Inhi Kim

Electric vehicles: A review of network modelling and future research needs

Electric vehicles are believed to be an effective solution for reducing greenhouse gas emissions. Despite extensive study on the attributes and characteristics of electric vehicles and their charging infrastructure design, the development and network modelling of electric vehicles are still evolving and limited. This article provides a comprehensive review of electric vehicle studies and identifies existing research gaps in the aspects of theories, modelling approaches, solution algorithms and applications. This article first describes the electric vehicles’ concepts, market share, characteristics and charging infrastructures. Then, the studies on traffic assignment problem with electric vehicles in the network and limited charging facilities are particularly discussed. We conclude that it is of great importance to take into account electric vehicles’ special characteristics (e.g. range limit) in predicting their routing behaviour and charging infrastructure design networks.

Integration of driving simulator and traffic simulation to analyse behaviour at railway crossings

The use of state-of-the-art technology to collect and analyse data has significantly improved the effectiveness of safety studies. Currently, despite the fact that there are many safety systems deployed at railway crossings, only limited research has been conducted to evaluate which of these systems is the most effective in terms of costs and safety. This paper demonstrates a way to evaluate safety at railway crossings using a twin-pronged approach: a driving simulator and traffic simulation software. A number of outputs have been observed from a driving simulator, such as driver compliance rate, vehicle speed profile, acceleration profile, initial braking position and final braking position. The compliance percentage at passive crossings (67 and 72% for a stop sign and rumble strips, respectively) has lower compliance rates compared with active crossings (97 and 93% for flashing red light and in-vehicle audible warning, respectively) at an 80 km/h approach speed. Using a statistical analysis it is shown that speed and acceleration profiles can be used to differentiate the effectiveness of active and passive crossings. These indicators are interpreted and used as input to a traffic simulation, which assists in determining which safety device is more efficient. By integrating driving simulator and traffic simulation models, this approach can be applied to evaluate and compare safety performance without the need to install costly test beds at real railway crossings.

Evaluating Safety at Railway Level Crossings with Microsimulation Modeling

Safety at railway level crossings (RLXs) is a worldwide issue that increasingly attracts the attention of relevant transport authorities, the rail industry, and the general public. The differences in the operation characteristics of varying types of warning devices, together with differences in crossing geometry, traffic, or train characteristics, leads to different driver behaviors at crossings. The aim of this study was to use traffic microsimulation modeling based on field video recording data to compare the safety performance of varying conventional RLX warning systems. The widely used microsimulation model VISSIM was modified to produce safety-related performance measures, namely, collision likelihood, delay, and queue length. The results showed that RLXs with an active warning system were safer than those with a passive sign by at least 17%. Integration of surrogate measures in conjunction with traffic simulation models determined which safety approach was more efficient for specified traffic and train volumes.

Location Design of Electric Vehicle Charging Facilities: A Path-Distance Constrained Stochastic User Equilibrium Approach

Location of public charging stations, range limit, and long battery-charging time inevitably affect drivers’ path choice behavior and equilibrium flows of battery electric vehicles (BEVs) in a transportation network. This study investigates the effect of the location of BEVs public charging facilities on a network with mixed conventional gasoline vehicles (GVs) and BEVs. These two types of vehicles are distinguished from each other in terms of travel cost composition and distance limit. A bilevel model is developed to address this problem. In the upper level, the objective is to maximize coverage of BEV flows by locating a given number of charging stations on road segments considering budget constraints. A mixed-integer nonlinear program is proposed to formulate this model. A simple equilibrium-based heuristic algorithm is developed to obtain the solution. Finally, two numerical tests are presented to demonstrate applicability of the proposed model and feasibility and effectiveness of the solution algorithm. The results demonstrate that the equilibrium traffic flows are affected by charging speed, range limit, and charging facilities’ utility and that BEV drivers incline to choose the route with charging stations and less charging time.

Comparison of SimTraffic and VISSIM Microscopic Traffic Simulation Tools in Modeling Roundabouts

SimTraffic and VISSIM are two microscopic traffic simulation tools that are capable of modeling arterial roads with signalized intersections and roundabouts. This study compares the performance of the two simulation tools in modeling dual lane and triple lane roundabouts under different scenarios such as traffic volume, proportion of left turning movement, and proportion of trucks in the traffic flow. The two simulation tools did not show statistically significant difference in general. However; in the case of high traffic volumes, VISSIM showed higher average delays than those from SimTraffic compared to nearly identical results in the case of low traffic volumes.

