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This study aims to study the connected vehicle (CV) impact on highway operational performance under a mixed CV and regular vehicle (RV) environment.

The authors implemented a mixed traffic flow model, along with a CV speed control model, in the simulation environment. According to the different traffic characteristics between CVs and RVs, this research first analyzed how the operation of CVs can affect highway capacity under both one-lane and multi-lane cases. A hypothesis was then made that there shall exist a critical CV penetration rate that can significantly show the benefit of CV to the overall traffic. To prove this concept, this study simulated the mixed traffic pattern under various conditions.

The results of this research revealed that performing optimal speed control to CVs will concurrently benefit RVs by improving highway capacity. Furthermore, a critical CV penetration rate should exist at a specified traffic demand level, which can significantly reduce the speed difference between RVs and CVs. The results offer effective insight to understand the potential impacts of different CV penetration rates on highway operation performance.

This approach assumes that there shall exist a critical CV penetration rate that can maximize the benefits of CV implementations. CV penetration rate (the proportion of CVs in mixed traffic) is the key factor affecting the impacts of CV on freeway operational performance. The evaluation criteria for freeway operational performance are using average travel time under different given traffic demand patterns.

On-ramp merging areas are typical bottlenecks in the freeway network since merging on-ramp vehicles may cause intensive disturbances on the mainline traffic flow and lead to various negative impacts on traffic efficiency and safety. The connected and autonomous vehicles (CAVs), with their capabilities of real-time communication and precise motion control, hold a great potential to facilitate ramp merging operation through enhanced coordination strategies. This paper aims to present a comprehensive review of the existing ramp merging strategies leveraging CAVs, focusing on the latest trends and developments in the research field.

The review comprehensively covers 44 papers recently published in leading transportation journals. Based on the application context, control strategies are categorized into three categories: merging into sing-lane freeways with total CAVs, merging into sing-lane freeways with mixed traffic flows and merging into multilane freeways.

Relevant literature is reviewed regarding the required technologies, control decision level, applied methods and impacts on traffic performance. More importantly, the authors identify the existing research gaps and provide insightful discussions on the potential and promising directions for future research based on the review, which facilitates further advancement in this research topic.

Many strategies based on the communication and automation capabilities of CAVs have been developed over the past decades, devoted to facilitating the merging/lane-changing maneuvers at freeway on-ramps. Despite the significant progress made, an up-to-date review covering these latest developments is missing to the authors’ best knowledge. This paper conducts a thorough review of the cooperation/coordination strategies that facilitate freeway on-ramp merging using CAVs, focusing on the latest developments in this field. Based on the review, the authors identify the existing research gaps in CAV ramp merging and discuss the potential and promising future research directions to address the gaps.

This paper aims to explore whether drivers would adapt their behavior when they drive among automated vehicles (AVs) compared to driving among manually driven vehicles (MVs).Understanding behavioral adaptation of drivers when they encounter AVs is crucial for assessing impacts of AVs in mixed-traffic situations. Here, mixed-traffic situations refer to situations where AVs share the roads with existing nonautomated vehicles such as conventional MVs.

A driving simulator study is designed to explore whether such behavioral adaptations exist. Two different driving scenarios were explored on a three-lane highway: driving on the main highway and merging from an on-ramp. For this study, 18 research participants were recruited.

Behavioral adaptation can be observed in terms of car-following speed, car-following time gap, number of lane change and overall driving speed. The adaptations are dependent on the driving scenario and whether the surrounding traffic was AVs or MVs. Although significant differences in behavior were found in more than 90% of the research participants, they adapted their behavior differently, and thus, magnitude of the behavioral adaptation remains unclear.

The observed behavioral adaptations in this paper were dependent on the driving scenario rather than the time gap between surrounding vehicles. This finding differs from previous studies, which have shown that drivers tend to adapt their behaviors with respect to the surrounding vehicles. Furthermore, the surrounding vehicles in this study are more “free flow'” compared to previous studies with a fixed formation such as platoons. Nevertheless, long-term observations are required to further support this claim.

This study aims to make full use of the advantages of connected and autonomous vehicles (CAVs) and dedicated CAV lanes to ensure all CAVs can pass intersections without stopping.

The authors developed a signal coordination model for arteries with dedicated CAV lanes by using mixed integer linear programming. CAV non-stop constraints are proposed to adapt to the characteristics of CAVs. As it is a continuous problem, various situations that CAVs arrive at intersections are analyzed. The rules are discovered to simplify the problem by discretization method.

A case study is conducted via SUMO traffic simulation program. The results show that the efficiency of CAVs can be improved significantly both in high-volume scenario and medium-volume scenario with the plan optimized by the model proposed in this paper. At the same time, the progression efficiency of regular vehicles is not affected significantly. It is indicated that full-scale benefits of dedicated CAV lanes can only be achieved with signal coordination plans considering CAV characteristics.

To the best of the authors’ knowledge, this is the first research that develops a signal coordination model for arteries with dedicated CAV lanes.

Heterogeneous traffic in Delhi is complex to understand due its typical composition, speed acceleration, cruising, deceleration and idling activity in flow. To arrive at accurate emission factor estimates and implement proper traffic demand management there is need to understand microscopic vehicle operation activity. The vehicular operations are easily quantified by understanding driving cycle of the particular vehicle in real world driving conditions. The purpose of this paper is to present a study on the understanding of driving conditions in India that are heterogeneous in nature.

