An optimal global algorithm for route guidance in advanced traveler information systems

ABSTRACTVariable message signs that provide various types of route guidance information have been widely deployed in large cities. To release proper information only using easily collected data, a simple traffic-condition-based (TCB) route guidance strategy was recently proposed. The strategy works based on the estimation of free-flow and congested traffic conditions and is capable of approximating user optimal equilibrium stably. Due to little consideration of the complexity of urban road networks, the TCB strategy is still away from field applications in urban areas. To further push the strategy toward field tests, this article improves the TCB strategy in the following aspects: supplementing the strategy with a self-regulation ability by considering existing traffic conditions; decomposing link capacity to solve the problem of overlapping routes by comparing link capacity on alternative routes; coping with stochastic traffic; and the impact of signalized intersections by utilizing aggregated data. A scenario for an urban road network in Beijing, China, is simulated to test the improved strategy, and the simulation results clearly indicate the effectiveness of the proposed improvements. The improvements extend the TCB strategy on moderately complicated urban road networks, and still have the advantages of simple diversion rules, easily obtained input data, and stable and effective diversion processes.

Transportation-based Cyber-Physical Systems (TCPS), also known as Intelligent Transportation Systems (ITS), have been introduced to increase traffic efficiency and safety. To reduce traffic congestion and traveling time, a number of real-time route guidance schemes have been developed to assist travelers in determining the optimal route for their transit. In this paper, we address the vulnerability issue of the route guiding process and study data integrity attacks against route guidance schemes. To be specific, we consider a generic attack, in which the adversary may compromise vehicles via wireless communication networks and then manipulate the real-time traffic information generated or forwarded by these vehicles, and finally broadcast the forged real-time traffic information into vehicular networks. We formally model the attack and quantitatively analyze its impact on the effectiveness of route guidance schemes. Our findings show that the investigated data integrity attack can effectively disrupt route guidance, resulting in significant traffic congestion, the increase of travel time, and the imbalanced use of transportation resources.

Speech recognition technology has potential for application to intelligent transportation systems (ITS) in the area of advanced traveler information systems (ATIS). ATIS areas which can greatly benefit from speech recognition are: pre-trip traffic information; en-route traffic information; route guidance; ride matching and reservation; transit information services; and traffic and transit management control centers. This paper concentrates on telephony applications of speech recognition to two ATIS applications, real-time traffic information and public transit information. We first discuss the general considerations involved in development of a multiline speech interface to a traffic or transit database, including system architecture and sizing, and the development of dialogs and grammars which are user friendly and efficient. We then discuss two prototype applications of this technology using BBN's HARK speaker-independent speech recognition product. The first is to SmartRoute System's SmarTraveler traveler information system, which was an FHWA Operational Test, and the second to Montgomery County Maryland's public transit system. These were small scale tests to help us develop the technology required for full-scale implementations, but showed that the speech interface was practical, and provided much improved ease of use and performance over conventional touch tone based interactive voice response (IVR) systems.

Modeling the benefits of advanced traveler information systems in corridors with incidents

The concepts of human information processing provide design recommendations for advanced traveler information systems (ATISs). A driver’s information processing model for the ATIS environment is proposed. This qualitative model explicitly depicts how drivers process ATIS information, from the moment it is received until a decision is made in response to the information. The model is supported by data collected with a driving simulator. The results of the driving simulator study indicate that, because of the limitations of human memory, drivers prefer to have short, simple ATIS information conveyed to them whenever the circumstance allows. Furthermore, drivers do not always need or want visually displayed information (e.g., an electronic map) to assist them in route navigation. In unfamiliar traffic networks, a motorist’s propensity to change routes is strongly correlated to the quality of ATIS information being processed. With the right amount of traffic information presented using an effective conveyance method, more drivers are likely to accept and use ATIS information and divert to alternate routes. The challenge for ATIS designers is to provide options that are acceptable to ATIS users.

Suppose that in an urban transportation network there is a specific advanced traveler information system (ATIS) which acts for reducing the drivers' travel time uncertainty through provision of pre‐trip route information. Because of the imperfect information provided, some travelers are not in compliance with the ATIS advice although equipped with the device. We thus divide all travelers into three groups, one group unequipped with ATIS, another group equipped and in compliance with ATIS advice and the third group equipped but without compliance with the advice. Each traveler makes route choice in a logit‐based manner and a stochastic user equilibrium with multiple user classes is reached for every day. In this paper, we propose a model to investigate the evolutions of daily path travel time, daily ATIS compliance rate and yearly ATIS adoption, in which the equilibrium for every day's route choice is kept. The stability of the evolution model is initially analyzed. Numerical results obtained from a test network are presented for demonstrating the model's ability in depicting the day‐to‐day and year‐to‐year evolutions.

An emerging application of mobile computing and communication is the delivery of information related to the transportation system to drivers and travelers. Such real-time information would be very valuable in providing services such as pre-trip planning, route guidance, intermodal transportation, yellow pages, and ride matching and reservation. This so-called advanced traveler information system (ATIS) is an important subset of an intelligent transportation system (ITS). The authors are developing an ATIS operational field test called SWIFT (Seattle wide-area information for travelers) in the Seattle metropolitan area which uses technological advances in wireless communication, personal digital assistants (PDA), and traffic modeling and analysis. SWIFT uses an advanced 19 kbps FM subcarrier broadcast medium for the delivery of transportation information as well as personal paging information. Preliminary description of the logical and physical architecture of the SWIFT system along with communication loading analysis for this system, are presented.

