Vehicle sorting for platoon formation: Impacts on highway entry and throughput

Automated highway systems (AHS) are intended to increase the throughput and safety of roadways through computer control, communication and sensing. In the “platoon” concept for AHS, vehicles travel on highways in closely spaced groups. To maximize benefits, it is desirable to form platoons that are reasonably large (five or more vehicles), and it is also desirable to ensure that platoons remain intact for considerable distances. This paper develops and evaluates strategies for organizing vehicles into platoons at highway entrances, with the objective of maximizing the distance that platoons stay intact, so that they do not need to be regrouped into new platoons on the highway itself. Fundamentally, this entails grouping vehicles according to their destination. We evaluate various strategies in which vehicles are sorted on entrance ramps, with respect to platoon sizes, throughput and platoon formation time.     

Observing freeway ramp merging phenomena in congested traffic

This work conducts a comprehensive investigation of traffic behavior and characteristics during freeway ramp merging under congested traffic conditions. On the Tokyo Metropolitan Expressway, traffic congestion frequently occurs at merging bottleneck sections, especially during heavy traffic demand. The Tokyo Metropolitan Expressway public corporation, generally applies different empirical strategies to increase the flow rate and decrease the accident rate at the merging sections. However, these strategies do not rely either on any behavioral characteristics of the merging traffic or on the geometric design of the merging segments. There have been only a few research publications concerned with traffic behavior and characteristics in these situations. Therefore, a three‐year study is undertaken to investigate traffic behavior and characteristics during the merging process under congested situations. Extensive traffic data capturing a wide range of traffic and geometric information were collected using detectors, videotaping, and surveys at eight interchanges in Tokyo Metropolitan Expressway. Maximum discharged flow rate from the head of the queue at merging sections in conjunction with traffic and geometric characteristics were analyzed. In addition, lane changing maneuver with respect to the freeway and ramp traffic behaviors were examined. It is believed that this study provides a thorough understanding of the freeway ramp merging dynamics. In addition, it forms a comprehensive database for the development and implementation of congestion management techniques at merging sections utilizing Intelligent Transportation System.     

A recursive, cell processing model for predicting freeway travel times

Travel time information influences driver behaviour and can contribute to reducing congestion and improving network efficiency. Consequently many road authorities disseminate travel time information on road side signs, web sites and radio traffic broadcasts. Operational systems commonly rely on speed data obtained from inductive loop detectors and estimate travel times using simple algorithms that are known to provide poor predictions particularly on either side of the peak period. This paper presents a new macroscopic model for predicting freeway travel times which overcomes the limitations of operational ‘instantaneous’ speed models by drawing on queuing theory to model the processing of vehicles in sections or cells of the freeway. The model draws on real-time speed, flow and occupancy data and is formulated to accommodate varying geometric conditions, the relative distribution of vehicles along the freeway, variations in speed limits, the impact of ramp flows and fixed or transient bottlenecks. Field validation of the new algorithm was undertaken using data from two operational freeways in Melbourne, Australia. Consistent with the results of simulation testing, the validation confirmed that the recursive model provided a substantial improvement in travel time predictions when compared to the model currently used to provide real-time travel time information to motorists in Melbourne.     

Developing control strategies for freeway merging points under congested traffic situations using modeling and a simulation approach

This work focuses on developing a variety of strategies for alleviating congestion at freeway merging points as well as improving the safety of these points. On the Tokyo Metropolitan Expressway, traffic congestion frequently occurs at merging bottleneck sections, especially during heavy traffic demand. The Tokyo Metropolitan Expressway public corporation, generally applies different empirical strategies to increase the flow rate and decrease the accident rate at the merging sections. However, these strategies do not rely either on any behavioral characteristic of the merging traffic or on the geometric design of the merging segments. There have been only a few research publications concerned with traffic behavior and characteristics in these situations. Therefore, a three‐year extensive study has been undertaken to investigate traffic behavior and characteristics during the merging process under congested situations in order to design safer and less congested merging points as well as to apply more efficient control at these bottleneck sections. Two groups of strategies were investigated in this study. The First group was related to the traffic characteristics, and the second group to the geometric characteristics. In the first group, the control strategies related to closure of freeway and ramp lanes as well as lane‐changing maneuver restriction were investigated through a simulation program, detector data, and field experiment. In the second group, the angle of convergence of the ramp with the freeway in relation to merging capacity was analyzed using a simulation program. Results suggested the potential benefits of using proposed strategies developed in this work and can serve as initial guidance for the reduction of delay and improvement of safety under congested traffic conditions.     

