Journal of Advanced Transportation, Vol. 36 No. 3, pp. 225-229 www. advanced-transport. corn EDITORIAL Special Issue: Intelligent Transportation Systems Guest Editor: William H.K. Lam Recent rapid development of Intelligent Transportation Systems (ITS) makes it possible to improve the efficiency and reliability of transportation networks. The combined application of various ITS technologies holds great promise for increasing the capacity of existing road networks through more efficient road use, which is particularly important in Hong Kong due to its road network of high traffic density and limited capacity together with fast-growing population. The ITS can provide area wide traffic data, travel time information, route guidance, traffic management and urban traffic control etc. Therefore, intelligent transportation systems affect road networks in a number of different ways including road capacity and travel times under various trafficked conditions. Adler (2001) showed how traffic information and route guidance could improve travel times by about 1 minute in a 15-minute journey. Rajamani and Shladover (2001) showed that current technologies could be used to provide autonomous adaptive cruise control systems that increase road capacity from about 2000 to about 3000 vehicles per hour per lane, whilst co-operative ones could achieve about 6400 vehicles per hour per lane. In addition, evaluation of the benefits of ITS requires consideration of drivers response to reliability andor uncertainty of travel time under various circumstances (Chatterjee et al., 2002). As a key technique required for evaluation of ITS, in particular the route guidance systems, dynamic traffic assignment (DTA) model has been received much attention in the past two decades. The DTA problem has been formulated by different approaches such as mathematical programming, optimal control theory, variational inequality (VI) and William H.K. Lam is a Professor in the Department of Civil Engineering, The Hong Kong Polytechnic University, Hong Kong, P.R. China, and Editor, Journal of Advanced Transportation.
226 William H.K. Lam simulation. Recent comprehensive reviews on this topic have been given by Chen and Hsueh (1998), Tong and Wong (2000), and Huang and Lam (2002). However, the emergence of ITS and the associated technologies has generated an urgent need for advanced models and solution algorithms so as to provide better understanding of the ITS impacts on networks with various trafic conditions. Hong Kong is a very densely populated city with about seven million people living in a total land area of 1,092 h2. Among cities of comparable GDP around the world, Hong Kong is one of the cities with the highest road traffic density in Asia. There are about 1.34 million private vehicle trips per day in a road network with 1800 kilometers only. The development and maintenance of a reliable and efficient road transport system are therefore extremely important for continuous economic development in Hong Kong. To this end, a Workshop on ITS was held in Hong Kong on 3d December 2001 to act as a forum for the exchange of expertise, knowledge and experience among overseas and local experts and researchers. A number of papers presented at the workshop are of particular interest to practicing engineers and researchers involved in the deployment of ITS. Among them, a number of papers are focused on the technologies and techniques for ITS impact assessment including advanced models and solution algorithms. This Special Issue is devoted to the dissemination of research findings by these authors. In total, six papers are included in this special issue and are summarized as follows. Following a stimulating introduction to the workshop, Bell presents the technology of impacts of in-vehicle information systems on transport efficiency. Three generations of system are discussed. It is hypothesised that the third generation will make use of the extra bandwidth offered by 3G mobile phones to download maps and other data as and when required. 3G mobile phones will probably obviate the need to invest extensively in beacons, in-vehicle DVD players and CD-ROM map databases. However, for locationing, GPS will probably still be required. Portable devices offering multi-modal information could encourage the use of public transport by reducing the uncertainties involved in modal interchange. This would go some way to improving inter-modal transport efficiency. For assessing the impacts of lts on transportation network, a number of simulation models have been developed. Horiguchi and Kuwahara summarize a standardized verification process for network traffic simulation models. Verification here means several examination tests of simulation models using virtual data on a simple network so as to
Editorial 227 confirm their fundamental functions such as 1) vehicle generation, 2) bottleneck capacity at simple road sections, 3) capacity of merginddiverging areas, 4) traffic jam growing/shrinking with propagation of shock waves, 5) capacity of IeWright turn at an intersection, 6) drivers route choice behavior, and so on. Several simulation models that are practically used in Japan have been evaluated based upon the proposed verification process. Horiguchi and Kuwahara have verified seven pilot models, such as AVENUE, SOUND, tiss-net, Paramics, NETSIM, REST, and SPA along the verification manual and validated with benchmark data set. This standardized verification process is useful for model developers to confirm the model functions. Moreover, the verification would be helphl for model users to receive results of the verification to get familiar with model characteristics as well as model parameters to be adjusted, since users may frequently have difficulty in fully understanding the theories of the simulation model from the literature and the manual only. With the rapid development of electronic information and communication technologies, there is great potential for providing shortterm travel time information to improve efficiency in road networks. Lam et al. present an off-line prediction system for short-term travel time forecasting. These forecasts are based on the historical traffic count data provided by detectors installed on