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As a key component of bus dwell time, passenger movement time in boarding and alighting processes plays an important role in affecting service reliability and service quality. Boarding and alighting processes are impacted by several factors, including vehicle configuration, friction between boarding and alighting passengers, bus floor level, and fare payment methods. The crowding effect refers to the interaction between passengers boarding, alighting, and on-board. In this paper, we introduce two indices, namely rank and occupancy, to describe the crowding effect. Rank reflects the sequence of passengers boarding and alighting, which reveals how passengers’ movement time changes in boarding/alighting process. Occupancy indicates level of crowdedness in vehicle, and quantifies the friction from on board passengers during boarding and alighting process. Based on time-stamped smart card transactions, we measured the inter-tapping interval between two successive boarding (alighting) passengers to identify the effect of rank and occupancy in determining boarding/alighting processes. Before our analysis, a cluster based outlier detection method is applied to guarantee data quality. Using large quantities of boarding/alighting observations from smart card data, we found that both rank and occupancy have strong effects on boarding and alighting processes. For occupancy, 60% is a critical threshold for boarding process, after which a dramatic increase of average boarding time is observed. This research may help better understand the passenger behavior in boarding and alighting processes.

The application of network science has greatly improved understanding about the structure and properties of public transport network (PTN). Using tools and methods provided from network science, several standardized representations have been developed and analyzed to understand the topological structure of PTN from different aspects. In this paper, the authors present an empirical study on the bus network in Singapore. Different from previous studies based on a direct mapping of PTN on road networks, they focus on the weighted C-space representation of public transport networks to better characterize the interaction of different bus services. By exploring the statistical properties of this representation, they find that the bus network in Singapore exhibits similar patterns as many other cities in terms of distributions of edge weight, vertex degree and vertex strength. However, a superlinear scaling is found when the authors examine the dependency of a vertex’s strength on degree, indicating that PTN in Singapore provides people with more alternatives to travel and transfer. The C-space representation also enables us to further explore the interactions between services by examining the community structure and the corresponding reverse mapping on road networks. This helps us to identify those crucial ‘bridges’ in a city, which is shared by different communities and connect diverse regions.

Advances in communication, automatic vehicle location, and geographic information system technologies have made available several types of real-time information which benefits commercial vehicle operations. However, most routing decisions or diversion plans in research literature are based on the current traffic situation and little attention is paid to the future. Such kinds of greedy strategy consistently suggest en route diversion at any point where the alternative route choice is better than the ongoing one. Hence, in the constantly varying real world, excessive diversions may appear and are much likely to create a sort of `zigzag' effect, eventually leading to a higher cost. Thus, a forward-looking diversion strategy considering both real-time and future information is proposed. This paper evaluates the potential benefits, limitations and difficulties of several diversion strategies in response to different information under a real road network, and the selected results derived from simulation are described. The research will help logistics companies to assess the benefits of in-vehicle route-guidance system in their day-to-day operations.

This paper presents the development of a real-time system for monitoring the security of container trucks in road networks. Embedded in the security monitoring system is a container truck tracking and incident detection algorithm which relies on a combination of vehicle telemetry data obtained from Global Positioning Systems and on-board sensors to continuously monitor the route choice and car-following behavior of the driver. The performance of this algorithm has been tested in a microscopic simulation model, on a set of hypothetical scenarios, which included deviations from the approved routes, forced to travel at unreasonably low speeds, or even stopped at unexpected places in the network. The initial results indicate that the proposed system has good potential in detecting abnormal driving behaviors, with 100% detection rate, 6.0 seconds of mean detection time, and less than 0.5% false alarm rate.

This paper presents dispatch systems using Intelligent Transportation Systems (ITS) technologies for taxi booking services. An overview of taxi services in Singapore was introduced at first and followed by a satellite-based taxi dispatch system for booking services and their shortcomings. Two novel dispatch strategies were therefore proposed, which have proven to be efficient to improve taxi-booking service.

A distribution strategy with balanced workload allocation aims to be "cost efficient", and helps in promoting customer service levels. However, little attention has been paid to the balanced workload allocation in logistics system design problems. In this paper, a bi-level programming model has been proposed, which optimizes the distribution network in logistic systems and at the same time, balances the workload of each distribution center (DC) on delivering products to its customers. A genetic algorithm (GA) based approach has been developed with the bi-level model, and it has been tested on a best "real" dataset.

