Comparing Driver Information Systems in a Dynamic Modeling Framework

The variable message signs (VMS) have been widely used in guiding and managing the dynamic traffic with development of intelligent transportation technologies. It is known that cell transmission model (CTM) can well reproduce such traffic dynamics as shock waves and jams. This paper is novel in simulating the traffic propagations based on CTM and VMS route recommendations. The impacts of VMS on congestion are numerically investigated. Simulation results show that the real-time traffic conditions can well be reproduced. The VMS can positively influence travelers' decision making so as to alleviate the grave degree of traffic congestion. And further, the higher traffic demands are, the better effect of VMS route recommendation is.

The use of variable message signs (VMS) to provide traffic information is widespread, but success depends upon behavioural response to the sign messages. The research described here focuses on user acceptance of VMS located in an urban road network (Southampton, UK), and investigates the public's perceived effectiveness and usefulness of these signs through the use of revealed preference questionnaire surveys and travel diaries. Three hundred and sixty-five commuters regularly driving into Southampton from the outskirts of the city completed a travel diary for a 5-day period as well as a general questionnaire, and 660 infrequent travellers to Southampton completed the general questionnaire. The study showed that it is difficult to capture a meaningful sample size of respondents passing an `active' VMS in a real-life incident scenario. Less than 1% of the commuter sample stated that they had diverted to an alternative route during the travel diary week as a result of VMS information, although this did correspond to 53% of those 45 drivers originally intending to travel past the incident location. The results showed that the VMS messages were well-understood and legible, and also indicated that a default VMS message reporting no problems in the network can indirectly affect a driver's route choice.

The vicinity of conurbations usually implies a strong interaction between, urban and interurban road and traffic systems. This results generally in extended congestion during peak periods and underlines the necessity of data exchange between urban and interurban traffic centres for the purpose of coordinated driver information and traffic control strategies. The paper proposes an integrated traffic management system, which will include several methods to assure adaptive traffic management in the covered area, such as: ramp-metering, driver information, variable message signs, variable speed.

As part of the Highways Agency's plans to make the best use of existing roads, it is increasingly common for key intersections of the UK strategic road network to be provided with variable message signs (VMS). In the event of an incident affecting part of the network, the VMS can be used to warn drivers of the problem, and possibly to divert them onto alternative routes. Warning messages or diversions are usually selected from a library of plans, prepared in advance, to cater for a range of incidents. It can be difficult for system operators to determine which of the library of plans is most appropriate for a given incident, under the prevailing traffic conditions. To assist operators in making this decision the Highways Agency has developed MOLA (MCONTRM On-Line Assistant), a computer system able to model traffic conditions on a road network in real time and, when an incident occurs, to predict the effectiveness of alternative strategies and recommend to the operator which he should implement. (5 pages)

This paper describes a dynamic model for evaluating the benefit of an Advanced Traveler Information System (ATIS). The model consists of five modules, including a route choice module and a traffic simulation module. The route choice module considers different categories of drivers’ route choice behaviors with different levels of access to traffic information. The traffic simulation module simulates dynamic network conditions in response to traffic information. The dynamic model allows the investigation of a network-wide performance in a road network under different traveler information systems. Some results are provided to demonstrate the use of the model. They suggest that providing traffic information can reduce the total network delay. However, there is an optimum level of market penetration beyond which real-time information can no longer reduce delay of the network and the individual.

Advanced traveler information systems (ATIS) for drivers are a very important element of modern traffic management. In recent years ITS infrastructure is being developed also in Poland. It allows for delivering to drivers information related to the conditions in the road network through, inter alia, dedicated Variable Message Signs (VMS). Such information enables drivers to take decisions, contributing to improving the efficiency and safety of the transport system. They also allow to manage the traffic speed dynamically, taking into account weather conditions hazards, temporary disruptions or incidents. Paper provides an overview of different solutions for Advanced Traveler Information Systems in Poland. The place of ATIS in architecture of Tri-City TRISTAR system is described as well as the use of data, functions and algorithms that allow them to be implemented. Furthermore ATIS development plans and plans for research to be carried out to improve the functioning of the system are presented.KeywordsIntelligent transport systemsTraffic managementInformation systems

