general motor model, in a stable following regime based on estimated driver reaction times. The calibrated model was then evaluated by closed-loop simulations.
Impact of Lane-Change Maneuvers on Congested Freeway Segment Delays
Authors: Coifman Benjamin , Mishalani Rabi , Wang Chao , Krishnamurthy Sivaraman
Published: May 2018

Freeway traffic congestion and associated delays have become a serious problem throughout much of the world. Among factors studied in relation to this congestion, lane-change maneuvers (LCMs) are suspected to be one source of traffic delay. Little empirical research has been done on this topic despite how common the lane-changing process is on multilane roadway segments. Two main problems hinder research: first, it is difficult to distinguish changes in delay caused by LCMs from that of a preexisting delay caused by a queue; second, quantifying LCMs is difficult because it requires both spatial and temporal coverage. This paper presents the concept of delay caused by LCMs and proposes a method to estimate such delays within a given lane relative to the situation in which no LCMs have taken place. This estimation method makes it possible to investigate the impact of LCMs on traffic delays based on vehicle trajectory data, which record the time and location of each vehicle at each instant. This preliminary study shows the effectiveness of the proposed method to estimate delays caused by LCMs and reveals how LCMs affect delays on congested freeway segments.
Failure Detection and Diagnosis in Microsimulation Traffic Models
Authors: Wan Baohong , Rouphail Nagui , Sacks Jerome
Published: May 2018

Effective and feasible procedures for validating microscopic, stochastic traffic simulation models are in short supply. Exercising such microsimulators many times may lead to the occurrence of traffic gridlock (or simulation failures) on some or all replications. Whereas lack of failures does not ensure validity of the simulator for predicting performance, the occurrence of failures can provide clues for identifying deficiencies of the simulation model and invite strategies for model improvement. Failure is defined as a severe malfunction in one or more traffic links on the network where vehicles are unable to discharge for an unusually long period. Such malfunctions can be detected with link-based time traces of vehicle trips. Identifying locations where malfunctions arise requires further spatial analyses. A procedure for identifying whether, when, and where failures occur is described. The simulator CORSIM serves as the test-bed simulator for the proposed methodology, but the procedure is applicable to any comparable microscopic model; real-world traffic networks are simulated as case studies. Possible root causes of detected failures are ( a) flaws in the simulator behavioral algorithms, ( b) improper calibration of inputs, and ( c) capacity problems related to the specific network (for example, when heavy traffic demand projections are simulated). Strategies to identify why failures occur are used in the case studies. The results indicate that the proposed failure detection and diagnosis process is an effective (and essential) way to explore the validity of traffic simulators and find improvements where needed.
Improvement and Evaluation of Cell-Transmission Model for Operational Analysis of Traffic Networks
Authors: Ishak Sherif , Alecsandru Ciprian , Seedah Dan
Published: May 2018

The cell-transmission model (CTM), developed by Daganzo in 1994, has not been fully exploited as an operations model for analysis of large-scale traffic networks. Because of its macroscopic and mesoscopic features, CTM offers calibration and computational advantages over microscopic models. This paper demonstrates specific improvements to the original form of CTM to increase its accuracy and realism of traffic flow representation. These improvements include modifications to provide flexibility in selection of cell lengths, noninteger movements of vehicles between cells, and algorithmic enhancements in the merging and diverging logics. The effect of such improvements on the performance of CTM was evaluated independently and comparatively. A sample freeway network of the I-10 corridor in Baton Rouge, Louisiana, was used to evaluate and compare the performance of the improved version of CTM versus CORSIM under heavily congested traffic conditions. The results showed comparable performance of both platforms in terms of link occupancy (density) and total network travel time.
Piecewise-Linearized Cell Transmission Model and Parameter Calibration Methodology
Authors: Muñoz Laura , Sun Xiaotian , Horowitz Roberto , Alvarez Luis
Published: May 2018

This paper studies the development of macroscopic freeway traffic models and parameter calibration methodologies that are computationally efficient and suitable for use in real-time traffic monitoring and control applications. Toward the fulfillment of these objectives, a macroscopic traffic model, the switching-mode model (SMM), is presented; it is a piecewise-linearized version of Daganzo's cell transmission model (CTM). The observability and controllability properties of the SMM modes are reviewed because these properties are of fundamental importance in the design of traffic estimators and on-ramp metering controllers. A semiautomated method has been developed for calibrating the CTM and SMM parameters. In this method, a least-squares data-fitting approach is applied to loop detector data to determine free-flow speeds, congestion-wave speeds, and jam densities for specified subsections of a freeway. Bottleneck capacities are estimated from measured mainline and on-ramp flows. The calibration method was tested with loop detector data from Interstate 210 westbound (I-210W) in Southern California. The main traffic data source was the performance measurement system. Parameters were calibrated for a 2-mi (3-km) subsection of I-210W and were tested on both the SMM and CTM, which were shown to perform similarly and to reproduce the general behavior of traffic congestion.
Status of the U.S.–Mexico Commercial Border Crossing Process
Authors: Villa Juan C.
Published: May 2018