Methods of dropping auxiliary lanes at freeway weaving segments

Auxiliary lanes connecting freeway entrance and exit ramps provide additional space for entering and exiting vehicles to change lanes. The method of dropping auxiliary lanes is critical in the design of freeway auxiliary lanes. This study investigates the performance of different methods of dropping auxiliary lanes. Case studies were conducted at two selected freeway segments with successive entrance or exit ramps in the City of Houston. Traffic simulation analysis results of these two case studies show that additional operational benefits can be achieved by extending an auxiliary lane beyond the freeway weaving segment. The study also found that if the weaving segment is followed by an entrance/exit ramp and this ramp has high traffic volume, it can be less operationally favorable to extend and terminate the auxiliary lane at this entrance/exit ramp location. Instead, dropping the auxiliary lane before this entrance/exit ramp represents a more operationally effective option.     

Distributed MPC for cooperative highway driving and energy-economy validation via microscopic simulations

Traffic congestion and energy issues have set a high bar for current ground transportation systems. With advances in vehicular communication technologies, collaborations of connected vehicles have becoming a fundamental block to build automated highway transportation systems of high efficiency. This paper presents a distributed optimal control scheme that takes into account macroscopic traffic management and microscopic vehicle dynamics to achieve efficiently cooperative highway driving. Critical traffic information beyond the scope of human perception is obtained from connected vehicles downstream to establish necessary traffic management mitigating congestion. With backpropagating traffic management advice, a connected vehicle having an adjustment intention exchanges control-oriented information with immediately connected neighbors to establish potential cooperation consensus, and to generate cooperative control actions. To achieve this goal, a distributed model predictive control (DMPC) scheme is developed accounting for driving safety and efficiency. By coupling the states of collaborators in the optimization index, connected vehicles achieve fundamental highway maneuvers cooperatively and optimally. The performance of the distributed control scheme and the energy-saving potential of conducting such cooperation are tested in a mixed highway traffic environment by the means of microscopic simulations.     

Creating complex congestion patterns via multi-objective optimal freeway traffic control with application to cyber-security

This article presents a study on freeway networks instrumented with coordinated ramp metering and the ability of such control systems to produce arbitrarily complex congestion patterns within the dynamical limits of the traffic system. The developed method is used to evaluate the potential for an adversary with access to control infrastructure to enact high-level attacks on the underlying freeway system. The attacks are executed using a predictive, coordinated ramp metering controller based on finite-horizon optimal control and multi-objective optimization techniques. The efficacy of the control schemes in carrying out the prescribed attacks is determined via simulations of traffic network models based on the cell transmission model with onramps modeled as queue buffers. Freeway attacks with high-level objectives are presented on two illustrative examples: congestion-on-demand, which aims to create precise, user-specified pockets of congestion, and catch-me-if-you-can, which attempts to aid a fleeing vehicle from pursuant vehicles.     

Multi-destination traffic flow control in automated highway systems

Traffic flow control in automated highway systems (AHS) is addressed. A link layer controller for a hierarchical AHS architecture is presented. The controller proposed in this paper stabilizes the vehicular density and flow around predetermined profiles in a stretch of highway using speed and lane changes as control signals. Multiple lane highways in which vehicles have different destinations and types are considered. The control laws are derived from a model based on a principle of vehicle conservation and Lyapunov stability techniques. The implementation requires only local information. Simulation results are presented.     

Spatiotemporal evolution of China’s railway network in the 20th century: An accessibility approach

The interrelatedness of transportation development and economic growth has been a constant theme of geographic inquiries, particularly in economic and transportation geography. This paper analyzes the expansion of China’s railway network, the evolution of its spatial accessibility, and the impacts on economic growth and urban systems over a time span of about one century (1906–2000). First, major historical events and policies and their effects on railway development in China are reviewed and grouped into four major eras: preliminary construction, network skeleton, corridor building, and deep intensification. All four eras followed a path of “inland expansion.” Second, spatial distribution of accessibility and its evolution are analyzed. The spatial structure of China’s railway network is characterized by “concentric rings” with its major axis in North China and the most accessible city gradually migrating from Tianjin to Zhengzhou. Finally, the study indicates that railway network expansion has significantly improved economic development and heavily influenced the formation of urban systems in China.     