In this research we utilize PARAMICS traffic micro-simulation software to study the impact of deploying Connected Vehicles (CV) in Deerfoot trail, Calgary, Alberta. We have implemented a V2V (Vehicle-to-Vehicle) Assisted V2I (Vehicle-to-Infrastructure) system for PARAMICS. It uses Dedicated Short Range Communication (DSRC) protocol to acquire traffic data, calculate and compare important traffic safety and mobility parameters and their impacts on CV by testing five scenarios differentiated by the percentage of 0% to 40% market penetration of CVs. Despite of previous studies which focused on upstream traffic, in this study we demonstrate effect of considering DSRC, re-routing guidance and advisory speed for upstream and downstream traffic. The study demonstrated that the CV technology can enhance traffic safety and mobility in freeways, if the percentage of CVs is significant (e.g. 30–40%) and the CV technology is accompanied by advisory speed reflected on Variable Message Signs (VMS) on both upstream and downstream of the incident location using DSRC range. In other words, equipping freeways with VMS, to use V2I communication, complements the CV technology, improves CV efficiency and leads to higher safety and mobility enhancement in freeways.

When operating traffic route guidance systems (TRGS) and providing road users information about traffic state through VMS (variable message signs) systems, most operators and engineers, with their experience and using aggregate statistic data, suppose that all drivers share the same standard for understanding and assessing traffic state. However, each receiver actually has his/her own standard to differentiate one traffic state from another. Different receivers may understand the same traffic situation differently due to their dissimilar individual characteristics. Ignoring this dissimilarity and blindly supplying the same traffic state information to all receivers cause TRGS hard to work well. This dissimilarity was firstly analyzed in this paper using statistic and regressive technique with SP (stated preference) and RP (revealed preference) survey data, then, a model was established to demonstrate the relationship between traffic-state-division-speed and information-receivers' individual identities including gender, age, driving years, familiarity with road network and trip purpose.

Variable message signs (VMSs) provide important traffic information to help drivers travel better on a transportation network. The effectiveness of VMSs largely depends on the numbers and locations of VMSs in a transportation network. Although a few optimization models have been proposed to find candidate roads for locating VMSs, few have been devoted to developing algorithms that can be used in a real transportation network. A large amount of traffic data, such as traffic flow data, is widely available, collected by various means. Based on those traffic data, a sorting algorithm for a VMS location problem is presented in this paper. The algorithm gave a VMS location order rather than a location set. The proposed method divided roads into categories according to multilevel attributes and preferentially selected roads of a higher class with larger flows and more information and the minimal effect of existing VMS in a certain order to locate VMS. The proposed algorithm was analyzed and verified through a practical case on the Beijing, China, urban road network.

PurposeThe aim of this study is to identify factors that influence drivers' route choice response to travel time information about both the expressway and local streets provided by variable message signs on arterial roads.Design/methodology/approachA stated preference questionnaire survey was conducted to collect behavioral data. The generalized estimating equations (GEEs) method with a logit link function was used to model driver response and account for correlations within repeated observations from the same respondent. Four GEEs‐based estimations with different working correlation structures were conducted and compared with each other as well as the conventional maximum likelihood estimation.FindingsDriving experiences, expressway delays, causes of delay, and the number of traffic lights on local streets are factors influencing route choice decisions. A new finding is that there exist differences in response behavior among employer‐provided car, taxi and private car drivers. On the modeling aspect, the exchangeable structure was the most appropriate in this study.Research limitations/implicationsThis study indicates the effectiveness and appropriateness of the GEEs method and suggests further examination of GEEs' performance.Practical implicationsThe route choice probability model established by this study will facilitate better investment, design and assessment of dynamic information services in transportation management.Originality/valueThe dynamic information this study concerns has rarely been addressed in the literature. Little literature to date has applied the GEEs method in information response modeling. This study reaches solider conclusions about the GEEs method.