The commercial border crossing process is an important element of the international transportation and supply-chain systems that influence greatly the national and international economies. Numerous research and analyses have identified issues and problems pertaining to the U.S.–Mexico commercial border crossing. The objective of this paper is to identify issues and problems that relate to the commercial border crossing process along the U.S.–Mexico border and to analyze, classify, and note the status of each issue. A brief description of the northbound commercial border crossing, the recently implemented security programs at the border, and the status of opening the border to Mexican trucks provide a background that facilitates the understanding of current conditions at commercial ports of entry. From the vast list of information on commercial border crossings, this paper presents a selection of reports and classifies issues and notes the status or change in the situation of each issue. Even though progress has been made in the past decade to improve the commercial border crossing process, information and data, interagency coordination, and binational cooperation are issues that still require attention and solution.
Freight Villages
Authors: Ballis Athanasios
Published: May 2018

Freight villages reflect a modern way of organizing logistics, transport, and goods distribution activities. Warehouses are a basic element in such building complexes, and their efficient planning and operation is essential for the viability of the system. Warehouse design requires a mixture of analytical skills and creativity. Although effort has been dedicated to defining a global methodological design framework, the most scientific papers on the subject address well-defined, isolated problems. A practitioner may notice, however, that many warehouses offering efficient, cost-effective services are in operation and that several warehouse design manuals exist that tackle aspects of design and operation. Investigating academic and pragmatic points of view, this paper is an attempt to present an overall view of the facility layout and warehouse design problem, and it introduces the analysis and results of the preliminary design phase of a new freight village where issues related to facilities layout, warehouse sizing, and rail connections have been considered.
Analysis and Evaluation of Incentive-Compatible Dynamic Mechanisms for Carrier Collaboration
Authors: Figliozzi Miguel Andres
Published: May 2018

This paper introduces a framework for carrier dynamic collaboration. In particular it proposes and analyzes dynamic collaborative mechanisms that are incentive compatible. The dynamic collaborative environment is characterized by a set of carriers that have a proprietary set of customers that generate a stream of random demands over time. The proposed collaborative mechanism is such that on each demand arrival each carrier has the incentive to submit the arrived shipment or service request to the collaborative mechanism. Intuition about the efficiency and the workings of the collaborative mechanism is developed. A general framework to formulate and study collaborative frameworks among transportation carriers is proposed. A truckload pickup-and-delivery collaborative environment is simulated, and results are analyzed.
Commodity Distribution Model Incorporating Spatial Interactions for Urban Freight Movement
Authors: Wisetjindawat Wisinee , Sano Kazushi , Matsumoto Shoji
Published: May 2018

The commodity distribution model proposed in this paper is developed in such a way that the movement of commodities is explained as an outcome of their flow through several freight agents in a supply chain. As commodity flow is fundamentally determined by demand, the proposed model was developed from a discrete choice model that considered the individual behavior of a customer to decide the suppliers from which to purchase and the amount of commodity to acquire from each of them. The model not only takes into account the interplay between shipper and customer in a supply chain but also captures the spatial interactions among alternatives and among customers, because spatial effects generally affect customer preference. In this study, several model specifications were developed and compared, with and without incorporating spatial interactions. The empirical results of the model, which were applied to analyze the urban commodity distribution in the Tokyo metropolitan area, indicate that integrating both spatial interactions among alternatives and among customers statistically improves the model's performance.
Effectiveness of Financial Incentives for Off-Peak Deliveries to Restaurants in Manhattan, New York
Authors: Holguín-Veras José , Pérez Noel , Cruz Brenda , Polimeni John
Published: May 2018