This paper investigates the average trip travel time for trucks during an incident, with real-time traffic information from (1) variable message signs (VMS); (2) combination of VMS and travel time displays (TTD); and (3) dynamic route guidance systems (DRGS). The evaluation was carried out with a microscopic traffic simulation model, in a network that consisted of a 26.5 km expressway and its parallel arterials. A factorial experiment was designed to investigate the effect of five factors, which were the level of traffic information available to truck drivers, network traffic demand, incident locations, incident severity and percentage background traffic which was familiar with the network. Our results confirmed that the five factors contributed significantly in affecting the average truck travel time. There were significantly interactions between the two factors with the exception of the level of traffic information and incident severity.

Storing containers in the yard, allocating resources in the terminal, and scheduling vessel loading and unloading operations are major tasks in a container port. This paper mainly deals with the allocation of yard resources to the containers. We consider optimizing crane scheduling and weighted container movement in the yard with deterministic machine availability constraints. The problem is formulated as a NP-hard problem. A genetic algorithm is devised for solution.

Proceedings of the Eighth International Conference on Applications of Advanced Technologies in Transportation Engineering, held in Beijing, China, on May 26-28, 2004. Sponsored by China Academy of Transportation Sciences; Ministry of Communications, China; the Transportation and Development Institute of ASCE. Coponsored by China Highway and Transportation Society, China; China Navigation Institute, China; Transportation Research Board, USA; Tsinghua University, China. This collection contains 124 papers on technical innovations for improving transportation infrastructure and providing more efficient transportation operations. The latest analytical tools for solving transportation difficulties were discussed, especially within China, which has the fastest growing economy in the world. Topics include: intelligent transportation systems; traffic flow theory and predications; traffic control and management; highway operations; and public transportation.

This paper introduces a model to estimate average link travel time of signalized arterials using data obtained from detectors in Sydney Co-Ordinated Adaptive Traffic System (SCATS). The proposed model makes use of detectors at the upstream stop line of a link to capture the arrival of vehicles, and use a platoon dispersion model to project the vehicle arrival times at the downstream stop line. Using the vehicle departure pattems obtained at detectors at the downstream stop line, the average link travel time is then estimated. The accuracy of the proposed model has been tested, by means of microscopic traffic simulations, for link lengths between 300 m to 800 m, and at different urban street level of service. Results indicate that the proposed link travel time estimation model has an average absolute error of 2.26 sec. INTRODUCTION With the development of Advanced Traveler Information Systems (ATIS), it has become more important to obtain accurate real-time travel time data that reflects the operating efficiency of a traffic network, for assessing the performance of traffic management strategies, and for provision of route-guidance information. Several researches have been conducted on arterial travel time or speed estimation despite the complexity caused by traffic signals at intersections. Most of these arterial travel time or speed estimation models rely on data gathered by loop detectors at a distance away from the stop line (Gault 1981, Sisiopiku and Rouphail 1994, Zhang 1999 and Xie et al. 2001). Relatively few efforts have been made for the case with detectors installed at the stop line, with the exception of Luk and Cahill (1986), because it is difficult to make use of stop-line detectors to measure the representative link speed, vehicle arrival rate and queue length at an intersection approach. In addition, conventional way of aggregating loop detector data at stop line at cyclic interval does not provide data of sufficient granularity. With the improvement and cost reduction in loop detector hardware, it is becoming possible to program new data processing logic into a detector's controller card, to record vehicle arrivals and departures over the detector at intervals of several seconds. It is with this in mind that a method of using stop-line detectors to estimate arterial travel time is developed and tested in this paper. The proposed arterial travel time estimation method makes use of the existing stop-line detectors of the traffic signal control system in Singapore named Green Link Determination, or GLIDE in short (Chin 1993). It is the local version of the wellknown Sydney Co-Ordinated Adaptive Traffic Systems (SCATS) (Sims and Assoc. Prof., Dept. of Civ. Engrg., Nat. Univ. of Singapore, 1 Engineering Dr. 2, Singapore 117576, Singapore (corresponding author). Email: cheu@nus.edu.sg. 2 Res. Scholar, Dept. of Civ. Engrg., Nat. Univ. of Singapore. 3 Asst. Prof., Dept. of Civ. lEngrg., Nat. Univ. of Singapore.