Patterns and projections of technical development in freeway surveillance and control in the U.S.A.

This paper explores the historical trends in freeway traffic management technology in the U.S., and the most likely projections for the coming two decades. First, existing computer‐supervised freeway surveillance and control techniques are reviewed with particular emphasis on the scientific and technological landmarks which has led to the evolution of these techniques. Next, the major underlying trends which bear on the future of automated freeway surveillance and control are identified. Finally, extrapolative projections are made to determine the most likely future of this technology. The paper concludes with implications for the issues of meeting short‐term transportation needs of urban areas through more efficient use of existing transportation facilities.     

Queue length estimation at metered freeway‐to‐freeway connectors

Freeway‐to‐freeway connector metering is a cost‐effective and proven freeway management strategy for relieving recurrent congestion. However, one of the critical challenges in design and operation of freeway‐to‐freeway connector metering is the lack of up‐to‐date queue storage length design guidance. In this study, it was found that ramp queue is dynamically related to the metering rate, on‐ramp demand, and traffic flow arrival pattern. Hence, simply using an average demand cannot provide accurate queue length estimation and is also not suitable for queue storage design where the maximum or a percentile queue length is generally used. A mesoscopic queue length simulation model was developed based on the input–output method for estimating queue lengths under various demand‐to‐capacity ratio scenarios. Simulation results indicate that for under‐saturated situations, the ramp queue may exist temporally due to the random short‐term surge of traffic arrivals, and the exponential function could best capture the relationship between queue length and demand‐to‐capacity ratio. For over‐saturated situations, the ramp queue tends to prolong linearly with the demand‐to‐capacity ratio. Based on the simulation, it was recommended that queue storage length be designed as 4.3% of on‐ramp demand when demand is lower than 1200 vph or 2.3% when demand is between 1200 and 2400 vph. Copyright © 2016 John Wiley & Sons, Ltd.     

Ramp meters on trial: Evidence from the Twin Cities metering holiday

Ramp meters in the Twin Cities have been the subject of a recent test of their effectiveness, involving turning them off for eight weeks. This paper analyzes the results with and without ramp metering for several representative freeways during the afternoon peak period. Seven performance measures: mobility, equity, productivity, consumers’ surplus, accessibility, travel time variation and travel demand responses are compared. It is found that ramp meters are particularly helpful for long trips relative to short trips. Ramp metering, while generally beneficial to freeway segments, may not improve trip travel times (including ramp delays). The reduction in travel time variation comprises another benefit from ramp meters. Non-work trips and work trips respond differently to ramp meters. The results are mixed, suggesting a more refined ramp control algorithm, which explicitly considers ramp delay, is in order.     

The mobility and accessibility expectations of seniors in an aging population

Populations of post-industrial nations are aging. With a growing number of people living well into their 80s and maintaining active lives, the transportation system will have to start focussing more closely on understanding their mobility and accessibility needs, so as to ensure that specific requirements of this large segment are not being ignored through the promotion of traditional ‘solutions’ and historical assumptions. This paper takes a close look at the evidence on the mobility needs and travel patterns of individuals over 64, distinguishing between the “young” elderly (aged 65–75 years) and the “old” elderly (over 75 years). This distinction is particularly useful in recognising the threshold of health change that impacts in a non-marginal way on mobility needs. This distinction also focuses transport planning and policy on a commitment to understanding the different needs of these sub-groups of the population, identifying services and facilities that better cater for these groups. We review the evidence, in particular, on the mobility characteristics of the over 75 years age group, including how they secure support through migration and settlement patterns. We use the empirical evidence from a number of western nations to identify the role of conventional and specialised public transport as an alternative to the automobile in meeting mobility and accessibility needs.     