Traffic management and route guidance are optimization problems by nature. In this article, we consider algorithms for centralized route guidance and discuss fairness aspects for the individual user resulting from optimal route guidance policies. The first part of this article deals with the mathematical aspects of these optimization problems from the viewpoint of network flow theory. We present algorithms which solve the constrained multicommodity minimum cost flow problem (CMCF) to optimality. A feasible routing is given by a flow x, and the cost of flow x is the total travel time spent in the network. The corresponding optimum is a restricted system optimum with a globally controlled constrained or fairness factor L > 1. This approach implements a compromise between user equilibrium and system optimum. The goal is to find a route guidance strategy which minimizes global and community criteria with individual needs as constraints. The fairness factor L restricts the set of all feasible routes to the subset of acceptable routes. This might include the avoidance of routes which are much longer than shortest routes, the exclusion of certain streets, preferences for scenic paths, or restrictions on the number of turns to be taken. Most remarkably is that the subset of acceptable routes can also be interpreted as a mental map of routes. In the second part we apply our CMCF algorithms in a large scale multi-agent transportation simulation toolkit, which is called MATSIM-T. We use as initial routes the ones computed by our CMCF algorithms. This choice of initial routes makes it possible to exploit the optimization potential within the simulation much better then it was done before. The result is a speed up of the iteration process in the simulation. We compare the existing simulation toolkit with the new integration of CMCF to proof our results.

In transportation-based cyberphysical systems (TCPS), also known as intelligent transportation systems (ITS), to increase traffic efficiency, a number of dynamic route guidance schemes have been designed to assist drivers in determining optimal routes for their travels. To determine optimal routes, it is critical to effectively predict the traffic condition of roads along the guided routes based on real-time traffic information collected by vehicular networks to mitigate traffic congestion and improve traffic efficiency. In this paper, we propose a Dynamic En-route Decision real-time Route guidance (DEDR) scheme to effectively mitigate road congestion caused by the sudden increase of vehicles and to reduce travel time and fuel consumption. DEDR considers real-time traffic information generation and transmission by vehicular networks. Based on the shared traffic information, DEDR introduces the trust probability to predict traffic conditions and to dynamically, en route, determine alternative optimal routes. DEDR also considers multiple metrics to comprehensively assess traffic conditions so that drivers can determine the optimal route with a preference to these metrics during travel. DEDR considers effects of external factors (bad weather, incidents, etc.) on traffic conditions as well. Through a combination of extensive theoretical analysis and simulation experiments, our data show that DEDR can greatly increase traffic efficiency in terms of time efficiency, balancing efficiency, and fuel efficiency, in comparison with existing schemes.

Effects of route guidance strategies on traffic emissions in urban traffic networks

This report describes the results of an on-road study that examined how Advanced Traveler Information Systems (ATIS) information influences driver behavior. The objective of the study was to develop ATIS design guidelines, primarily for In-Vehicle Signing and Information Systems (ISIS) and In-Vehicle Safety Advisory and Warning Systems (IVSAWS), to define the amount and format of information that can safely be displayed in an ATIS. A general issue facing ATIS designers is to determine how much information can safely be presented in an ATIS. This study investigated rates of one, two, or three message presentations per minute. No effects of information density were observed on driving performance. Another general issue that faces ATIS designers is how message potency (i.e., message style and display modality) affects driving safety and compliance with ATIS messages. Message potency is shown to have an important effect on both compliance and driving safety, confirming previous findings on how particular ATIS design characteristics can undermine driving safety by fostering an over-reliance on ATIS information. Also investigated in this study was whether advance notification messages that warn drivers of upcoming route guidance instructions are helpful. The results show that the drivers make use of advance notification messages to prepare for upcoming turns.

The passenger’s motion behavior during the check-in process will directly influence the check-in efficiency. However, little effort has been made to study this topic. This paper incorporates the passenger’s motion behavior into the route guidance strategy to enhance the check-in efficiency. Firstly, an extended social force (SF) model is developed to describe each passenger’s movement at an airport terminal. Secondly, a route guidance strategy accounting for the flight’s remaining departure time and the passenger density is designed to enhance the passengers’ check-in efficiency. Thirdly, a greedy algorithm is designed to search an optimal route for each passenger during the check-in process. Finally, the check-in process of one flight at an airport terminal is selected to testify the extended SF model and the proposed route guidance strategy. The simulation results show that (i) the extended SF model can reasonably describe the motion behavior of each passenger, and (ii) the proposed route-guidance strategy can enhance the check-in efficiency under passengers’ state described by the extend SF model. The results can guide administrators to better organize and manage the check-in process.

Traveler-Oriented Advanced Traveler Information System based on Dynamic Discovery of Resources: Potentials and Challenges

The paper formulates risk taking behavior over general queing network with advanced traveler information systems (ATIS). It supposes that drivers equipped with ATIS will make their choices based on the complete information about travel time and its possible variations, while drivers without ATIS have to choose based on their past experience and subjective understandings. The mixed behavior time dependent equilibrium problem is formulated as a nonlinear complementarity problem and a heuristic route/time swapping approach is proposed to solve the problem. Also investigated is the implementation of ATIS on a toy network under varied values of market penetration.

An evaluation study of the Smart Traveler Automated Ridematching Service is reported. This advanced traveler information system (ATIS) demonstration used a fully automated Touch-Tone telephone system to offer real-time ride matching service for just 1 day or for conventional carpool arrangements. An innovative feature was an automated messaging system in which a computer was used to dial up and leave recorded messages with potential matches. The system failed to perform as intended, and problems were experienced with the generation of computer-based reports for monitoring purposes. The demonstration revealed a low level of use and a mismatch with the needs of the market. Lessons are drawn for future ATIS initiatives.