Annual Traffic Census (ATC) stations in Hong Kong. A traffic flow simulator (TFS) is developed for the offline prediction system to forecast short-term travel times in road network, in which the variation of perceived travel time error and the fluctuations of origin-destination (0-D) demand are considered explicitly. On the basis of prior 0-D demand and partial updated detector data, the TFS can estimate the link travel times and flows for the whole network together with their variances and co-variances. The short-term travel time forecasting by 0-D pair can also be assessed and the 0-D matrix can be updated simultaneously. The application of the proposed off-line prediction system is illustrated by a numerical example in Hong Kong. Intelligent transportation systems provide various means to improve capacity and travel time in road networks. Evaluation of the benefits of these improvements requires consideration of travelers response to them. Heydecker explores the equilibrium model of departure time choice, and in particular, its implication for the sensitivity of each of the costs incurred by travelers and the period during which travel takes place as certain parameters of the network performance are varied as through the implementation of ITS measures. Explicit formulae are established for
228 William H.K. Lam the derivatives of cost with respect to total amount of travel, the capacity of a route, and the uncongested travel time on that route when travelers exercise equilibrium choice of departure times. Corresponding formulae are established for the derivatives of the start and end times of the interval during which travel takes place, which delimit the peak period. Thus it is shown how the present equilibrium model can be used to analyze various ITS measures after due allowance has been made for travelers response that gives rise to the phenomenon of peak spreading. The results of some simple calculations based upon this are presented and discussed by way of illustration. It shows the importance of the values of time in evaluation, and that if travelers value their time at both the origin and destination of their journeys, their responses will lead them to achieve a greater reduction in costs than would be achieved under free-flow conditions. Urban traffic control is one of the most important elements in Intelligent Transportation Systems (ITS). It coordinates the traffic signals among adjacent junctions to improve the operational performance of a signal-controlled network. The last two papers are concerned with the urban traffic control systems. Lo and Chow present an adaptive traffic control system (ATCS) for controlling the imminent traffic, which is yet to arrive and hence not known perfectly. Therefore, volume prediction is an essential part. Associated with the prediction are two aspects: resolution and accuracy. Recent studies indicate a trade-off between prediction resolution and accuracy: finer resolutions, larger errors. It is imperative to study the relationship and trade-off between the control strategy, prediction resolution, and its associated error, which are crucial to the development of ATCS. Lo and Chow investigate this relationship through an extensive simulation of scenarios in Hong Kong with a novel dynamic traffic control model, DISCO. Based on the Hong Kong scenarios conducted with DISCO, the major findings include: (i) the importance of resolution outweighs that of error; (ii) dynamic timing plans generally outperform time-invariant timing plans; (iii) up to a certain extent, overestimated predictions lead to better results than underestimated predictions.: Wong and Wong extend the lane-based optimization method to a traffic equilibrium network, which improves the operational performance of signalcontrolled network. A decomposition approach is formulated to simultaneously optimize the lane markings and signal settings for a signal-controlled network that comprises two levels of optimization. At the intersection level, the lane markings, control sequence, and other aspects of the signal settings are optimized for individual intersections,
Editorial 229 whereas at the network level, the group-based signal settings are optimized to take into account the re-routing characteristics of travelers and signal coordination effects that are based on a TRANSYT traffic model, which is a well-known procedure for evaluating the performance of signal-controlled networks. A numerical example is used to demonstrate the effectiveness of the proposed methodology. Owing to the diversity of research and development (R & D) on ITS, the papers presented in this special issue are by no means exhaustive. However, they do provide general coverage of various important areas of R & D on this subject. The editor hope that this issue will bring state-ofthe-art methodologies for development of ITS to the attention of practicing engineers and researchers, and that it will inspire and stimulate new R & D opportunities and efforts in the field. After all, it is hoped that this would improve the planning, design and operation of intelligent transportation systems and help promote their use to improve the reliability and efficiency of transportation networks in our cities. References: Adler, J.L. (2001) Investigation the learning effects of route guidance and traffic advisories on route choice behavior. Transportation Research, 9C, 1-14. Chatterjee, K., Hounsell, N., Firmin, P. and Bonsall, P. (2002) Driver response to variable message sign information in London. Transportation Research, loc, 149-169. Chen, H.K. and Hsueh, C.F. (1998) A model and an algorithm for the dynamic user-optimal route choice problem. Transportation Research, 32B, 219-234. Huang, H.J. and Lam, W.H.K (2002) Modeling and solving the dynamic user equilibrium route and departure time choice problem in network with queues. Transportation Research, 36B, 253-273. Rajamani, R. and Shladover, SE. (2001) An experimental comparative study of autonomous and co-operative vehicle-follower control systems. Transportation Research, 9C, 15-31. Tong, C.O. and Wong, S.C. (2000) A predictive dynamic traffic assignment model in congested capacityconstrained road networks. Transportation Research, 34B, 625-644.