Congestion relief toll tunnels

Changing urban land-use patterns have reduced the importance of traditional downtowns as the origin and destination of numerous vehicular trips. Much traffic on downtown-area freeways seeks merely to get past downtown, thereby worsening the level of congestion for those seeking access to downtown.A number of European cities have begun to develop a new type of transportation facility: congestion-relief toll tunnels in downtown areas. These projects appear to be economically feasible largely or entirely from premium-price tolls paid by users. Hence, they are being developed by private consortia, operating under long-term franchises from government. Other keys to the feasibility of such projects are peak/off-peak pricing structures (congestion pricing), nonstop electronic toll collection, and restriction of use to auto-size vehicles only (to reduce tunnel dimensions and therefore capital investment).Preliminary analysis indicates that congestion-telief bypass runnels for downtown Los Angeles and San Francisco would be economically feasible as private business ventures, if developed along European lines. Similar approaches might be applied to other controversial freeway projects in both cities, and to restructuring Boston's huge and controversial Central Artery/Tunnel project.Congress has already authorized public-private partnerships of this type, permitting private capital and private owner/operation to be used, both for new projects and to rebuild existing highway, bridge, and tunnel facilities. Six states and Puerto Rico have enacted private-tollway legislation under which such projects could be developed and operated.This type of project should be politically feasible, since it offers a way to make significant transportation improvements in impacted downtowns with little or no public funding. While transit proponents may oppose the construction of toll tunnels, highway users are likely to support such projects, and some environmental groups may support this method of implementing congestion pricing in urban areas, because of its potential for reducing air emissions.     

Merging bus routes in Hong Kong’s central business district: Analysis and models

A significant portion of the 200,000 people working in Hong Kong’s central business district (CBD) relies on buses as their primary means of transport. During peak hours, nearly a thousand double-decker buses pour into a tiny area of 150 ha. This causes traffic congestion and air pollution. Moreover, given that the flow is uni-directional (into the CBD in the morning and out of the CBD in the afternoon), the occupancy of buses in the CBD is actually low.In this paper, we propose to reduce traffic congestion and to increase bus occupancy by merging bus routes. We describe the peculiar situation of the CBD in Hong Kong and explain the necessary conditions for the possible success of merging routes. Our analysis shows that merging will lead to an overall benefit for all parties, including government, bus operators, and passengers. The actual merging decisions, which routes to merge and at what frequencies buses should run, are determined by a mathematical model. The model also shows quantitatively the benefits of merging routes and the impacts of other factors. The procedure that we follow and the model that we adopt can be applied to other CBD.     

A combined land use-transportation model when zonal travel demand is endogenously determined

A combined transportation-land use model is proposed in this paper. Unlike other existing urban land use and transportation planning models in which a “fixed demand” for services is assumed to be known at the zonal level of an urban area, zonal travel demand is endogenously determined together with link congestion costs, optimal amounts of production and resulting efficient densities of land uses, once the transportation network is given. Some characteristics of alternative solutions are demonstrated. The proposed model represents progress over previous efforts in combining land use-transportation problems since the travel choice as to origin, destination and routes as well as amounts of goods to be produced at the optimal density of land uses are integrated into a consistent mathematical programming framework.     

Understanding the variability of speed distributions under mixed traffic conditions caused by holiday traffic

Understanding the variability of speed patterns and congestion characteristics of interstate freeway systems caused by holiday traffic is beneficial because appropriate countermeasures for safety improvement and congestion mitigation can be prepared and drivers can avoid traffic congestion and change their holiday travel schedules. This study evaluated the traffic congestion patterns during the Thanksgiving holiday period in 2006 using a Gaussian mixture speed distribution estimated by the Expectation–Maximization (EM) algorithm. This mathematical approach showed the potential of improving freeway operational performance evaluation schemes for holiday periods (even non-holiday periods). This study suggested that a Gaussian mixture model using the EM algorithm could be used to properly characterize the severity and the variability of congestion on certain interstate roadway systems. However, this study also pointed out that the fundamental limitations of the mixture model and the statistical significance test about the mixture components should be well understood and need to be further investigated. In addition, because this study investigated the changing patterns of speed distributions with only one interstate freeway system, I-95 northbound, other freeway systems with both directions need to be evaluated so that a more broad and confident analysis on holiday traffic can be achieved.     