Integrating driving and traffic simulators for the study of railway level crossing safety interventions: a methodology

Safety at Railway Level Crossings (RLXs) is an important issue within the Australian transport system. Crashes at RLXs involving road vehicles in Australia are estimated to cost

Evaluation of Large Signalized Intersection with New Pedestrians Twice Crossing

10 million each year. Such crashes are mainly due to human factors; unintentional errors contribute to 46% of all fatal collisions and are far more common than deliberate violations. This suggests that innovative intervention targeting drivers is particularly promising to help improve RLX safety. In recent years there has been a rapid development of a variety of affordable technologies which can be used to increase driver’s risk awareness around crossings. To date, no research has evaluated the potential effects of such technologies at RLXs in terms of safety, traffic and acceptance of the technology. Integrating driving and traffic simulations is a safe and affordable approach for evaluating these effects. This methodology will be implemented in a driving simulator, where we recreated realistic driving scenario with typical road environments and realistic traffic. This paper presents a methodology for evaluating comprehensively potential benefits and negative effects of such interventions: this methodology evaluates driver awareness at RLXs, driver distraction and workload when using the technology. Subjective assessment on perceived usefulness and ease of use of the technology is obtained from standard questionnaires. Driving simulation will provide a model of driving behaviour at RLXs which will be used to estimate the effects of such new technology on a road ...

Driver Behaviors at Level Crossings from Fixed and Moving Driving Simulators

Abstract: Phase sequence and pedestrian cross pattern have significant impacts on the capacity of intersection. This paper concentrates on realigning a signal phase sequence to design a new pedestrian twice crossing (PTC) pattern providing additional time for pedestrians. To fully evaluate the operational performance of such an intersection with applying the realigned signal phase and the new PTC pattern, another two similar intersections with different signal phase sequences and cross patterns are established using VISSIM. One applies a typical 4-phase signal sequence * , and pedestrians only can cross the street in vehicle-through phase. The other applies the same vehicle signal sequence as model 1, but pedestrians apply a normal PTC pattern to cross the street. Five indices such as vehicle average travel time (VATT), vehicle average delay (VAD), pedestrian average travel time (PATT), pedestrian average delay (PAD), and the number of vehicles and pedestrians crossing the intersection per hour are employed to evaluate the performance of these three developed scenarios. The simulation results show that three models have very little gaps in VATT, VAD and the number of vehicle and pedestrian crossing the intersection. The New PTC pattern, however, makes a significant progress in pedestrian PATT and PAD compared with other two patterns.

Congestion patterns of electric vehicles with limited battery capacity

Many studies were conducted to evaluate safety at railway crossings equipped with different types of warning devices. In this study, a desktop driving simulator (fixed simulator) and an advanced simulator (moving simulator) were used to identify the impacts of two warning devices namely stop sign and in-vehicle audio warning on alerting drivers at railway crossings. Although these high-end technologies have been widely used for safety evaluation in many areas, there is a little research on their application and comparison at railway crossings. This paper reports the results of a comparison of the two simulators. As a preliminary result, vehicle speeds at given distance/time were analyzed. The results showed that when the warning started, drivers in the fixed simulator were slower than those in the moving simulator in responding. However, after four seconds of warning, the speed from both simulators showed statistically identical results. In summary, the different properties of the simulator lead drivers to react to warnings differently.

Study of Mandatory Lane Change Execution Behavior Model for Heavy Vehicles and Passenger Cars

The path choice behavior of battery electric vehicle (BEV) drivers is influenced by the lack of public charging stations, limited battery capacity, range anxiety and long battery charging time. This paper investigates the congestion/flow pattern captured by stochastic user equilibrium (SUE) traffic assignment problem in transportation networks with BEVs, where the BEV paths are restricted by their battery capacities. The BEV energy consumption is assumed to be a linear function of path length and path travel time, which addresses both path distance limit problem and road congestion effect. A mathematical programming model is proposed for the path-based SUE traffic assignment where the path cost is the sum of the corresponding link costs and a path specific out-of-energy penalty. We then apply the convergent Lagrangian dual method to transform the original problem into a concave maximization problem and develop a customized gradient projection algorithm to solve it. A column generation procedure is incorporated to generate the path set. Finally, two numerical examples are presented to demonstrate the applicability of the proposed model and the solution algorithm.