The fundamental tenet of this paper is that moving deliveries by trucks to off-peak hours requires the implementation of comprehensive policies targeting the critical components of the supply-chain process. This is so because by far the most decisions concerning time of travel of commercial trucks in urban areas are either made by the receivers or made jointly by the receiver and the carrier. In this context, without receivers able and willing to accept off-peak deliveries, the ability of trucking companies to move out of normal hours is severely hampered. This paper analyzes the receptiveness of an important group of receivers, the restaurant sector in Manhattan, New York City, to policies aimed at fostering off-peak deliveries. This study focused on restaurants for several reasons. First, in-depth interviews with private-sector executives indicated that the restaurant sector could be a good candidate for off-peak deliveries. Second, and more important, the relatively high number of restaurants and drinking places in Manhattan (exceeding 6,500 establishments) generates an estimated minimum of 20,000 truck trips per day. These numbers suggest there would be a significant payoff if a significant portion of these truck trips were switched to the off-peak hours. The analyses are based on a small attitudinal survey used to evaluate the effectiveness of four different policies involving financial incentives to the restaurants accepting off-peak deliveries. Despite the small sample size, the key findings from these analyses are consistent with the estimates from behavioral models based on a larger data set. These preliminary results show that financial incentives may be effective in fostering off-peak deliveries.
Estimating Traffic Changes and Pavement Impacts from Freight Truck Diversion following Changes in Interstate Truck Weight Limits
Authors: Fortowsky J. Keith , Humphreys Jennifer
Published: May 2018

This paper reports on two methodologies that were developed and used in a study for the State of Maine. The study examined the pavement, crash, and bridge costs of higher truck weight limits being allowed on an Interstate route. These higher weight limits would attract to the Interstate route high-weight (between 80,000 and 100,000 lb gross vehicle weight) combination trucks that currently use alternative routes on Maine state roads (which already allow these higher weight limits). The first methodology estimated the changes in freight truck traffic volumes. The methodology estimates gains and losses in vehicle miles traveled by route and by vehicle configuration and the associated gains and losses in equivalent single-axle loads (ESALs) on these routes. The second methodology estimated road cost per ESAL by road type; this allows pavement costs to be derived from the ESAL effects estimated by the first methodology. The data used for the methodologies included TRANSEARCH data, weigh-in-motion station data, traffic classification count data, and the Maine Department of Transportation's TIDE road database system. The traffic estimation methodology used successive (iterative) rounds of expert opinion derived through interviews, data analysis, and route mapping. This paper also discusses the key role of an evolving picture of the system within the analysis team.
Estimating Freight Transportation System Capacity, Flexibility, and Degraded-Condition Performance
Authors: Sun Yao , Turnquist Mark A. , Nozick Linda K.
Published: May 2018

This paper extends previous models of rail freight system capacity and capacity flexibility in three important ways. First, uncertainty in the future traffic pattern is included; second, volume–delay functions and a level-of-service constraint are added to represent deterioration of service quality as capacity limits in individual facilities are approached; and third, a stochastic traffic assignment procedure is added to eliminate the need for path enumeration and to make the model more useful for large networks. These enhancements make the model suitable for use in the assessment of the performance of a freight network under conditions in which individual links or terminals have degraded capacity. An illustration of the model as applied to the intermodal double-stack container network in the western United States indicates the improved estimates of capacity and capacity flexibility that the model provides.
Assessing Adequacy of America's Transportation Policies
Authors: Gordon Cameron
Published: May 2018

This paper compares and contrasts two debates about the role of transportation in the American economy. The contemporary policy debate revolves around adequacy of current transportation infrastructure, whether infrastructure investment should be increased, and how and whether congestion should be addressed by public policy. An earlier debate in the economic history field revolved around whether the railroads were indispensable to America's economic growth and how the building of a rail network affected the shape of that growth. This paper argues that in certain ways the contemporary policy exchange is covering much of the same ground covered by analysts studying the railroads and that the former can be usefully informed by the latter.
Virtual Commercial Vehicle Compliance Stations
Authors: Rodier Caroline J. , Shaheen Susan A. , Cavanagh Ellen
Published: May 2018

In the past 5 years, commercial vehicle travel has increased 60% on California's highways, without a corresponding increase in compliance inspection station capacity or enforcement officers. Commercial vehicles that do not comply with regulations impose significant costs on the public (e.g., costs due to pavement and structural damage to roads and catastrophic crashes). In response to these problems, the California Department of Transportation is investigating the potential application of detection and communication technology in virtual compliance stations (VCS) to improve enforcement of commercial vehicle regulations cost-effectively. This study begins with a description of the fledgling VCS research programs in North America as well more advanced international programs. Next, the results of expert interviews with key officials involved in the North American VCS programs in Kentucky, Florida, and Indiana in the United States and in Saskatchewan, Canada, are reported. This is followed by an analysis of institutional barriers to VCS implementation based on the evaluation literature on commercial vehicle electronic pre-screening and red-light and speeding automated enforcement programs. The paper concludes with some key recommendations to address legal and institutional barriers to VCS deployment in the United States.