Evaluation of forced flows on freeways with single‐loop detectors

This paper documents the development of a simple method for identifying and/or predicting freeway congestion using single loop detection systems. The proposed algorithm is simple and easy to incorporate into most freeway management systems. The Washington State Department of Transportation's Traffic Systems Management Center (TSMC) sponsored the original study. The investigation also led to a recommendation to replace the original TSMC definition of congestion or forced flow conditions with a more reliable indicator. Although, the TSMC has recently implemented a more advanced prediction system based on fuzzy set theory and neural networks to further identify patterns and rules for ramp metering strategies, the findings presented here continue to be constructive to freeway managers looking for quick and easy analyses that rely solely on single‐loop detection systems. The Seattle Area freeway study section used for the original study was the portion of mainline 1–5 northbound starting at the downtown Seattle Station 108 and ending at the Mountlake Terrace Station 193. Several days' worth of volume and lane‐occupancy data were collected for the afternoon time period from 2:30 p.m. to 6:30 p.m. Time intervals of 20 seconds were chosen for each data collection period. Important products of this research include the following:

• simple, and more reliable criterion for the definition of “bottleneck” or forced flow conditions than that originally used by the TSMC.
• simple, and reliable criterion for predicting impending “bottlenecks” or forced flow conditions.
• A proposed variable for improved selection of the appropriate metering rate. (Further analysis of the use of this variable for determining metering rates is recommended for future studies.

The proposed criteria are simple and easy to incorporate into current freeway management computer systems. Further investigation of freeway performance measurement using volume and occupancy data obtained from single‐loop systems is currently being performed.     

Modeling the effects of congestion on fuel economy for advanced power train vehicles

Fuel-speed curves (FSC) are used to account for the aggregate effects of congestion on fuel consumption in transportation scenario analysis. This paper presents plausible FSC for conventional internal combustion engine (ICE) vehicles and for advanced vehicles such as hybrid electric vehicles, fully electric vehicles (EVs), and fuel cell vehicles (FCVs) using a fuel consumption model with transient driving schedules and a set of 145 hypothetical vehicles. The FSC shapes show that advanced power train vehicles are expected to maintain fuel economy (FE) in congestion better than ICE vehicles, and FE can even improve for EV and FCV in freeway congestion. In order to implement these FSC for long-range scenario modeling, a bounded approach is presented which uses a single congestion sensitivity parameter. The results in this paper will assist analysis of the roles that vehicle technology and congestion mitigation can play in reducing fuel consumption and greenhouse gas emissions from motor vehicles.     

Machine learning for multi-jurisdictional optimal traffic corridor control

Urban traffic corridors are often controlled by more than one agency. Typically in North America, a state of provincial transportation department controls freeways while another agency at the municipal or city level controls the nearby arterials. While the different segments of the corridor fall under different jurisdictions, traffic and users know no boundaries and expect seamless service. Common lack of coordination amongst those authorities due to lack of means for information exchange and/or possible bureaucratic ‘institutional grid-lock’ could hinder the full potential of technically-possible integrated control. Such institutional gridlock and related lack of timely coordination amongst the different agencies involved can have a direct impact on traffic gridlock. One potential solution to this problem is through integrated automatic control under intelligent transportation systems (ITS). Advancements in ITS and communication technology have the potential to considerably reduce delay and congestion through an array of network-wide traffic control and management strategies that can seamlessly cross-jurisdictional boundaries. Perhaps two of the most promising such control tools for freeway corridors are traffic-responsive ramp metering and/or dynamic traffic diversion possibly using variable message signs (VMS). Technically, the use of these control methods separately might limit their potential usefulness. Therefore, integrated corridor control using ramp metering and VMS diversion simultaneously might be synergetic and beneficial. Motivated by the above problem and potential solution approach, the aim of the research presented in this paper is to develop a self-learning adaptive integrated freeway-arterial corridor control for both recurring and non-recurring congestion. The paper introduces the use of reinforcement learning, an Artificial Intelligence method for machine learning, to provide optimal control using ramp metering and VMS routing in an integrated agent for a freeway-arterial corridor. Reinforcement learning is an approach whereby the control agent directly learns optimal strategies via feedback reward signals from its environment. A simple but powerful reinforcement learning method known as Q-learning is used. Results from an elaborate simulation study on a key corridor in Toronto are very encouraging and discussed in the paper.