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7.1. Conclusions

This research analysed the influence of heavy vehicle management strategies on traffic performance measures (average speeds, average travel times and average delay times). Two main strategies were proposed in this thesis to address the issue of reducing traffic congestion caused by heavy vehicles. The first heavy vehicle management strategy proposed in this research was signal coordination. From existing studies, it was found that signal coordination is often done based on the operational characteristics (e.g. speed, acceleration, deceleration) of only passenger cars. This research analysed the influence of having a signal coordination program which takes into consideration the operational characteristics (e.g. speed, acceleration, deceleration) of heavy vehicles as well. The second heavy vehicle management strategy which was analysed in the thesis was heavy vehicle lane restriction strategies. The influence of both time and space restriction strategies had been examined through previous studies. However, heavy vehicles vary in their physical characteristics (e.g. size, length) based on their type. Therefore, a restriction strategy which targeted different types of heavy vehicles was analysed in this research. The key conclusions from each of the management strategies are summarised in the following subsections.

7.1.1. Signal Coordination

In this research, signal coordination was examined to assess its validity as an efficient method to reduce congestion caused by heavy vehicles. Three different signal coordination set-ups

81 were used in this research. The first set-up targeted passenger cars as the main beneficiary of signal coordination. The second set-up targeted heavy vehicles as the main beneficiary of signal coordination. The third and final set-up targeted all vehicles on the corridor. The influence of signal coordination was evaluated at high heavy vehicle compositions, then the heavy vehicle composition was increased at 5% increments reaching up to a 30% heavy vehicle composition. Increasing the heavy vehicle compositions tested the ability of signal coordination to cope with the increased number of heavy vehicles in the corridor. The influence of signal coordination on reducing traffic congestion can be summarised below: ❖ Signal coordination proved to be an efficient heavy vehicle management strategy.

Utilising the optimal signal coordination set-up yielded positive results in terms of the traffic performance measures evaluated in this research. In addition, the positive impacts of signal coordination were increased as the heavy vehicle composition was increased. This shows that reducing congestion caused by even high heavy vehicle compositions is achievable, with the appropriate signal coordination set-up put in place.

❖ The influence of signal coordination on 6 different heavy vehicle compositions was evaluated. Positive results in terms of the traffic performance measures were yielded for all vehicle types. This result shows that applying the appropriate signal coordination set-up can improve the performance of all vehicle types present in the network and not just passenger cars.

❖ The main distinction which differentiates signal coordination from restriction strategies is the fact that no vehicle type is being restricted from using the corridor. This means that logistics and transportation services will not be affected by the implementation of this heavy vehicle management strategy.

7.1.2. Restriction Strategies

In this research, three restriction strategies were evaluated in this thesis. Each restriction strategy restricted a certain type of heavy vehicle. The heavy vehicle types were categorised

82 based on the guidelines used in the state of Victoria, Australia. The first restriction strategy banned multi combination vehicles from using the corridor. The second restriction strategy banned multi and heavy combination vehicles from using the corridor. The third restriction strategy banned all heavy vehicles from using the corridor. The influence of the restriction strategies can be summarised below:

❖ Restriction strategies were applied to a peak and off-peak period to evaluate their influence throughout the day. From the results that were yielded for both time periods, it is recommended that restriction strategies are applied only in the morning peak period. However, the results yielded from the off-peak period indicate that restriction strategies are effective in the case of a very high heavy vehicle composition.

❖ The application of a multi combination restriction strategy provided minimalistic results when compared to the other two restriction strategies. Based on this conclusion, it is not recommended to apply such a restriction strategy which bans only multi combination vehicles.

❖ A multi and heavy combination restriction strategy provided improvements to the corridor in terms of the traffic performance measures (average speeds, average travel times and average delay times). Restriction of all heavy vehicles was comprehensibly the most effective restriction strategy in the peak period. Based on these results, it can be concluded that both restriction strategies (multi and heavy combination restriction strategy, as well as restricting all heavy vehicles) can be taken into consideration to reduce traffic congestion caused by heavy vehicles.

❖ In terms of influence on the traffic performance measures (average speeds, average travel times and average delay times) that were used in this study, restricting all heavy vehicles was the most effective heavy vehicle management strategy. However, restricting all heavy vehicles from using the corridor will cause an impact on the transportation and logistics services to find alternative routes for their fleets.

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7.2. Contributions

This research has provided detailed evaluation of the influence of two different heavy vehicle management strategies: signal coordination (Chapter 5) and restriction strategies (Chapter 6). The contribution of each is outlined as follows:

❖ From examining existing studies, signal coordination mostly appears to reduce congestion caused by passenger cars. This research showed that signal coordination can be used as a heavy vehicle management method on a highway with interrupted traffic flows and during congestion. In addition, this research also showed that signal coordination is capable of handling high heavy vehicle compositions.

❖ Restriction strategies have been used globally for a long period of time, and their influence is mostly positive when they are applied. However, this research has provided insight on the influence of a vehicle type restriction strategy. The main reason for proposing such a restriction strategy was to differentiate between the types of heavy vehicles and provide a clear picture of the influence that each heavy vehicle type poses on the surrounding traffic.

The results show how signal coordination and heavy vehicle restriction strategies can influence traffic congestion and improve road serviceability. However, the two management strategies applied to this case study can be applied to any other corridor with interrupted traffic flows.

7.3. Future Research

❖ Regarding future directions to the outcomes of this research; a cost analysis could be conducted on each of the restriction strategies. It should be mentioned that transportation and logistics industries would be the most affected entities if such strategies are applied. Therefore, having an understanding or forecast regarding the costs involved with applying such strategies would prove beneficial to transportation and logistics industries.

84 ❖ Reduction of environmental pollutants caused by vehicles is always heavily associated with the advantages of signal coordination. The influence of signal coordination was measured only in terms of the traffic performance measures (average speeds, average travel times and average delay times) in this research. Therefore, evaluating the influence of signal coordination on vehicular emissions will prove beneficial.

❖ Demand data was not used in this research since it was out of the study’s scope; therefore, a similar study which incorporates demand data would prove beneficial. In addition, optimisation of either restriction strategies was not implemented. Selecting the most efficient management strategy and applying optimisation to it would be considered as a major step forward in this research.

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