Given the role of road tunnels in a road network, it is relevant to quantitatively assess their resilience due to disruptive events. In this respect, the travel speed of traffic flow, as a metric of resilience, in the event of traffic accidents in road tunnels has been scarcely used. This represents a gap of knowledge that this paper intends to fill. For the purpose, the research method applied involves the development of a traffic macro-simulation model, and the analysis of results using the average travel speed and its spatial profile as a resilience metric. Particularly, we have evaluated the resilience of a twin-tube motorway tunnel when a traffic accident occurs in a tube. The findings showed how the best functionality level of the system, expressed in terms of average vehicles’ speed, with its related greatest resilience index, is associated with the partial closure of the disrupted tube rather than the complete one. Further benefits might be obtained by activating Variable Message Signs (VMSs) that alert only the Heavy Goods Vehicles (HGVs) to exit the motorway before entering the tunnel and to use an alternative itinerary identified in the nearby transportation network. In this respect, we found that by means of the activation of VMSs as a traffic control strategy, the resilience index increased by about 7–17% when the traffic accident caused the partial closure of the disrupted tube for 1–3 h. Improvements might also be achieved by rapidly opening the two traffic by-passes at the tunnel portals that allow for the use of the adjacent undisrupted tube for two-way traffic. The unavailability of an alternative itinerary in the nearby transportation network along which to re-route the HGVs is also examined, finding a reduction in the functionality conditions of the system. The results obtained might serve as a support tool in the choice of functional recovery strategies in the case of the temporary partial or complete block of a tunnel tube due to a traffic accident.

Strategic decision making plays an important role in disaster management. In view of an imminent or already occurring event, e.g. flood, that has the potential to stress and threaten populated regions, humanitarian supply chain management is a place where strategic decision making plays a major role. Sensible or strategic measures have to be developed in order to mitigate damages. Strategic measures should take into account available and possibly distributed resources, e.g. vehicles, storages and street networks, and of course the type of measure against the background of protection goals. Finding good or sensible measures becomes a hard task if the menaced region refers to a densely populated area, where the functionality of street network has a dynamic feature in terms of the emergence of blocked segments. This task gets even harder if the protection of certain critical infrastructures also has to be considered. Our work proposes a framework of a decision support system that is based on the synergetic coupling of a critical infrastructure and a traffic simulation module. By defining different event scenarios, different simulation runs can be triggered beforehand and according to the decision maker's preferences, sensible measures in terms of type of resources and routes are stored and displayed to the decision maker. Especially simultaneously occurring issues of different problem categories requiring decisions by various decision makers are addressed.

This paper describes the real time data fusion demonstrator that has been developed for use within the proposed Regional Traffic Control Centres (RTCC). RTCCs are identified as one of the key tasks within the Highways Agency business plan for implementing strategic network control and the provision of reliable driver information systems so as to make better use of the existing road network. The objectives are: to improve road safety; improve network efficiency and journey time reliability; improve environmental conditions; and the provision of relevant and reliable information to drivers. The RTCCs will provide an additional tier of strategic control allowing a management overview of the road network to be taken and accurate advice generated. Within the RTCC the data from a variety of sources, locations and times will be fused to provide a coherent picture of real time traffic conditions over the whole network. The fusion process will calculate confidence values for the traffic data value based on the accuracy of the measurement method, the location and time when the measurement was made and the availability of supporting confirmation data. The data held in the RTCC database will be used to calculate traffic management strategies for the regional network and will be disseminated via the traffic information highway to external driver information service providers.

Fuzzy Power Heronian function based CoCoSo method for the advantage prioritization of autonomous vehicles in real-time traffic management

Information about traffic conditions has traditionally been conveyed to drivers via radio, variable message signs, and, more recently, the Internet and advanced traveler information systems. This has spurred research on how travelers respond to information, how much they are willing to pay for it, and how much they are likely to benefit from it collectively. In this paper, we analyze the decisions of drivers on whether to acquire information and which routes to take on simple congested road networks. Drivers vary in their degrees of risk aversion with respect to travel time. Four information regimes are considered: no information, free information (publicly available at no cost), costly information (publicly available for a fee), and private information (available free to single individuals). Private information is shown to be individually more valuable than either free or costly information while the benefits from free and costly information cannot be ranked in general. Free or costly information can decrease the expected utility of drivers who are very risk averse; with sufficient risk aversion in the population, the aggregate compensating variation for information can be negative.