To understand the heterogeneity, the driving cycle data were collected using GPS on different types of both motorised and non‐motorized modes of transport, e.g. car, auto rickshaw, bus, motorcycle and cycle rickshaw and bicycle on different traffic corridors in Delhi.

Research findings show that driving cycles differ for different types of vehicles. Therefore, each mode should be encouraged based on their average speed‐time sequence in any traffic mix. The real‐world driving cycle will be also useful for the understanding of fuel consumption and emissions in real‐world scenarios, in order to control vehicle emissions properly, achieve fuel efficiency and to obtain a more sustainable transport system.

This type of research has not been carried out previously in any Indian city.

This paper aims to present a cooperative adaptive cruise control, called stable smart driving model (SSDM), for connected and autonomous vehicles (CAVs) in mixed traffic streams with human-driven vehicles.

Considering the linear stability, SSDM is able to provide smooth deceleration and acceleration in the vehicle platoons with or without cut-in. Besides, the calibrated Virginia tech microscopic energy and emission model is applied in this study to investigate the impact of CAVs on the fuel consumption of the vehicle platoon and traffic flows. Under the cut-in condition, the SSDM outperforms ecological SDM and SDM in terms of stability considering different desired time headways. Moreover, single-lane vehicle dynamics are simulated for human-driven vehicles and CAVs.

The result shows that CAVs can reduce platoon-level fuel consumption. SSDM can save the platoon-level fuel consumption up to 15%, outperforming other existing control strategies. Considering the single-lane highway with merging, the higher market penetration of SSDM-equipped CAVs leads to less fuel consumption.

The proposed rule-based control method considered linear stability to generate smoother deceleration and acceleration curves. The research results can help to develop environmental-friendly control strategies and lay the foundation for the new methods.

There is lack of knowledge about how the existing streets need to be redesigned and the infrastructural changes that need to be made to adopt autonomous vehicles. The purpose of this study is to investigate the infrastructure requirements of autonomous vehicles in terms of (1) lane widths, (2) parking spaces, (3) drop-off zones and (4) other facilities, followed by analyzing them and suggesting changes in the existing urban design of Msheireb Downtown Doha (MDD).

Mixed method of combining both qualitative (secondary research of analyzing the existing data about the urban design guidelines for an autonomous future, observations of the existing infrastructure) and quantitative methods (on-site measurements of pedestrian walkways and road lane widths) is used.

The outcome of the research consists of a series of major infrastructural changes with regard to lane widths, parking spaces, pick-up and drop-off zones and other facilities needed for the deployment of autonomous vehicles.

The results imply that Qatar can benefit by adopting the proposed urban design suggestions for the implementation of autonomous vehicles on the streets of MDD in particular, and smart cities of Qatar and the region in general.

The proposed changes can work as a reference and serve as a possible setting for addressing Autonomous Vehicle preparations in emerging cities.

The proposed urban design changes can be adapted for an autonomous future in emerging cities.

Purpose – This chapter reviews planning and design approaches for cycle traffic in order to direct future thinking towards the critical aspects of network design that will have a beneficial impact on the utility and nature of the environment for cycling.

Approach – This chapter provides a critique of the approach of adopting a so-called hierarchy of solutions frequently adopted in western countries with low levels of cycling use.

Findings – The guiding principle for designing routes for cycle traffic is that the bicycle is a vehicle capable of speed and, as a consequence, links and junctions need to be designed according to appropriate geometric design standards. In addition, owing to the nature of the cycle and rider combination, the oft repeated Dutch characteristics for good design for cycle traffic of coherence, directness, attractiveness, safety and comfort remain firm.

Practical implications – The practical implications of the outcomes from the chapter are a method of approach for planning infrastructure for cycle traffic which starts with an analysis of demand and works through to the creation of suitable networks for cycle traffic which are grounded in, and extended from, suitably regulated existing highway networks.

Social implications – An extensive transport system suitable in nature for cycle traffic will attract a wide base of users and consequently allow for the benefits of cycling to be captured.

Value of chapter – The value of the chapter rests in its emphasis on the need to treat cycling as a distinct transport mode and, consequentially, planning and engineering needs to be undertaken in a way conducive to providing the basic necessary infrastructure for such a distinct mode.

The purpose is to enhance the capabilities of a general‐purpose IDS solution with additional knowledge of multimedia file formats and protocols, to better handle multimedia‐specific security exploits.

The authors have designed a multimedia traffic classifier, implemented as an optional preprocessor for Snort. The solution has been successfully tested with downloading and streaming traffic.

Test results confirm that the additional specialized knowledge encoded in the preprocessor results in two significant gains: trusted multimedia contents can be identified and allowed to bypass the detection engine, with substantial computational savings; the IDS is now able to detect multimedia‐specific exploits which would otherwise go unnoticed.

Not all multimedia‐related scenarios have been covered by the described implementation yet. The proposed solution is being extended to other file types and protocols, fine‐tuned, as well as tested more extensively.

Snort users interested in this work will be able to add the multimedia‐specific functionality – and enjoy the resulting benefits – with minimal effort.

The research reported in this paper is – to the authors' knowledge – the first effort to add multimedia‐specific knowledge to the operation of an IDS. In addition to being innovative, the proposed method is relevant for more than one reason, since it enhances the IDS capabilities while at the same time alleviating the computational cost of performing detailed traffic analysis in high‐speed networks.